技术领域technical field
本发明涉及航空领域，尤指一种空中交通管制扇区运行性能综合检测方法及系统。The invention relates to the field of aviation, in particular to a method and system for comprehensively detecting the operating performance of an air traffic control sector.
背景技术Background technique
伴随着航空运输业的发展，为了保证各类飞行活动的安全和有序，空中交通管制服务应运而生并不断得到发展完善，至20世纪80年代趋于成熟。现代空中交通管制服务的主要内容是：空中交通管制员(简称为“管制员”，下同)依托现代通信、导航、监视技术，对所辖航空器实施管理和控制，协调和指导其运动路径和模式，以防止空中航空器与航空器相撞及在机场机动区内航空器与障碍物相撞，维护和加快空中交通的有序流动。空中交通管制扇区(简称为“管制扇区”，下同)是空中交通管制(简称为“管制”，下同)的基本空间单元。一般情况下，为航空器提供空中交通管制服务的空域被划设为若干管制扇区，每个管制扇区对应一个管制员工作席位。管制扇区运行性能是管制扇区内航空器运行态势的技术性指标提炼，既反映管制员对所辖管制扇区提供管制服务的质量和水准，又反映特定管制空域使用效能。因此，对管制扇区运行性能的有效检测是调整管制运行策略、优化管制空域结构的基础和前提。With the development of the air transport industry, in order to ensure the safety and order of various flight activities, the air traffic control service came into being and was continuously developed and improved until it became mature in the 1980s. The main content of modern air traffic control services is: Air traffic controllers (referred to as "controllers", the same below) rely on modern communication, navigation, and surveillance technologies to manage and control aircraft under their jurisdiction, coordinate and guide their movement paths and Mode to prevent collisions between aircraft in the air and collisions between aircraft and obstacles in the maneuvering area of the airport, and maintain and speed up the orderly flow of air traffic. The air traffic control sector (referred to as "control sector", the same below) is the basic spatial unit of air traffic control (referred to as "control", the same below). Generally, the airspace providing air traffic control services for aircraft is divided into several control sectors, and each control sector corresponds to a controller job seat. The operational performance of a control sector is the extraction of technical indicators of the aircraft operating situation in the control sector, which not only reflects the quality and level of control services provided by the controllers to the control sector under their jurisdiction, but also reflects the use efficiency of specific controlled airspace. Therefore, the effective detection of the operational performance of the control sector is the basis and premise for adjusting the control operation strategy and optimizing the structure of the control airspace.
比如，公开号为CN104332073A的专利文献在2015-02-04公开了一种智能空中交通管制系统，包括数据接收接口模块、数据处理中心、应急超控模块、电子飞行计划显示模块、航班监控显示模块和航班控制指令发送模块。通过接收飞机准确的实时飞行信息，数据处理中心即可展开飞行计划的精确计算，并优化整个飞行队列，如缩短飞机间距，合理调配对应跑道的起降顺序，实时更改着陆角，曲线进近等，有效提高整个飞行队列的效率，加强安全性。最终，整个飞行计划将显示在管制员的监控显示器上。航空管制员可以随时通过显示器观察飞行队列起飞着陆的优先顺序，并通过更改飞机起飞/着陆航迹，航速等参数，调整队列顺序。从而提高机场通勤率，提高管制员的工作效率。For example, the patent document whose publication number is CN104332073A discloses an intelligent air traffic control system on 2015-02-04, including a data receiving interface module, a data processing center, an emergency override module, an electronic flight plan display module, and a flight monitoring display module and flight control instruction sending module. By receiving the accurate real-time flight information of the aircraft, the data processing center can carry out accurate calculation of the flight plan and optimize the entire flight queue, such as shortening the distance between aircraft, reasonably adjusting the take-off and landing sequence of the corresponding runway, changing the landing angle in real time, and curved approach, etc. , effectively improve the efficiency of the entire flight queue and enhance safety. Eventually, the entire flight plan will be displayed on the controller's monitoring display. Air traffic controllers can observe the priority order of flight queues for takeoff and landing through the display at any time, and adjust the queue order by changing parameters such as aircraft takeoff/landing track and speed. Thereby improving the airport commuting rate and improving the work efficiency of controllers.
但即便如此，目前针对空中交通管制扇区运行性能的研究较少，大部分研究主要体现在以下几个孤立方面：(1)空中交通流密度，分为战略和战术两层面，其中前者主要体现为空域复杂性指标，后者主要体现为管制单元空中交通拥挤程度判定。目前，空中交通流密度指标在应用上仍以管制单元的航空器架次统计作为主要呈现。(2)管制运行安全性能，包括定量和定性两方面。定量方面，国际民航组织(ICAO)依据碰撞风险分析制定的总的安全目标等级(TLS)是1.5×10-8次致命飞行事故/飞行小时，而我国民航空管系统根据危险接近风险分析将事故征候万架次率作为关键安全指标。定性方面，ICAO推荐采用威胁差错管理(ThreatandErrorManagement，TEM)或日常运行安全监测(NormalOperationsSafetySurvey，NOSS)方法，实施定性的管制运行安全性能评价。国内学者围绕人、机、环、管理等4类因素分别建立了安全风险评估指标体系，并开展了指标权重分析。(3)管制运行效率性能，主要围绕航班延误指标方面。目前，国外航班延误统计指标涉及延误架次率及延误时间。我国民航欠缺航班延误时间的细化统计，在航班延误原因界定、统计指标设计、统计方法及流程等方面亟待改善。(4)管制员工作负荷，是管制扇区容量评估的重要考量。国外学者从生理/行为特征、主观测评、工作细分的角度，分别提出了电击皮肤的反应、心率、心电图、血压、体液等生理指标，设备操作次数、陆空通话时间记录等行为指标；ATWIT技术、NASA–TLX量表、SWAT量表和MCH法等主观测评技术；DORATASK、MBB法、RAMS法等衡量管制员工作时间的方法。国内学者发展了主观测评方法，提出了基于可拓学的管制员工作负荷评价模型。But even so, there are few studies on the operational performance of air traffic control sectors, most of which are mainly reflected in the following isolated aspects: (1) air traffic flow density, which is divided into strategic and tactical levels, of which the former mainly reflects is the airspace complexity index, and the latter is mainly reflected in the judgment of the air traffic congestion degree of the control unit. At present, the application of air traffic flow density indicators is still mainly presented by the statistics of aircraft sorties in control units. (2) Regulate operational safety performance, including both quantitative and qualitative aspects. Quantitatively, the International Civil Aviation Organization (ICAO) based on the collision risk analysis established a total safety target level (TLS) of 1.5×10-8 fatal flight accidents/flight hour, while China’s civil aviation control system The rate of 10,000 sorties is regarded as a key safety indicator. Qualitatively, ICAO recommends the use of Threat and Error Management (TEM) or Normal Operations Safety Survey (NOSS) methods to implement qualitative regulatory operational safety performance evaluations. Domestic scholars have established safety risk assessment index systems around the four factors of human, machine, environment, and management, and carried out index weight analysis. (3) Control the performance of operational efficiency, mainly around flight delay indicators. At present, the statistical indicators of foreign flight delays involve the delay rate and delay time. my country's civil aviation lacks detailed statistics of flight delay time, and it is urgent to improve in the definition of flight delay reasons, statistical index design, statistical methods and procedures. (4) The controller workload is an important consideration in the evaluation of the capacity of the control sector. From the perspective of physiological/behavioral characteristics, subjective evaluation, and work subdivision, foreign scholars have proposed physiological indicators such as skin response to electric shock, heart rate, electrocardiogram, blood pressure, and body fluids, as well as behavioral indicators such as equipment operation times, land and air call time records; ATWIT Technology, NASA-TLX scale, SWAT scale and MCH method and other subjective evaluation techniques; DORATASK, MBB method, RAMS method and other methods to measure the working time of controllers. Domestic scholars have developed subjective evaluation methods and proposed a controller workload evaluation model based on extenics.
例如，公开号为CN104636890A的专利文献在2015-05-20公开了一种空中交通管制员工作负荷测量方法，包括：步骤A：确定管制负荷测量指标，该管制负荷测量指标包括眼动指标和语音指标；步骤B：实时记录各眼动指标对应的眼动指标数据，以及各语音指标对应的语音指标数据；步骤C：对记录的眼动指标数据进行因子分析，计算出眼动指标数据的眼动综合因子；步骤D：以眼动综合因子和语音指标为输入因素，管制综合指标值为输出因素，建立管制负荷回归模型。该方法能够实时、无干扰的测量管制员的综合指标，实用性强。For example, the patent document whose publication number is CN104636890A discloses a method for measuring the workload of air traffic controllers on 2015-05-20, including: Step A: determining the control load measurement index, the control load measurement index includes eye movement index and voice index; step B: record the eye movement index data corresponding to each eye movement index in real time, and the voice index data corresponding to each voice index; step C: perform factor analysis on the recorded eye movement index data, and calculate the eye movement index data of the eye movement index data; The comprehensive factor of movement; step D: take the comprehensive factor of eye movement and voice index as the input factor, and the comprehensive index value of control as the output factor, and establish the control load regression model. The method can measure the comprehensive index of the controller in real time and without interference, and has strong practicability.
但该方法参考的数据比较局限，指标维度单一，不够全面、综合，该测量方法仅利用局限的数据片面的对管制员工作负荷进行了测量，存在一定的局限性，预测可靠度不高。However, the data referenced by this method is relatively limited, the index dimension is single, and it is not comprehensive and comprehensive enough. This measurement method only uses limited data to measure the workload of controllers one-sidedly, which has certain limitations and the prediction reliability is not high.
发明内容Contents of the invention
本发明提供一种可以提高扇区性能的检测结果的可靠性的空中交通管制扇区运行性能检测方法和系统。The invention provides an air traffic control sector operation performance detection method and system which can improve the reliability of the sector performance detection result.
本发明的目的是通过以下技术方案来实现的：The purpose of the present invention is achieved through the following technical solutions:
一种扇区运行性能综合检测方法，包括步骤：A comprehensive detection method for sector operating performance, comprising the steps of:
步骤1：输入历史扇区运行性能指标数据，包括扇区通行性检测指标、扇区复杂性检测指标、扇区安全性检测指标、扇区经济性检测指标和管制员工作负荷检测指标；Step 1: Input historical sector operation performance index data, including sector traffic detection index, sector complexity detection index, sector security detection index, sector economy detection index and controller workload detection index;
步骤2：基于聚类分析模型处理历史扇区运行性能指标数据，建立扇区运行性能档案；Step 2: Based on the cluster analysis model, process the historical sector operation performance index data, and establish sector operation performance files;
步骤3：输入当前扇区运行性能指标数据，对照扇区运行性能档案寻找最大相似类，以此判断扇区运行性能等级，并计算得到最小相似度；Step 3: Input the current sector operation performance index data, and compare the sector operation performance files to find the largest similar class, so as to judge the sector operation performance level, and calculate the minimum similarity;
步骤4：根据最小相似度确定是否触发扇区异常运行响应告警。Step 4: Determine whether to trigger a sector abnormal operation response alarm according to the minimum similarity.
进一步的，所述步骤1中的所述扇区通行性检测指标为扇区流量、扇区航行里程、扇区航行时间和扇区交通流密度；Further, the sector accessibility detection indicators in the step 1 are sector flow, sector mileage, sector voyage time and sector traffic flow density;
所述扇区复杂性检测指标为扇区航空器爬升次数、扇区航空器下降次数、扇区航空器改速次数、扇区航空器改航次数；The sector complexity detection index is the number of climb times of sector aircraft, the number of times of descent of sector aircraft, the number of times of speed change of sector aircraft, and the number of times of sector aircraft diversion;
所述扇区安全性检测指标为扇区短期冲突告警频率和扇区最低安全高度告警频率；The sector safety detection index is the sector short-term conflict warning frequency and the sector minimum safety altitude warning frequency;
所述扇区经济性检测指标为扇区饱和度、扇区排队长度、扇区航空器延误架次率、扇区航空器延误时间、扇区航空器平均延误时间；The sector economy detection index is sector saturation, sector queuing length, sector aircraft delay rate, sector aircraft delay time, and sector aircraft average delay time;
所述管制员工作负荷检测指标为陆空通话信道占用率、陆空通话次数。The controller workload detection indicators are the land-air call channel occupancy rate and the number of land-air call calls.
进一步的，在所述步骤1与步骤2之间还包括对历史扇区运行性能指标数据进行无量纲化处理，具体过程如下：Further, between step 1 and step 2, it also includes dimensionless processing of historical sector operation performance index data, and the specific process is as follows:
令第i个样本的第j项指标的实际值为xi,j，yi,j为无量纲化处理后的指标值，为第j项指标的均值，sj为第j项指标的标准差，则对于正向指标，对于逆向指标，先取其倒数或取负使其正向化，再使用上述公式对其进行无量纲化处理。Let the actual value of the j-th index of the i-th sample be xi,j , and yi,j be the index value after dimensionless processing, is the mean value of the j-th index, sj is the standard deviation of the j-th index, then for the positive index, For the reverse index, first take its reciprocal or negative to make it positive, and then use the above formula to make it dimensionless.
进一步的，所述步骤2具体包括如下过程：Further, the step 2 specifically includes the following process:
步骤2.1：根据预设的聚类数目k对历史扇区运行性能指标数据点进行分类，形成k个初始类，并确定每一初始类中心结点；Step 2.1: According to the preset number k of clusters, classify the data points of historical sector operation performance indicators to form k initial clusters, and determine the central node of each initial cluster;
步骤2.2：计算历史扇区运行性能指标数据中的每个数据点到k个初始类中心结点之间的欧几里德距离，并根据距离类中心结点最短的原则将所有的数据进行重新分类形成k个类；Step 2.2: Calculate the Euclidean distance between each data point in the historical sector operation performance index data and the k initial class center nodes, and recreate all the data according to the principle of the shortest distance to the class center nodes Classify to form k classes;
步骤2.3：依次计算各类变量的均值，并以均值作为新的k个类的类中心结点；Step 2.3: Calculate the mean value of various variables in turn, and use the mean value as the class center node of the new k classes;
步骤2.4：计算新确定的类中心结点距上一个类中心结点之间的偏移量，当最大偏移量大于设定值时，返回分类模块，否则聚类结束得到k个类，从而得到扇区正常运行性能档案。Step 2.4: Calculate the offset between the newly determined class center node and the previous class center node. When the maximum offset is greater than the set value, return to the classification module, otherwise the clustering ends and k classes are obtained, so that Get sector normal operation performance file.
进一步的，所述步骤3具体包括如下步骤：Further, the step 3 specifically includes the following steps:
步骤3.1：实时数据输入与标准化：Step 3.1: Real-time data entry and normalization:
获取当前扇区运行性能的上述17项指标数据r＝{rj,j＝1,2,...,17}，tj为无量纲化处理后的第j项指标值，为第j项指标的均值，sj为第j项指标的标准差，则对于正向指标，对于逆向指标，先取其倒数或取负使其正向化，再使用上述公式对其进行无量纲化处理；Obtain the above-mentioned 17 index data r={rj ,j=1,2,...,17} of the current sector operating performance, tj is the jth index value after dimensionless processing, is the mean value of the j-th index, sj is the standard deviation of the j-th index, then for the positive index, For the reverse index, first take its reciprocal or negative to make it positive, and then use the above formula to perform dimensionless processing;
其中均值和标准差从扇区运行性能档案中提取；The mean and standard deviation are extracted from the sector’s operating performance archives;
步骤3.2：最大相似类寻找：Step 3.2: Maximum Similarity Class Finding:
计算检测数据无量纲化指标值t与扇区运行性能档案中各个类的类中心点Ck的相似度sim(t,Ck)，并求得与扇区运行性能档案中k个类中心点的最大相似度simm(t,Ck)及其类Class(k)，其中sim(t,Ck)可记为：Calculate the similarity sim(t,Ck ) between the dimensionless index value t of the detection data and the class center point Ck of each class in the sector operating performance file, and obtain the k class center points in the sector operating performance file The maximum similarity simm (t,Ck ) and its class Class(k), where sim(t,Ck ) can be written as:
其中，tj为检测数据无量纲化后第j项指标值，ck,j为第k个类中心点的第j项无量纲化指标值；Among them, tj is the index value of the jth item after the detection data is dimensionless, and ck,j is the dimensionless index value of the jth item of the kth class center point;
当前扇区运行性能等级即以扇区运行性能档案中的最大相似类确定。The current sector operating performance level is determined by the largest similar class in the sector operating performance file.
步骤3.3：最小相似度计算：Step 3.3: Minimum similarity calculation:
计算t与所属Class(k)中各样本无量纲化数据的相似度，得到最大相似类中的最小相似度minSim。Calculate the similarity between t and the dimensionless data of each sample in Class(k) to which it belongs, and obtain the minimum similarity minSim in the largest similar class.
进一步的，步骤4：若计算得到的minSim与预设的阈值进行比较，minSim超过预先设定的相似度阈值，则判断扇区运行性能情况异常，并进行扇区异常运行响应告警。Further, Step 4: If the calculated minSim is compared with the preset threshold, and the minSim exceeds the preset similarity threshold, it is judged that the sector operation performance is abnormal, and an abnormal sector operation response alarm is issued.
一种空中交通管制扇区运行性能检测系统，包括：An air traffic control sector operational performance detection system, comprising:
扇区运行性能档案创建模块，根据聚类分析后的历史扇区运行性能指标数据创建扇区运行性能档案；The sector operation performance file creation module creates a sector operation performance file according to the historical sector operation performance index data after cluster analysis;
检测模块：根据输入的当前扇区运行性能指标数据，对照扇区运行性能档案计算得到最大相似类和最小相似度，并根据最小相似度判断扇区运行性能是否异常。Detection module: according to the input current sector performance index data, calculate the maximum similarity class and the minimum similarity according to the sector performance file, and judge whether the sector performance is abnormal according to the minimum similarity.
进一步的，所述扇区运行性能档案创建模块包括聚类分析单元和创建单元，所述聚类分析单元用于对输入的，经过无量纲化处理的历史扇区运行性能指标数据进行聚类分析处理，所述创建模块用于根据聚类分析处理得到的结果创建扇区运行性能档案；Further, the sector operation performance file creation module includes a cluster analysis unit and a creation unit, and the cluster analysis unit is used to perform cluster analysis on the input, dimensionless historical sector operation performance index data Processing, the creation module is used to create sector operating performance files according to the results obtained by cluster analysis processing;
所述检测模块包括相似度处理单元，所述相似度处理单元根据输入的当前扇区运行性能指标数据，以及扇区运行性能档案计算最大相似类和最小相似度；The detection module includes a similarity processing unit, and the similarity processing unit calculates the maximum similarity class and the minimum similarity according to the input current sector operation performance index data and the sector operation performance file;
所述空中交通管制扇区运行性能检测系统还包括耦合于所述相似度处理单元的警告模块；若计算得到的最小相似度符合预设条件，则所述警告模块响应警告；The air traffic control sector operation performance detection system also includes a warning module coupled to the similarity processing unit; if the calculated minimum similarity meets preset conditions, the warning module responds to the warning;
所述空中交通管制扇区运行性能检测系统还包括管制扇区运行性能检测数据库、以及分别耦合于所述管制扇区运行性能检测数据库的数据引接模块和管制扇区运行性能指标检测模块；所述数据接引模块包括电报数据接口、综合航迹数据接口和管制语音数据接口；所述管制扇区运行性能指标检测模块用于采集扇区通行性指标、扇区复杂性指标、扇区安全性指标、扇区经济性指标和管制员工作负荷指标；The air traffic control sector operation performance detection system also includes a control sector operation performance detection database, and a data connection module and a control sector operation performance index detection module respectively coupled to the control sector operation performance detection database; The data connection module includes a telegram data interface, an integrated track data interface and a control voice data interface; the control sector operation performance index detection module is used to collect sector traffic indicators, sector complexity indicators, and sector security indicators , sector economic indicators and controller workload indicators;
所述管制扇区运行性能检测数据库耦合于所述扇区运行性能档案创建模块和检测模块的输入端。The control sector operation performance detection database is coupled to the sector operation performance file creation module and the input end of the detection module.
本方案采用定量研究方法，将影响扇区运行性能的多维度指标进行全面、综合考虑，从而实现对扇区运行性能的有效检测；所设计的空中交通管制扇区运行性能检测系统，能够应用于工程单位，具有很强的操作性。This program adopts the quantitative research method, comprehensively and comprehensively considers the multi-dimensional indicators that affect the operation performance of the sector, so as to realize the effective detection of the operation performance of the sector; the air traffic control sector operation performance detection system designed can be applied to Engineering unit with strong operability.
本发明由于采用定量分析方法，通过对海量运行数据的不间断检测和计算分析，并依靠对历史扇区运行性能指标数据的挖掘，获取指标数据与扇区运行性能情况之间的关系，克服了现有技术定性研究较多，定量研究较少，导致客观性不足的情况；不仅从反映管制员工作负荷的指标下手，同时综合考虑其他影响检测结果的影响因子，将影响扇区运行性能的多维度指标进行全面、综合考虑，能够实现对扇区运行性能情况的有效检测，检测可靠性得以保证；而且，通过对大量管制扇区运行性能实际数据进行聚类分析，能提取管制扇区运行性能特征，建立扇区运行性能档案；更为重要的是，本发明全面、综合地涵盖了管制扇区运行性能的各类影响因素，能够满足空中交通管制单位对扇区运行性能情况进行实时检测和告警的实际需求，对于提升管制运行管理水平、优化管制空域结构具有数据支持作用。Due to the adoption of the quantitative analysis method, the present invention obtains the relationship between the index data and the operating performance of the sector through uninterrupted detection and calculation analysis of massive operating data, and relies on the mining of historical sector operating performance index data, thereby overcoming the There are many qualitative studies and few quantitative studies in the existing technology, which leads to the lack of objectivity; not only starting from the indicators reflecting the workload of the controllers, but also comprehensively considering other influencing factors that affect the detection results, will affect the performance of the sector. Comprehensive and comprehensive consideration of the dimension indicators can realize the effective detection of the operating performance of the sector, and the reliability of the detection can be guaranteed; moreover, by clustering and analyzing the actual data of the operating performance of a large number of controlled sectors, the operating performance of the controlled sector can be extracted. features, and establish sector performance files; more importantly, the present invention comprehensively and comprehensively covers all kinds of influencing factors of control sector performance, and can satisfy air traffic control units in real-time detection and analysis of sector performance conditions. The actual demand for warnings has a data support effect on improving the level of control operation management and optimizing the structure of control airspace.
附图说明Description of drawings
图1是本发明实施例一的一种空中交通管制扇区运行性能检测方法的流程图；Fig. 1 is a flow chart of a method for detecting the operational performance of an air traffic control sector in Embodiment 1 of the present invention;
图2是本发明一个优选实施例的一种空中交通管制扇区运行性能检测方法的流程图；Fig. 2 is a flow chart of a method for detecting the operational performance of an air traffic control sector in a preferred embodiment of the present invention;
图3是本发明实施例二的一种空中交通管制扇区运行性能检测系统的示意图；3 is a schematic diagram of an air traffic control sector operating performance detection system according to Embodiment 2 of the present invention;
图4是本发明另一个优选实施例的一种空中交通管制扇区运行性能检测系统的示意图；Fig. 4 is a schematic diagram of an air traffic control sector operating performance detection system of another preferred embodiment of the present invention;
图5是本发明实施例二的一种空中交通管制扇区运行性能检测系统的逻辑结构图；5 is a logical structure diagram of an air traffic control sector operating performance detection system according to Embodiment 2 of the present invention;
图6是本发明实施例二的系统对应的网络结构图；FIG. 6 is a network structure diagram corresponding to the system of Embodiment 2 of the present invention;
图7是本发明实施例二的系统对应的功能结构图；FIG. 7 is a functional structure diagram corresponding to the system of Embodiment 2 of the present invention;
图8是本发明实施例二的综合航迹数据接口，对应的综合航迹数据采集功能结构图；Fig. 8 is the integrated track data interface of the second embodiment of the present invention, and the corresponding integrated track data acquisition functional structure diagram;
图9是本发明实施例二的管制语音数据接口对应的语音数据采集流程图；FIG. 9 is a flow chart of voice data collection corresponding to the control voice data interface in Embodiment 2 of the present invention;
图10是本发明实施例二的电报数据接口对应的电报数据采集功能结构图；Fig. 10 is a structural diagram of the telegram data acquisition function corresponding to the telegram data interface of Embodiment 2 of the present invention;
图11是本发明实施例一扇区异常运行性能告警。Fig. 11 is an alarm of abnormal operation performance of a sector according to an embodiment of the present invention.
其中，1：扇区运行性能档案创建模块；2、检测模块；3、警告模块；4、管制扇区运行性能检测数据库；5、数据引接模块；6、扇区性能检测指标数据检测模块；11、聚类分析单元；12、创建单元；13、相似度处理单元；100、空中交通管制扇区运行性能检测系统。Among them, 1: sector operation performance file creation module; 2. detection module; 3. warning module; 4. control sector operation performance detection database; 5. data connection module; 6. sector performance detection index data detection module; 11 1. Cluster analysis unit; 12. Creation unit; 13. Similarity processing unit; 100. Air traffic control sector operation performance detection system.
具体实施方式detailed description
对管制扇区运行性能的有效检测是调整管制运行策略、优化管制空域结构的基础和前提。The effective detection of the operational performance of the control sector is the basis and premise for adjusting the control operation strategy and optimizing the structure of the control airspace.
目前针对空中交通管制扇区运行性能的既有研究内容，主要存在以下不足：(1)研究方法方面，定性研究较多，定量研究较少，客观性不足。(2)检测指标方面，指标维度较为单一，不够全面、综合，导致综合检测能力不足。(3)应用性方面，既有研究仍停留在实验室研究阶段，主要服务于战略决策，而面向空中交通管制单位的实际工程应用少。由于上述不足，导致目前国内外对于管制扇区运行性能检测的研究在客观性、全面性、可操作性等方面均有所欠缺，特别是对于实际中需要对管制扇区运行性能进行实时检测和响应告警这一需求，尚未有效实现。At present, the existing research contents on the operational performance of the air traffic control sector mainly have the following deficiencies: (1) In terms of research methods, there are more qualitative researches, less quantitative researches, and insufficient objectivity. (2) In terms of detection indicators, the index dimension is relatively single, not comprehensive and comprehensive, resulting in insufficient comprehensive detection capabilities. (3) In terms of applicability, existing research is still at the stage of laboratory research, which mainly serves strategic decision-making, while there are few actual engineering applications for air traffic control units. Due to the above deficiencies, the current domestic and foreign research on the performance detection of the control sector is lacking in objectivity, comprehensiveness, and operability. The need to respond to alarms has not been effectively implemented.
因此，本专利所采用的定量研究的方法，能够将影响管制扇区运行性能的各指标，全面、综合的进行考虑，同时，保证检测效率高效。所设计的管制扇区运行性能综合检测方法和系统，能够应用于工程单位，具有很强的操作性。Therefore, the quantitative research method adopted in this patent can comprehensively and comprehensively consider various indicators that affect the operation performance of the control sector, and at the same time, ensure high detection efficiency. The designed comprehensive detection method and system for the operation performance of the control sector can be applied to engineering units and has strong operability.
下面结合附图和较佳的实施例对本发明作进一步说明。The present invention will be further described below in conjunction with the accompanying drawings and preferred embodiments.
实施例一：Embodiment one:
图1是本发明实施例一的一种空中交通管制扇区运行性能检测方法的流程图，如图所示，该方法包括步骤：Fig. 1 is a flow chart of a method for detecting the operational performance of an air traffic control sector in Embodiment 1 of the present invention. As shown in the figure, the method includes steps:
S1：输入历史扇区运行性能指标数据；S1: Input historical sector operation performance index data;
S2：基于聚类分析模型处理历史扇区运行性能指标数据，建立扇区运行性能档案；S2: Based on the cluster analysis model, process the historical sector operation performance index data, and establish sector operation performance files;
S3：输入当前扇区运行性能指标数据，对照扇区运行性能档案计算得到最大相似类和最小相似度；S3: Input the current sector operating performance index data, and calculate the maximum similarity class and minimum similarity according to the sector operating performance file;
S4：根据最小相似度判断扇区运行性能是否异常，及产生响应告警。S4: According to the minimum similarity, it is judged whether the operation performance of the sector is abnormal, and a response alarm is generated.
需要注意的是，本发明的步骤，并不限制动作执行的先后顺序，只为方便理解本发明的思想。It should be noted that the steps of the present invention do not limit the sequence of execution of actions, but are only for the convenience of understanding the concept of the present invention.
本发明由于采用定量分析方法，通过对海量运行数据的不间断检测和计算分析，并依靠对历史扇区运行性能指标数据的挖掘，获取指标数据与扇区运行性能情况之间的关系，克服了现有技术定性研究较多，定量研究较少，导致客观性不足的情况；不仅从反映管制员工作负荷的指标下手，同时综合考虑其他影响检测结果的影响因子，将影响扇区运行性能的多维度指标进行全面、综合考虑，能够实现对扇区运行性能情况的有效检测，检测可靠性得以保证；而且，通过对大量管制扇区运行性能实际数据进行聚类分析，能提取管制扇区运行性能特征，建立扇区运行性能档案；更为重要的是，本发明全面、综合地涵盖了管制扇区运行性能的各类影响因素，能够满足空中交通管制单位对扇区运行性能情况进行实时检测和告警的实际需求，对于提升管制运行管理水平、优化管制空域结构具有数据支持作用。Due to the adoption of the quantitative analysis method, the present invention obtains the relationship between the index data and the operating performance of the sector through uninterrupted detection and calculation analysis of massive operating data, and relies on the mining of historical sector operating performance index data, thereby overcoming the There are many qualitative studies and few quantitative studies in the existing technology, which leads to the lack of objectivity; not only starting from the indicators reflecting the workload of the controllers, but also comprehensively considering other influencing factors that affect the detection results, will affect the performance of the sector. Comprehensive and comprehensive consideration of the dimension indicators can realize the effective detection of the operating performance of the sector, and the reliability of the detection can be guaranteed; moreover, by clustering and analyzing the actual data of the operating performance of a large number of controlled sectors, the operating performance of the controlled sector can be extracted. features, and establish sector performance files; more importantly, the present invention comprehensively and comprehensively covers all kinds of influencing factors of control sector performance, and can satisfy air traffic control units in real-time detection and analysis of sector performance conditions. The actual demand for warnings has a data support role in improving the level of control operation management and optimizing the structure of control airspace.
上述的聚类分析模型中的聚类分析(ClusterAnalysis)是数据挖掘方法的一种，它通过建立评价函数，根据数据库中的数据之间的相似程度将其进行分类，使得同一类中的数据具有较高的相似度，而不同类间的相似度较小。通过对大量管制扇区运行性能实际数据进行聚类分析，能提取管制扇区运行性能特征，通过建立扇区运行性能档案，能够对扇区运行情况进行针对性的检测，进而实现扇区运行性能综合检测及异常告警。The cluster analysis (Cluster Analysis) in the above cluster analysis model is a kind of data mining method. It establishes an evaluation function and classifies the data in the database according to the degree of similarity between them, so that the data in the same class have Higher similarity, less similarity between different classes. By clustering and analyzing the actual data of the operating performance of a large number of controlled sectors, the operating performance characteristics of the controlled sectors can be extracted. By establishing the sector operating performance files, it is possible to carry out targeted detection of the operating conditions of the sectors, and then realize the operating performance of the sectors. Comprehensive detection and abnormal alarm.
在数据空间A里，数据集X中的n个数据点可以使用矩阵形式进行表述，称为数据矩阵，如下所示：In the data space A, the n data points in the data set X can be expressed in matrix form, called the data matrix, as follows:
其中数据点xi＝(xi,1,xi,2,…,xi,m)由m个维度组成，xi,j为第i个数据点的第j个维度。聚类分析的最终目的是把数据集X划分为k个分割Ck，这些分割被称为类。聚类分析中使用相似度来判断数据之间的差异程度。通常采用多种形式距离的倒数来度量相似度，距离越小表明数据相似度越大，反之相似度越小。常用的距离统计量包括欧几里德(Euclidean)距离和曼哈顿(Manhattan)距离等。由于在计算距离的公式中没有确定上限，因此不同量纲下数据大小的差异程度会直接影响相似度计算，从而影响聚类结果，所以需要对数据进行无量纲化处理。无量纲化处理是指将原始指标值通过简单数学变化以消除各指标量纲影响的方法，常用的无量纲化方法主要包括极差化和Z分数法(标准差法)。Wherein the data point xi =(xi,1 ,xi,2 ,...,xi,m ) consists of m dimensions, and xi,j is the j-th dimension of the i-th data point. The ultimate goal of cluster analysis is to divide the data set X into k partitions Ck , and these partitions are called classes. Similarity is used in cluster analysis to judge the degree of difference between data. The reciprocal of the distance in various forms is usually used to measure the similarity. The smaller the distance, the greater the similarity of the data, and vice versa. Commonly used distance statistics include Euclidean distance and Manhattan distance. Since there is no upper limit in the formula for calculating distance, the degree of difference in data size under different dimensions will directly affect the calculation of similarity, thereby affecting the clustering results, so it is necessary to perform dimensionless processing on the data. Dimensionless processing refers to the method of changing the original index value through simple mathematics to eliminate the influence of each index dimension. Commonly used dimensionless methods mainly include range and Z-score method (standard deviation method).
k-平均聚类方法是聚类分析中最主要使用的一种方法，它具有良好的可扩展性，对于大规模数据集具有较高的计算效率。该方法设定聚类数为k，并根据类中数据点的变量平均值(即类的中心结点)来计算类之间的相似度，将数据点分配到最近的类并更新中心结点位置，直至满足收敛条件。The k-means clustering method is the most widely used method in cluster analysis, which has good scalability and high computational efficiency for large-scale data sets. This method sets the number of clusters to k, and calculates the similarity between classes according to the variable average value of the data points in the class (that is, the central node of the class), assigns the data points to the nearest class and updates the central node position until the convergence condition is met.
如图2所示是本发明一个优选实施例的流程图；如图所示，具体的，步骤S2包括过程：As shown in Figure 2 is a flow chart of a preferred embodiment of the present invention; As shown in the figure, specifically, step S2 includes the process:
S2-1：根据预设的聚类数目k对历史扇区运行性能指标数据进行分类，形成k个初始类，并确定每一初始类的中心结点；S2-1: Classify the historical sector operation performance index data according to the preset cluster number k, form k initial clusters, and determine the central node of each initial cluster;
S2-2：计算历史扇区运行性能指标数据中的每个数据点到k个初始类的中心结点之间的欧几里德距离，并根据距离类中心结点最短的原则将所有的数据点进行重新分类形成k个类；S2-2: Calculate the Euclidean distance between each data point in the historical sector operation performance index data and the central nodes of the k initial classes, and divide all the data according to the principle of the shortest distance from the central nodes of the class The points are reclassified to form k classes;
S2-3：依次计算各类的变量均值，并以均值作为新的k个类的中心结点；S2-3: Calculate the mean value of various variables in turn, and use the mean value as the central node of the new k classes;
S2-4：计算新确定的类中心结点距初始类的中心结点之间的偏移量，当最大偏移量等于或小于设定值时，根据新确定的k个类，得到扇区运行性能档案。S2-4: Calculate the offset between the newly determined center node of the class and the center node of the initial class. When the maximum offset is equal to or less than the set value, obtain the sector according to the newly determined k classes Run the performance profile.
聚类分析模型中使用相似度来判断数据之间的差异程度，采用欧几里德距离来度量相似度，距离越小表明数据相似度越大，反之相似度越小；而采用聚类分析模型，可以提高对大规模数据集的计算效率，以提高扇区运行性能综合检测的实效性和及时性。In the cluster analysis model, the similarity is used to judge the degree of difference between the data, and the Euclidean distance is used to measure the similarity. The smaller the distance, the greater the similarity of the data, otherwise the smaller the similarity; and the cluster analysis model , which can improve the computing efficiency of large-scale data sets, so as to improve the effectiveness and timeliness of comprehensive detection of sector operating performance.
其中，若最大偏移量大于设定值，则重新计算欧几里德距离，并根据欧几里德距离进行分类。通过设定值，可以确保确认和建立的扇区运行性能档案可以较好匹配于该扇区运行性能综合检测，提高检测结果的准确度。Among them, if the maximum offset is greater than the set value, the Euclidean distance is recalculated, and classification is performed according to the Euclidean distance. By setting the value, it can be ensured that the confirmed and established sector operating performance file can better match the comprehensive detection of the sector's operating performance, improving the accuracy of the detection results.
而在步骤S3中，还包括过程：And in step S3, also include process:
S3-1：输入当前扇区运行性能指标数据；S3-1: Input the current sector operation performance index data;
S3-2：计算输入的当前扇区运行性能指标数据与扇区运行性能档案中每个类的中心点的相似度；S3-2: Calculate the similarity between the input current sector performance index data and the center point of each class in the sector performance file;
S3-3：求得其中的最大相似度，以及最大相似度对应的类；S3-3: Obtain the maximum similarity and the class corresponding to the maximum similarity;
S3-4：计算当前扇区运行性能指标数据与最大相似度对应的类中各数据点的相似度，得到最小相似度。S3-4: Calculate the similarity between the current sector operation performance index data and each data point in the class corresponding to the maximum similarity to obtain the minimum similarity.
通过进行最大相似类的确定和后续计算，可以提高对大规模数据集的计算效率，以提高扇区运行性能综合检测的实效性和及时性。Through the determination and subsequent calculation of the maximum similarity class, the calculation efficiency of large-scale data sets can be improved, so as to improve the effectiveness and timeliness of comprehensive detection of sector operating performance.
本方法选取扇区运行性能的17项指标数据进行聚类分析，则每个数据点xi有17个维度，可记为：This method selects 17 index data of sector operating performance for cluster analysis, then each data point xi has 17 dimensions, which can be recorded as:
xi＝{xi,j,j＝1,2,...,17}xi ={xi,j ,j=1,2,...,17}
其中，扇区通行性检测指标为{xi,1,xi,2,xi,3,xi,4}，分别表示扇区流量、扇区航行里程、扇区航行时间和扇区交通流密度；扇区复杂性检测指标为{xi,5,xi,6,xi,7,xi,8}，分别表示扇区航空器爬升次数、扇区航空器下降次数、扇区航空器改速次数、扇区航空器改航次数；扇区安全性检测指标为{xi,9,xi,10}，分别表示扇区短期冲突告警频率和扇区最低安全高度告警频率；扇区经济性检测指标为{xi,11,xi,12,xi,13,xi,14,xi,15}，分别表示扇区饱和度、扇区排队长度、扇区航空器延误架次率、扇区航空器延误时间、扇区航空器平均延误时间；管制员工作负荷检测指标为{xi,16,xi,17}，分别表示陆空通话信道占用率、陆空通话次数。Among them, the sector trafficability detection index is {xi,1 ,xi,2 ,xi,3 ,xi,4 }, respectively representing sector flow, sector mileage, sector navigation time and sector traffic flow density; the sector complexity detection index is {xi,5 ,xi,6 ,xi,7 ,xi,8 }, respectively representing the number of climbs of aircraft in the sector, the number of descents of aircraft in the sector, and the number of aircraft changes in the sector. speed times, sector aircraft diversion times; the sector safety detection index is {xi,9 ,xi,10 }, respectively representing the sector short-term conflict warning frequency and the sector minimum safe altitude warning frequency; the sector economy The detection index is {xi,11 ,xi,12 ,xi,13 ,xi,14 ,xi,15 }, respectively representing sector saturation, sector queue length, sector aircraft delay rate, sector The delay time of aircraft in the area and the average delay time of aircraft in the sector; the controller workload detection index is {xi,16 ,xi,17 }, which respectively represent the land-air call channel occupancy rate and the number of land-air call.
以1小时为时长采样，得到各样本上述17个指标的输入值，样本数据示例如下表1所示：Take 1 hour as the sampling time to obtain the input values of the above 17 indicators for each sample. The sample data examples are shown in Table 1 below:
表1扇区运行性能指标数据样本示例Table 1 Example of data samples of sector operation performance indicators
其中，最大相似类与最小相似度的寻找如下：Among them, the search for the maximum similarity class and the minimum similarity is as follows:
计算当前扇区运行性能指标无量纲化后的数据集t与扇区运行性能档案中各个类中的中心结点ck的相似度sim(t,ck)，并求得与扇区运行性能档案中k个类中心结点的最大相似度simm(t,ck)及其类Class(k)，其中sim(t,ck)可记为：Calculate the similarity sim(t,ck ) between the current sector operating performance index dimensionless data set t and the central node ck in each class in the sector operating performance file, and obtain the similarity with the sector operating performance The maximum similarity simm (t,ck ) and its class Class(k) of k class center nodes in the file, where sim(t,ck ) can be written as:
tj为检测数据无量纲化后第j项指标值，ck,j为第k个类中心点的第j项无量纲化指标值。tj is the index value of the jth item after the detection data is dimensionless, and ck,j is the dimensionless index value of the jth item of the kth class center point.
计算t与Class(k)中各数据点的相似度，得到最小相似度minSim。Calculate the similarity between t and each data point in Class(k) to obtain the minimum similarity minSim.
进一步的，步骤S4包括过程：若计算的到的最小相似度超过预先设定的相似度阈值，则判断扇区运行性能情况异常，Further, step S4 includes a process: if the calculated minimum similarity exceeds the preset similarity threshold, it is judged that the operating performance of the sector is abnormal,
进行扇区异常运行响应告警。Perform abnormal operation of the sector to respond to the alarm.
本方案，提高了本方法的实用性，使其可以较好的应用于工程单位等，用于进行扇区异常情况的响应告警。This solution improves the practicability of the method, so that it can be better applied to engineering units and the like for responding to alarms for sector abnormalities.
具体的，参照设定的管制扇区运行性能响应告警阈值，若minSim超出设定的阈值范围，则表示扇区运行性能出现异常，输出报警信号，否则表示该时段内的扇区运行性能为正常。Specifically, referring to the set control sector operation performance response alarm threshold, if minSim exceeds the set threshold range, it indicates that the sector operation performance is abnormal, and an alarm signal is output, otherwise it indicates that the sector operation performance within this period is normal .
另外，在步骤S2之前，即步骤S1还包括过程：In addition, before step S2, that is, step S1 also includes the process:
S1-1：输入历史扇区运行性能数据；S1-1: Input historical sector performance data;
S1-2：对历史扇区运行性能指标数据中的数据进行无量纲化处理；S1-2: Perform dimensionless processing on the data in the historical sector operation performance index data;
在步骤S3中还包括过程S3-1-1：In step S3, process S3-1-1 is also included:
对输入的当前扇区运行性能指标数据进行无量纲化处理。Dimensionless processing is performed on the input current sector operation performance index data.
由于在计算距离的公式中没有确定上限，因此不同量纲下数据大小的差异程度会直接影响相似度计算，从而影响聚类结果，通过对数据进行无量纲化处理，可以避免以上情况。Since there is no upper limit in the formula for calculating distance, the degree of difference in data size in different dimensions will directly affect the calculation of similarity, thereby affecting the clustering results. The above situation can be avoided by dimensionless processing of data.
其中，历史扇区运行性能指标数据包括正向指标数据和逆向指标数据；Among them, the historical sector operation performance index data includes forward index data and reverse index data;
若该数据为逆向指标数据，则先取其倒数或者取负后，再对该数据进行无量纲化处理。逆向指标数据先进行先取其倒数或者取负，可以保证无量纲化处理的效果。If the data is reverse index data, take its reciprocal or negative value first, and then perform dimensionless processing on the data. The reverse index data is firstly taken to take its reciprocal or negative, which can ensure the effect of dimensionless processing.
对应的，在对照扇区运行性能档案计算得到最大相似类和最小相似度之前，具体的可以在步骤S3-1中包括过程S3-1-1：对当前扇区运行性能指标数据中的数据进行无量纲化处理。Correspondingly, before calculating the maximum similarity class and the minimum similarity degree according to the sector operation performance file, the specific step S3-1 may include the process S3-1-1: the data in the current sector operation performance index data Dimensionless processing.
由于在计算距离的公式中没有确定上限，因此不同量纲下数据大小的差异程度会直接影响相似度计算，从而影响聚类结果，通过对数据进行无量纲化处理，可以避免以上情况。Since there is no upper limit in the formula for calculating distance, the degree of difference in data size in different dimensions will directly affect the calculation of similarity, thereby affecting the clustering results. The above situation can be avoided by dimensionless processing of data.
究其原因，是考虑到不同指标间存在量纲不同及数量级的差异，为消除这些差异对相似度计算的影响，需要对指标数据进行标准化转换。扇区运行性能指标数据可以分为两类，第一类为正向指标，即值越大越好的指标，包括扇区通行性指标(扇区流量、扇区航行里程、扇区航行时间、扇区交通流密度)、部分扇区经济性指标(扇区饱和度)和管制员工作负荷指标(陆空通话信道占用率、陆空通话次数)；第二类为逆向指标，即值越小越好的指标，包括扇区复杂性指标(扇区航空器爬升次数、扇区航空器下降次数、扇区航空器改速次数、扇区航空器改航次数)、扇区安全性指标(STCA告警和MSAW告警数据)和部分空域经济性指标(扇区排队长度、扇区航空器延误架次率、扇区航空器延误时间和扇区航空器平均延误时间)。The reason is that there are differences in dimensions and orders of magnitude between different indicators. In order to eliminate the impact of these differences on the similarity calculation, it is necessary to standardize the conversion of the indicator data. Sector operation performance index data can be divided into two categories. The first category is positive indicators, that is, the larger the value, the better the indicators, including sector traffic indicators (sector flow, sector mileage, sector voyage time, sector area traffic density), some sector economic indicators (sector saturation) and controller workload indicators (occupancy rate of land-air call channel, number of land-air calls); the second category is the reverse index, that is, the smaller the value, the better Good indicators, including sector complexity indicators (number of sector aircraft climbs, number of sector aircraft descents, number of sector aircraft speed changes, number of sector aircraft diversions), sector safety indicators (STCA alert and MSAW alert data ) and some airspace economic indicators (sector queuing length, sector aircraft delay rate, sector aircraft delay time and sector aircraft average delay time).
当前扇区运行性能的17项指标数据记为r＝{rj,j＝1,2,...,17}，tj为无量纲化处理后的第j项指标值，为第j项指标的均值，sj为第j项指标的标准差，则对于正向指标，对于逆向指标，先取其倒数或取负使其正向化，再使用上述公式对其进行无量纲化处理；其中均值和标准差从扇区运行性能档案中提取。The 17 index data of the current sector’s operating performance are recorded as r={rj ,j=1,2,...,17}, and tj is the jth index value after dimensionless processing, is the mean value of the j-th index, sj is the standard deviation of the j-th index, then for the positive index, For the reverse index, first take its reciprocal or negative to make it positive, and then use the above formula to perform dimensionless processing; the mean and standard deviation are extracted from the sector's operating performance archives.
根据上述方法流程，采集成都ACC01扇区相关运行性能指标数据共计648组。确立其中的628组数据构建扇区运行性能档案，使用余下的20组数据用于测试管制扇区异常运行性能告警方法。According to the above-mentioned method flow, a total of 648 sets of data related to the operational performance indicators of the ACC01 sector in Chengdu were collected. Establish 628 sets of data among them to build sector operating performance files, and use the remaining 20 sets of data to test the alarm method for abnormal operating performance of control sectors.
首先利用Z分数法将指标数据标准化以消除不同量纲对聚类结果的影响。设定聚类结果为三类，使用软件SPSS实现扇区运行性能档案的构建。经过19次迭代以后聚类中心达到收敛。在得到的聚类结果中，第一类有323个时段的数据点(扇区运行性能良好)，第二类有150个时段的数据点(扇区运行性能一般)，第三类有155个时段的数据点(扇区运行性能较好)。表2中展示了最终聚类中心的情况，从表中可以得到管制扇区运行性能各项指标经无量纲后的特征，为后续的扇区运行性能异常告警提供依据。Firstly, the Z-score method is used to standardize the index data to eliminate the impact of different dimensions on the clustering results. Set the clustering results into three categories, and use the software SPSS to realize the construction of sector operating performance files. After 19 iterations, the cluster center reaches convergence. In the obtained clustering results, the first category has 323 data points of time periods (the sector has good performance), the second category has 150 data points of the period (the sector has average performance), and the third category has 155 Data points for time periods (sectors run better). Table 2 shows the situation of the final clustering center. From the table, the dimensionless characteristics of the operating performance indicators of the control sector can be obtained, which provides a basis for the subsequent abnormal alarm of the sector operating performance.
表2最终聚类中心情况Table 2 Final cluster center situation
表3展示了各指标在不同类中的均值比较情况，从表中可以看出各类间均方较大，类内均方较小，各指标在三类中的差异显著。此外，从F值可以看出，一些指标例如扇区流量、交通流密度、改航次数、饱和度等对扇区运行性能的影响较显著。Table 3 shows the comparison of the mean values of each indicator in different categories. It can be seen from the table that the mean square between the categories is larger, and the mean square within the category is smaller. The difference of each indicator among the three categories is significant. In addition, it can be seen from the F value that some indicators such as sector flow, traffic flow density, number of diversions, saturation, etc. have a significant impact on sector performance.
表3聚类分析结果ANOVA表Table 3 ANOVA table of cluster analysis results
根据相似性原理，使用MATLAB软件将20个测试时间段内管制扇区运行性能指标和与管制扇区运行性能档案求取相似度，再取最小相似度作为标准衡量其运行性能，设定最小相似度的报警阈值为0.074，可得检测结果如图11所示，从图中可以看出，在时段8和11的最小相似度小于阈值，应输出告警信号对异常扇区运行性能进行警告。According to the principle of similarity, use MATLAB software to obtain the similarity between the operating performance indicators of the controlled sector and the operating performance files of the controlled sector during the 20 test periods, and then take the minimum similarity as the standard to measure its operating performance, and set the minimum similarity The alarm threshold of the degree is 0.074, and the detection results are shown in Figure 11. It can be seen from the figure that the minimum similarity in periods 8 and 11 is less than the threshold, and an alarm signal should be output to warn of abnormal sector performance.
实施例二：Embodiment two:
如图3所示是本发明实施例二的一种空中交通管制扇区运行性能检测系统的示意图，结合实施例一可知，该空中交通管制扇区运行性能检测系统100包括：As shown in FIG. 3, it is a schematic diagram of an air traffic control sector operating performance detection system according to Embodiment 2 of the present invention. In combination with Embodiment 1, it can be seen that the air traffic control sector operating performance detection system 100 includes:
扇区运行性能档案创建模块1，根据聚类分析后的历史扇区运行性能指标数据创建扇区运行性能档案；The sector operation performance file creation module 1 creates a sector operation performance file according to the historical sector operation performance index data after cluster analysis;
检测模块2：根据输入的当前扇区运行性能指标数据，对照扇区运行性能档案计算得到最大相似类和最小相似度，并根据最小相似度判断扇区运行性能是否异常。Detection module 2: According to the input current sector operation performance index data, calculate the maximum similarity class and minimum similarity according to the sector operation performance file, and judge whether the sector operation performance is abnormal according to the minimum similarity.
本发明由于采用定量分析方法，通过对海量运行数据的不间断检测和计算分析，并依靠对历史扇区运行性能指标数据的挖掘，获取指标数据与扇区运行性能情况之间的关系，克服了现有技术定性研究较多，定量研究较少，导致客观性不足的情况；不仅从反映管制员工作负荷的指标下手，同时综合考虑其他影响检测结果的影响因子，将影响扇区运行性能的多维度指标进行全面、综合考虑，能够实现对扇区运行性能情况的有效检测，检测可靠性得以保证；而且，通过对大量管制扇区运行性能实际数据进行聚类分析，能提取管制扇区运行性能特征，建立扇区运行性能档案；更为重要的是，本发明全面、综合地涵盖了管制扇区运行性能的各类影响因素，能够满足空中交通管制单位对扇区运行性能情况进行实时检测和告警的实际需求，对于提升管制运行管理水平、优化管制空域结构具有数据支持作用。Due to the adoption of the quantitative analysis method, the present invention obtains the relationship between the index data and the operating performance of the sector through uninterrupted detection and calculation analysis of massive operating data, and relies on the mining of historical sector operating performance index data, thereby overcoming the There are many qualitative studies and few quantitative studies in the existing technology, which leads to the lack of objectivity; not only starting from the indicators reflecting the workload of the controllers, but also comprehensively considering other influencing factors that affect the detection results, will affect the performance of the sector. Comprehensive and comprehensive consideration of the dimension indicators can realize the effective detection of the operating performance of the sector, and the reliability of the detection can be guaranteed; moreover, by clustering and analyzing the actual data of the operating performance of a large number of controlled sectors, the operating performance of the controlled sector can be extracted. features, and establish sector performance files; more importantly, the present invention comprehensively and comprehensively covers all kinds of influencing factors of control sector performance, and can satisfy air traffic control units in real-time detection and analysis of sector performance conditions. The actual demand for warnings has a data support effect on improving the level of control operation management and optimizing the structure of control airspace.
图4是本发明另一优选实施例的示意图，结合图3可知，扇区运行性能档案创建模块1包括聚类分析单元11和创建单元12，聚类分析单元11用于对输入的，经过无量纲化处理的历史扇区运行性能指标数据进行聚类分析处理，创建模块12用于根据聚类分析处理得到的结果创建扇区运行性能档案；Fig. 4 is a schematic diagram of another preferred embodiment of the present invention. It can be known in conjunction with Fig. 3 that the sector operation performance file creation module 1 includes a cluster analysis unit 11 and a creation unit 12, and the cluster analysis unit 11 is used for inputting, through infinite Cluster analysis processing is performed on the historical sector operation performance index data of the outline processing, and the creation module 12 is used to create sector operation performance files according to the results obtained by the cluster analysis processing;
检测模块2包括相似度处理单元21，相似度处理单元21根据输入的当前扇区运行性能指标，以及扇区运行性能档案计算最大相似类和最小相似度；The detection module 2 includes a similarity processing unit 21, and the similarity processing unit 21 calculates the maximum similarity class and the minimum similarity according to the input current sector operating performance index and the sector operating performance file;
空中交通管制扇区运行性能检测系统100还包括耦合于相似度处理单元的警告模块；若计算得到的最小相似度符合预设条件，则警告模块响应警告；The air traffic control sector operation performance detection system 100 also includes a warning module coupled to the similarity processing unit; if the calculated minimum similarity meets the preset condition, the warning module responds to the warning;
空中交通管制扇区运行性能检测系统100还包括管制扇区运行性能检测数据库4、以及分别耦合于管制扇区运行性能检测数据库4的数据引接模块5和管制扇区运行性能指标检测模块6；数据接引模块5包括电报数据接口、综合航迹数据接口和管制语音数据接口；管制扇区运行性能指标检测模块6用于采集扇区通行性指标、扇区复杂性指标、扇区安全性指标、扇区经济性指标和管制员工作负荷指标；The air traffic control sector operational performance detection system 100 also includes a control sector operational performance detection database 4, and a data connection module 5 and a control sector operational performance index detection module 6 respectively coupled to the control sector operational performance detection database 4; The connection module 5 includes a telegram data interface, an integrated track data interface and a control voice data interface; the control sector operation performance index detection module 6 is used to collect sector traffic indicators, sector complexity indicators, sector security indicators, Sector economic indicators and controller workload indicators;
管制扇区运行性能检测数据库4耦合于扇区运行性能档案创建模块1和检测模块2的输入端。The control sector operation performance detection database 4 is coupled to the input ends of the sector operation performance file creation module 1 and the detection module 2 .
本方案采用定量研究方法，将影响扇区性能的多维度指标进行全面、综合考虑，从而实现对扇区运行性能的有效检测；所设计的空中交通管制扇区运行性能检测系统，能够应用于工程单位，具有很强的操作性。This program adopts the quantitative research method, comprehensively and comprehensively considers the multi-dimensional indicators that affect the performance of the sector, so as to realize the effective detection of the operational performance of the sector; the designed air traffic control sector operational performance detection system can be applied to engineering unit with strong operability.
如图5所示是本发明的空中交通管制扇区运行性能检测系统的逻辑结构图；空中交通空中交通管制扇区运行性能检测系统主要包括一套管制扇区运行性能检测数据库和数据引接、数据计算三大功能模块。As shown in Figure 5, it is a logical structure diagram of the air traffic control sector operational performance detection system of the present invention; the air traffic air traffic control sector operational performance detection system mainly includes a set of control sector operational performance detection database and data lead, data Calculate the three major functional modules.
管制扇区运行性能检测数据库将各信息采集点采集的空中交通管制数据(包括雷达综合航迹数据、电报数据、VHF录音数据等)归类、保存，以及检测到的管制扇区运行性能指标(包括管制扇区通行性指标、管制扇区复杂性指标、管制扇区安全性指标、管制扇区经济性指标、管制员工作负荷指标等)，为扇区运行性能检测提供数据依据。The control sector operation performance detection database classifies and saves the air traffic control data collected by each information collection point (including radar comprehensive track data, telegraph data, VHF recording data, etc.), and the detected control sector operation performance indicators ( Including control sector traffic indicators, control sector complexity indicators, control sector security indicators, control sector economic indicators, controller workload indicators, etc.), provide data basis for sector operation performance testing.
如图6所示是系统对应的网络结构图，系统通过数据采集服务器收集实时数据，通过管制扇区运行性能指标检测服务器和综合检测服务器实时监视运行数据，检测和分析管制扇区运行性能状况，并对最小相似度超出阈值的时段进行告警。整个系统的网络平台将依托现有的管理信息网，采集平台和空管生产网络进行物理隔离，保证数据的单向传递，阻止网络攻击，以保障相关数据安全性和生产运行系统可靠性。Figure 6 shows the corresponding network structure diagram of the system. The system collects real-time data through the data acquisition server, monitors the operating data in real time through the control sector operation performance index detection server and the comprehensive detection server, and detects and analyzes the control sector operation performance status. And give an alarm for the period when the minimum similarity exceeds the threshold. The network platform of the entire system will rely on the existing management information network, and the collection platform will be physically isolated from the air traffic control production network to ensure the one-way transmission of data and prevent network attacks, so as to ensure the security of relevant data and the reliability of the production and operation system.
如图7所示是本发明实施例的系统对应的功能结构图；主要包括管制运行数据采集、管制扇区运行性能指标检测、管制扇区运行性能综合检测以及管制扇区运行性能告警等功能模块。As shown in Figure 7, it is a functional structure diagram corresponding to the system of the embodiment of the present invention; it mainly includes functional modules such as control operation data collection, control sector operation performance index detection, control sector operation performance comprehensive detection, and control sector operation performance alarm. .
在数据接引模块中，包括综合航迹数据接口，对应的综合航迹数据采集功能结构图如图8所示，空管自动化系统对航管一、二次雷达等监视信号进行数据融汇和数据处理，输出综合航迹信息，其主要的处理模块包括雷达前端处理模块，雷达数据处理模块和飞行计划处理模块。In the data connection module, including the integrated track data interface, the corresponding integrated track data acquisition function structure diagram is shown in Figure 8. The air traffic control automation system performs data fusion and integration of the monitoring signals of the air traffic control primary and secondary radars. Data processing, outputting comprehensive track information, its main processing modules include radar front-end processing module, radar data processing module and flight plan processing module.
本系统从空管自动化系统采集综合航迹数据，通过网络的方式进行传输。数据采集服务器对采集的综合航迹数据进行解析，获取航空器的高度、速度、位置等信息用于指标的计算。This system collects comprehensive track data from the air traffic control automation system and transmits it through the network. The data acquisition server analyzes the collected comprehensive track data, and obtains information such as the altitude, speed, and position of the aircraft for the calculation of indicators.
综合航迹数据采集模块包括航迹数据格式转换模块、航迹数据解析模块、航迹数据存储模块。The comprehensive track data acquisition module includes a track data format conversion module, a track data analysis module, and a track data storage module.
如图9所示是本发明的管制语音数据接口对应的语音数据采集流程图，管制员与飞行员通过VHF通信系统实现陆空语音通话。该系统由甚高频(VeryHighFrequency，VHF)收发电台及信号传输、处理装置组成。As shown in Fig. 9 is the flow chart of voice data acquisition corresponding to the control voice data interface of the present invention, the controller and the pilot realize the ground-air voice communication through the VHF communication system. The system is composed of VHF (Very High Frequency, VHF) transceiver station and signal transmission and processing devices.
语音数据采集从配线架上并接采集语音信号，将陆空通话信息进行解码和存储，用于管制员管制指挥通话负荷的分析。Voice data collection collects voice signals parallelly from the distribution frame, decodes and stores land and air call information, and uses it for controllers to control and command call load analysis.
如图9所示，席位语音数据由内话系统配线架通过带屏蔽网线并接引入系统数据采集服务器，语音通道与席位(扇区)对应。语音信号从配线架上高阻抗(录音模块为200K欧姆)采集(管制员地空通话)席位语音，不影响地空通话和语音记录，采用多对电缆线将语音信号从配线架引接至语音处理器，实现对多个席位语音的采集和分析。As shown in Figure 9, seat voice data is connected to the system data collection server through the intercom system distribution frame through a shielded network cable, and the voice channel corresponds to the seat (sector). The voice signal is collected from the distribution frame with high impedance (recording module is 200K ohm) (controller ground-to-air call) seat voice, which does not affect the ground-to-air call and voice recording. Multiple pairs of cables are used to lead the voice signal from the distribution frame to the The voice processor realizes the collection and analysis of the voices of multiple seats.
如图10所示是本发明的电报数据接口对应的电报数据采集功能结构图，转报系统是收发民用航空飞行动态固定电报的枢纽装置，民用航空飞行动态固定电报的报文由若干个规定的数据编组按固定顺序排列而成。As shown in Figure 10, it is the corresponding telegraph data acquisition functional structural diagram of the telegraph data interface of the present invention, and the forwarding system is a hub device for sending and receiving civil aviation flight dynamic fixed telegrams, and the message of civil aviation flight dynamic fixed telegrams is composed of several regulations Data groups are arranged in a fixed order.
电报数据采集模块引接转报系统输出的电报数据，并对数据进行格式转换、解析和存储，获取飞行计划数据，如图所示，该模块将接收到的电报数据解析后存储到数据库中保存，用于扇区性能检测指标数据计算。The telegram data acquisition module leads to the telegram data output by the transfer system, and converts, parses and stores the data to obtain the flight plan data. As shown in the figure, this module parses the received telegram data and stores them in the database for storage , used for sector performance detection indicator data calculation.
本发明的管制扇区运行性能指标检测模块具体如下：扇区通行性指标，包括扇区流量、扇区航行里程、扇区航行时间、扇区交通流密度；扇区复杂性指标，包括扇区航空器爬升次数、扇区航空器下降次数、扇区航空器改速次数、扇区航空器改航次数；扇区安全性指标，包括扇区短期冲突告警(STCA,Short-termconflictalert)频率、扇区最低安全高度告警(MSAW,Minimumsafealtitudewarning)频率；扇区经济性指标，包括扇区饱和度、扇区排队长度、扇区航空器延误架次率、扇区航空器延误时间、扇区航空器平均延误时间；管制员工作负荷指标，包括陆空通话信道占用率、陆空通话次数。并基于指标体系输出管制扇区性能检测指标数据计算结果。系统提供良好的人机界面，供用户查看各种实时统计图形。The control sector operation performance index detection module of the present invention is specifically as follows: sector traffic index, including sector flow, sector mileage, sector flight time, sector traffic flow density; sector complexity index, including sector The number of aircraft climbs, the number of sector aircraft descents, the number of sector aircraft speed changes, the number of sector aircraft diversion times; sector safety indicators, including sector short-term conflict alert (STCA, Short-term conflictalert) frequency, sector minimum safe altitude Warning (MSAW, Minimum safe attitude warning) frequency; sector economic indicators, including sector saturation, sector queuing length, sector aircraft delay rate, sector aircraft delay time, sector aircraft average delay time; controller workload indicators , including the land-air call channel occupancy rate and the number of land-air call calls. And based on the index system, output the calculation results of the control sector performance detection index data. The system provides a good man-machine interface for users to view various real-time statistical graphics.
其中，扇区通行性指标是指：Among them, the sector accessibility index refers to:
(1)扇区流量(1) Sector traffic
扇区流量是指管制扇区单位时间内所管辖的航空器架次。系统通过引接空管自动化系统综合航迹数据获取空中航空器的位置信息，结合已配置的扇区边界信息，计算得到扇区流量。Sector traffic refers to the number of aircraft sorties under the jurisdiction of the control sector per unit time. The system obtains the position information of the airborne aircraft by connecting the comprehensive track data of the air traffic control automation system, and combines the configured sector boundary information to calculate the sector flow.
(2)扇区航行里程(2) Sector mileage
扇区航行里程是指管制扇区单位时间内所管辖的航空器航行里程的总和。设管制扇区单位时间内航空器架次数为Q，第q架航空器的航行里程为Mq，扇区航行里程为Mtotal，则通过引接空管自动化系统综合航迹数据获取空中航空器的位置信息，结合已配置的扇区边界信息，计算得到扇区航行里程。Sector mileage refers to the sum of the mileage of aircraft under the jurisdiction of the control sector unit time. Assuming that the number of aircraft sorties in the control sector unit time is Q, the flight mileage of the qth aircraft is Mq , and the sector flight mileage is Mtotal , then The location information of the aircraft in the air is obtained by connecting the comprehensive track data of the air traffic control automation system, and combined with the configured sector boundary information, the sector mileage is calculated.
(3)扇区航行时间(3) Sector sailing time
扇区航行时间是指管制扇区单位时间内所管辖的航空器航行时间的总和。设管制扇区单位时间内航空器架次数为Q，第q架航空器的航行时间为Tq，扇区航行时间为Ttotal，则通过引接空管自动化系统综合航迹数据获取空中航空器的位置信息，结合已配置的扇区边界信息，计算得到扇区航行时间。Sector flight time refers to the sum of the flight time of aircraft under the jurisdiction of the control sector unit time. Assuming that the number of aircraft movements in the control sector unit time is Q, the flight time of the qth aircraft is Tq , and the sector flight time is Ttotal , then The position information of the aircraft in the air is obtained by connecting the comprehensive track data of the air traffic control automation system, and combined with the configured sector boundary information, the sector flight time is calculated.
(4)扇区交通流密度(4) Sector traffic flow density
扇区交通流密度是对管制扇区单位时间内所管辖的航空器架次密集程度的测度。设扇区面积为Ssec，管制扇区单位时间内航空器架次数为Q，单位时间内扇区交通流密度为Dsec，则Dsec＝Q/Ssec。系统读取配置的扇区边界信息得到扇区面积，结合扇区流量计算得到扇区交通流密度。Sector traffic density is a measure of the density of aircraft sorties under the jurisdiction of the control sector per unit time. Suppose the area of the sector is Ssec , the number of aircraft movements in the control sector per unit time is Q, and the traffic flow density in the sector per unit time is Dsec , then Dsec =Q/Ssec . The system reads the configured sector boundary information to obtain the sector area, and calculates the sector traffic flow density in combination with the sector flow.
扇区复杂性指标是指：The sector complexity index refers to:
(1)扇区航空器爬升次数(1) Number of aircraft climbs in the sector
扇区航空器爬升次数是指管制扇区单位时间内所管辖的航空器爬升次数的总和。设管制扇区单位时间内航空器架次数为Q，第q架航空器的爬升次数为Cq，扇区航空器爬升次数为Ctotal，则引接实时综合航迹数据，对扇区中航空器的爬升情况进行监视与统计，一个航空器爬升一个高度层为爬升一次，计算得到扇区航空器爬升次数。The number of climbs of aircraft in a sector refers to the sum of the number of climbs of aircraft under the jurisdiction of the control sector per unit time. Assuming that the number of aircrafts in the control sector unit time is Q, the number of climbs of the qth aircraft is Cq , and the number of climbs of aircraft in the sector is Ctotal , then The real-time integrated track data is used to monitor and count the climb of aircraft in the sector. An aircraft climbs one altitude layer to climb once, and the number of climbs of aircraft in the sector is calculated.
(2)扇区航空器下降次数(2) Number of aircraft descents in the sector
扇区航空器下降次数是指管制扇区单位时间内航空器下降次数的总和。设管制扇区单位时间内航空器架次数为Q，第q架航空器的下降次数为Dq，扇区航空器下降次数为Dtotal，则引接实时综合航迹数据，对扇区中航空器的下降情况进行监视与统计，一个航空器下降一个高度层为下降一次，计算得到扇区航空器爬升次数。The number of aircraft descents in the sector refers to the sum of the number of aircraft descents in the control sector per unit time. Assuming that the number of aircrafts in the control sector per unit time is Q, the number of descents of the qth aircraft is Dq , and the number of aircrafts in the sector is Dtotal , then The real-time integrated track data is used to monitor and count the aircraft's descent in the sector. One aircraft descends to one altitude level to descend once, and the number of climbs of the aircraft in the sector is calculated.
(3)扇区航空器改速次数(3) Number of aircraft speed changes in the sector
扇区航空器改速次数是指管制扇区单位时间内航空器速度改变次数的总和。设管制扇区单位时间内航空器架次数为Q，第q架航空器的改速次数为Sq，扇区航空器改速次数为Stotal，则引接实时综合航迹数据，对扇区中航空器的速度改变情况进行监视与统计，一个航空器速度连续改变达到设定参数为一次速度改变，计算得到扇区航空器改速次数。The number of aircraft speed changes in a sector refers to the sum of the number of aircraft speed changes in the control sector per unit time. Assuming that the number of aircraft movements per unit time in the control sector is Q, the number of speed changes of the qth aircraft is Sq , and the number of speed changes of aircraft in the sector is Stotal , then The real-time integrated track data is used to monitor and count the speed changes of aircraft in the sector. A continuous change in the speed of an aircraft reaches the set parameter as a speed change, and the number of speed changes of the aircraft in the sector is calculated.
(4)扇区航空器改航次数(4) Number of aircraft diversions in the sector
扇区航空器改航次数是指管制扇区单位时间内航空器航向改变次数的总和。设管制扇区单位时间内航空器架次数为Q，第q架航空器的改航次数为Hq，扇区航空器改航次数为Htotal，则引接实时综合航迹数据，对扇区中航空器的航向改变情况进行监视与统计，一个航空器航向连续改变达到设定参数为一次航向改变，计算得到扇区航空器改航次数。The number of aircraft diversions in a sector refers to the sum of the number of aircraft course changes in the control sector per unit time. Assuming that the number of aircraft movements per unit time in the control sector is Q, the number of diversions of the qth aircraft is Hq , and the number of diversions of aircraft in the sector is Htotal , then The real-time integrated track data is used to monitor and count the course changes of aircraft in the sector. The continuous course change of an aircraft reaches the set parameter as one course change, and the number of aircraft diversions in the sector is calculated.
而，扇区安全性指标是指：However, sector security indicators refer to:
(1)扇区短期冲突告警频率(1) Sector short-term collision alarm frequency
扇区短期冲突告警频率是指管制扇区单位时间内所管辖的航空器短期冲突告警次数，由系统引接空管自动化系统的STCA告警数据统计得到。The sector short-term conflict warning frequency refers to the number of aircraft short-term conflict warnings under the jurisdiction of the control sector per unit time, which is obtained from the statistics of the STCA warning data connected to the air traffic control automation system by the system.
(2)扇区最低安全高度告警频率(2) Alarm frequency of the minimum safe altitude in the sector
扇区最低安全高度告警频率是指管制扇区单位时间内所管辖的航空器最低安全高度告警次数，由系统引接空管自动化系统的MSAW告警数据统计得到。The minimum safe altitude warning frequency of a sector refers to the number of minimum safe altitude warnings of aircraft under the jurisdiction of the control sector per unit time, which is obtained from the statistics of the MSAW warning data connected to the air traffic control automation system by the system.
再者，扇区经济性指标是指：Furthermore, sector economic indicators refer to:
(1)扇区饱和度(1) Sector saturation
扇区饱和度是指管制扇区单位时间内流量与容量的比值，管制扇区单位时间内所能管辖的航空器最大数量标定为管制扇区容量。设管制扇区单位时间内航空器架次数为Q，管制扇区容量为C，扇区饱和度为Satusec，则Satusec＝Q/C。系统读取配置的扇区容量参数，结合扇区流量计算得到扇区饱和度。Sector saturation refers to the ratio of traffic flow to capacity per unit time of the control sector, and the maximum number of aircraft that can be controlled by the control sector per unit time is calibrated as the control sector capacity. Assuming that the number of aircraft sorties per unit time in the control sector is Q, the capacity of the control sector is C, and the saturation of the sector is Satusec , then Satusec =Q/C. The system reads the configured sector capacity parameters and calculates the sector saturation in combination with sector traffic.
(2)扇区排队长度(2) Sector queue length
在管制扇区单位时间内所管辖的航空器中，如进入扇区时出现盘旋等待等排队状况，则定义其为排队航空器，定义扇区排队长度为排队航空器的数量。系统引接综合航迹数据，判断目标航空器是否在扇区边界进行盘旋等待，并计算得到扇区排队长度。Among the aircraft under the jurisdiction of the control sector unit time, if there is a queuing situation such as circling and waiting when entering the sector, it is defined as a queuing aircraft, and the sector queuing length is defined as the number of queuing aircraft. The system leads the integrated track data to judge whether the target aircraft is circling and waiting at the boundary of the sector, and calculates the sector queue length.
(3)扇区航空器延误架次率(3) Sector aircraft delay rate
在管制扇区单位时间内所管辖的航空器中，航行时间超出了正常范围的航空器定义为延误航空器，航行时间超出正常范围的部分定义为延误时间。设管制扇区单位时间内航空器架次数为Q，扇区航空器的延误架次数为d，扇区航空器的延误架次率为Dratsec，则Dratsec＝d/Q。引接综合航迹数据，对每架航空器在管制扇区中的实际飞行时间与经验飞行时间进行对比，若实际飞行时间大于经验飞行时间，则视为延误航空器，并计算得到扇区航空器延误架次率。Among the aircraft under the jurisdiction of the control sector unit time, the aircraft whose flight time exceeds the normal range is defined as the delayed aircraft, and the part of the flight time which exceeds the normal range is defined as the delayed time. Assuming that Q is the number of aircraft sorties in the unit time of the control sector, the number of delayed aircraft in the sector is d, and the delayed rate of aircraft in the sector is Dratsec , then Dratsec = d/Q. Introduce the comprehensive track data, compare the actual flight time of each aircraft in the control sector with the experienced flight time, if the actual flight time is greater than the experienced flight time, it will be regarded as a delayed aircraft, and the sector aircraft delay rate will be calculated .
(4)扇区航空器延误时间(4) Sector aircraft delay time
在管制扇区单位时间内所管辖的航空器中，航行时间超出了正常范围的航空器定义为延误航空器，航行时间超出正常范围的部分定义为延误时间，延误时间总和定义为扇区航空器延误时间。设管制扇区单位时间内航空器架次数为Q，第q架航空器的延误时间为Delayq，扇区航空器延误时间为Delaysec，则引接综合航迹数据，对每架航空器在管制扇区中的实际飞行时间与经验飞行时间进行对比，若实际飞行时间大于经验飞行时间，则视为延误航空器，并计算得到扇区航空器延误时间。Among the aircraft under the jurisdiction of the control sector unit time, the aircraft whose flight time exceeds the normal range is defined as the delayed aircraft, the part of the flight time beyond the normal range is defined as the delayed time, and the total delay time is defined as the sector aircraft delay time. Assuming that the number of aircraft movements in the unit time of the control sector is Q, the delay time of the qth aircraft is Delayq , and the delay time of the sector aircraft is Delaysec , then Introduce the comprehensive track data, and compare the actual flight time of each aircraft in the control sector with the experienced flight time. If the actual flight time is greater than the experienced flight time, it will be regarded as a delayed aircraft, and the sector aircraft delay time will be calculated.
(5)扇区航空器平均延误时间(5) Average delay time of aircraft in the sector
在管制扇区单位时间内所管辖的航空器中，航行时间超出了正常范围的航空器定义为延误航空器，航行时间超出正常范围的部分定义为延误时间。设扇区航空器延误时间为Delaysec，扇区航空器的延误架次数为Q，扇区航空器的平均延误时间为Davgsec，则Davgsec＝Delaysec/Q。引接综合航迹数据，对每架航空器在管制扇区中的实际飞行时间与经验飞行时间进行对比，若实际飞行时间大于经验飞行时间，则视为延误航空器，并计算得到扇区航空器平均延误时间。Among the aircraft under the jurisdiction of the control sector unit time, the aircraft whose flight time exceeds the normal range is defined as the delayed aircraft, and the part of the flight time which exceeds the normal range is defined as the delayed time. Let the delay time of aircraft in the sector be Delaysec , the number of delayed aircraft in the sector be Q, and the average delay time of aircraft in the sector be Davgsec , then Davgsec = Delaysec /Q. Introduce the comprehensive track data, compare the actual flight time of each aircraft in the control sector with the experienced flight time, if the actual flight time is greater than the experienced flight time, it will be regarded as a delayed aircraft, and the average delay time of aircraft in the sector will be calculated .
另外，管制员工作负荷检测指的是：Additionally, controller workload detection refers to:
管制员为完成管制任务需承受身体上和精神上的压力，这些压力可以转化为时间上的消耗，通过时间消耗来缓解承受到的压力和完成客观任务的要求，这个时间消耗的长短就是管制员工作负荷的大小。在可测计的管制员工作时间消耗中，陆空通话信道占用率和陆空通话次数是反映管制员工作负荷的基础指标。(1)陆空通话信道占用率检测Controllers need to bear physical and mental pressure in order to complete control tasks. These pressures can be converted into time consumption. Time consumption can be used to relieve the pressure and complete the requirements of objective tasks. The length of this time consumption is the controller The size of the workload. Among the measurable controller working time consumption, the land-air communication channel occupancy rate and the number of land-air communication are the basic indicators to reflect the controller's workload. (1) Land and air call channel occupancy detection
陆空通话信道占用率是指管制扇区单位时间内陆空通话时长占比。设管制扇区在单位时间T内共陆空通话R次，第r次陆空通话的时间长度为Tr，陆空通话信道占用率为Trate，则引接管制语音数据，分析对应扇区管制席位的管制员与飞行员通话开始时间和结束时间，然后将每段通话的时长进行累加，从而得到扇区陆空通话时长，进而计算得到陆空通话信道占用率。The land-air call channel occupancy rate refers to the proportion of land-air call time in the control sector per unit time. Assuming that the control sector has a total of R land-air calls within a unit time T, the length of the r-th land-air call is Tr , and the land-air call channel occupancy rate is Trate , then Introduce the control voice data, analyze the start time and end time of the call between the controller and the pilot at the corresponding sector control seat, and then add up the duration of each call to obtain the sector land-air call duration, and then calculate the land-air call channel occupancy Rate.
(2)陆空通话次数检测(2) Detection of the number of land and air calls
陆空通话次数是指管制扇区单位时间内陆空通话的次数。系统对管制语音数据进行分析，每次通话计为一次陆空通话，对单位时间内通话次数进行累加得出陆空通话次数。The number of land and air calls refers to the number of land and air calls per unit time in the control sector. The system analyzes the control voice data, counts each call as a land-air call, and accumulates the number of calls per unit time to obtain the number of land-air calls.
本研究以管制扇区运行性能为因变量。扇区运行性能检测指标数据共计17项，记自变量X＝{Xj,j＝1,2,…,17}。This study takes the operational performance of the control sector as the dependent variable. There are 17 items in total for sector operation performance detection index data, recorded as independent variable X={Xj ,j=1,2,...,17}.
其中，扇区通行性检测指标为{X1，X2，X3，X4}，分别表示扇区流量、扇区航行里程、扇区航行时间和扇区交通流密度；扇区复杂性检测指标为{X5，X6，X7，X8}，分别表示扇区航空器爬升次数、扇区航空器下降次数、扇区航空器改速次数、扇区航空器改航次数；扇区安全性检测指标为{X9，X10}，分别表示扇区短期冲突告警频率和扇区最低安全高度告警频率；扇区经济性检测指标为{X11，X12，X13，X14，X15}，分别表示扇区饱和度、扇区排队长度、扇区航空器延误架次率、扇区航空器延误时间、扇区航空器平均延误时间；管制员工作负荷检测指标为{X16，X17}，分别表示陆空通话信道占用率、陆空通话次数。Among them, the sector trafficability detection index is {X1 , X2 , X3 , X4 }, respectively representing sector flow, sector mileage, sector voyage time and sector traffic flow density; sector complexity detection The indicators are {X5 , X6 , X7 , X8 }, respectively representing the number of climbs of aircraft in the sector, the number of descents of aircraft in the sector, the number of speed changes of aircraft in the sector, and the number of diversions of aircraft in the sector; the safety detection indicators of the sector is {X9 , X10 }, respectively representing the sector short-term conflict warning frequency and the sector minimum safety altitude warning frequency; the sector economy detection index is {X11 , X12 , X13 , X14 , X15 }, Respectively represent sector saturation, sector queuing length, sector aircraft delay rate, sector aircraft delay time, sector aircraft average delay time; controller workload detection index is {X16 , X17 }, which respectively represent land Air call channel occupancy rate, number of land and air calls.
以上内容是结合具体的优选实施方式对本发明所作的进一步详细说明，不能认定本发明的具体实施只局限于这些说明。对于本发明所属技术领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干简单推演或替换，都应当视为属于本发明的保护范围。The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be assumed that the specific implementation of the present invention is limited to these descriptions. For those of ordinary skill in the technical field of the present invention, without departing from the concept of the present invention, some simple deduction or replacement can be made, which should be regarded as belonging to the protection scope of the present invention.
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