技术领域Technical Field
本发明属于输电线路检测领域，具体地说，涉及一种用于输电线路的光电检测方法。The invention belongs to the field of power transmission line detection, and in particular, relates to a photoelectric detection method for power transmission lines.
背景技术Background Art
常规输电线路的光电检测技术主要用于监测输电线路的运行状态，识别和评估线路表面污染、金属部件腐蚀、线路损伤以及其他潜在故障。Photoelectric detection technology for conventional transmission lines is mainly used to monitor the operating status of transmission lines, identify and evaluate line surface contamination, corrosion of metal components, line damage and other potential faults.
地面设备的检测受限于视角和距离，难以准确捕捉高空输电线路的细微变化，容易遗漏小范围的污染和腐蚀问题，导致潜在故障无法及时发现和处理。而且不同检测设备采集的数据格式和类型各异，缺乏统一的分析平台，导致数据整合和综合分析困难，无法形成全面、准确的检测报告，影响维护决策的有效性。传统方法主要依赖静态数据，缺乏对历史数据的动态分析和未来故障的预测能力，无法提供有效的预测性维护建议，容易导致突发故障和紧急维护。The detection of ground equipment is limited by the viewing angle and distance, and it is difficult to accurately capture the subtle changes of high-altitude transmission lines. It is easy to miss small-scale pollution and corrosion problems, resulting in the inability to timely discover and deal with potential faults. In addition, the data formats and types collected by different detection equipment are different, and there is a lack of a unified analysis platform, which makes data integration and comprehensive analysis difficult, and it is impossible to form a comprehensive and accurate detection report, affecting the effectiveness of maintenance decisions. Traditional methods mainly rely on static data, lack the ability to dynamically analyze historical data and predict future faults, and cannot provide effective predictive maintenance suggestions, which easily leads to sudden failures and emergency maintenance.
有鉴于此特提出本发明。In view of this, the present invention is proposed.
发明内容Summary of the invention
本发明要解决的技术问题在于克服现有技术的不足，提供一种用于输电线路的光电检测方法，解决了上述背景技术中提出的问题。The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a photoelectric detection method for a power transmission line, thereby solving the problems raised in the above-mentioned background technology.
为解决上述技术问题，本发明采用技术方案的基本构思是：In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:
一种用于输电线路的光电检测方法，包括：a)提供无人机光电检测系统并使用无人机光电检测系统采集输电线路的图像数据；A photoelectric detection method for a power transmission line comprises: a) providing a drone photoelectric detection system and using the drone photoelectric detection system to collect image data of the power transmission line;
b)将无人机系统采集的图像数据通过无线传输设备传输至中央控制系统识别表面的污染程度和金属部件腐蚀情况；b) Transmit the image data collected by the UAV system to the central control system through wireless transmission equipment to identify the degree of surface contamination and corrosion of metal parts;
c)将无人机采集的表面的污染程度和金属部件腐蚀情况进行融合，并进行综合分析，生成更加全面的检测结果；c) Integrate the surface contamination level and metal component corrosion conditions collected by the drone and conduct a comprehensive analysis to generate more comprehensive test results;
d)对检测结果进行历史数据对比分析，识别出长期趋势和潜在故障点，实现预测性维护，并通过无线网络将检测结果和维护建议实时传送至移动终端。d) Conduct historical data comparison and analysis on the test results to identify long-term trends and potential failure points, implement predictive maintenance, and transmit the test results and maintenance recommendations to mobile terminals in real time via wireless networks.
可选的，所述无人机光电检测系统包括可见光相机、红外相机或紫外相机、多光谱相机，所述相机安装于机上稳定平台之中。Optionally, the unmanned aerial vehicle photoelectric detection system includes a visible light camera, an infrared camera or an ultraviolet camera, and a multi-spectral camera, and the camera is installed on a stable platform on the aircraft.
可选的，无人机在获取输电线路的污染程度的图像数据时执行以下步骤：Optionally, the drone performs the following steps when acquiring image data of the pollution degree of the power transmission line:
利用GIS和输电线路数据，确定需要检测的具体区域并识别关键点；Using GIS and transmission line data, determine specific areas that need to be inspected and identify critical points;
确定飞行路线的起点、终点和路径点，每个根据检测的输电线路设定飞行高度和速度和停留时间及其位置；Determine the starting point, end point and waypoints of the flight route, each setting the flight altitude and speed and dwell time according to the detected power transmission line and its location;
启动无人机，使用自动飞行模式按照预设路线进行飞行，地面站实时监控无人机的位置、速度、高度和传感器状态；Start the drone and use the automatic flight mode to fly along the preset route. The ground station monitors the drone's position, speed, altitude and sensor status in real time.
在达到取样地点后使用高分辨率摄像机采集输电线路的高清图像，并使用红外相机采集输电线路的温度分布图像，识别热点和温度异常区域，最后采用多光谱相机采集不同波段的反射数据；After reaching the sampling location, a high-resolution camera is used to collect high-definition images of the transmission line, and an infrared camera is used to collect temperature distribution images of the transmission line to identify hot spots and temperature anomaly areas. Finally, a multispectral camera is used to collect reflection data in different bands;
无人机飞行过程中，通过Wi-Fi、4G/5G实时将数据传输到地面站。During the flight of the drone, data is transmitted to the ground station in real time via Wi-Fi and 4G/5G.
可选的，无人机对输电线路图像数据中的表面的污染程度进行检测时的步骤为：Optionally, the steps for the drone to detect the degree of contamination on the surface of the transmission line image data are as follows:
获取污染程度的历史数据并将历史数据分为训练集和测试集，构建卷积神经网络(CNN)并使用训练集训练卷积神经网络(CNN)；Obtain historical data on pollution levels and divide the historical data into a training set and a test set, build a convolutional neural network (CNN), and use the training set to train the convolutional neural network (CNN);
对接收到的图像数据进行噪声过滤，去除图像中的干扰噪声并增强图像对比度，突出输电线路表面的细节，使用Canny边缘检测算法识别图像中的显著边缘；Perform noise filtering on the received image data to remove interference noise in the image and enhance the image contrast, highlight the details of the transmission line surface, and use the Canny edge detection algorithm to identify significant edges in the image;
从预处理后的图像中提取输电线路表面的颜色特征、纹理特征和形状特征，将提取的特征向量输入到预先训练好的卷积神经网络(CNN)中；Extract color features, texture features, and shape features of the transmission line surface from the preprocessed image, and input the extracted feature vector into a pre-trained convolutional neural network (CNN);
从预处理后的图像中提取输电线路表面的特征，包括颜色、纹理和形状特征并将得到的特征输入到卷积神经网络(CNN)中，经过多层卷积、池化和全连接层，输出输电线路的污染区域掩码；Extract the surface features of the power transmission line from the preprocessed image, including color, texture and shape features, and input the obtained features into the convolutional neural network (CNN). After multiple layers of convolution, pooling and full connection layers, the contaminated area mask of the power transmission line is output;
根据识别出的污染区域，计算污染面积和污染程度，并将污染区域和污染程度的数据可视化，生成污染检测数据；According to the identified pollution areas, the pollution area and pollution degree are calculated, and the data of pollution area and pollution degree are visualized to generate pollution detection data;
将检测数据通过无线传输设备传输至移动终端。The detection data is transmitted to the mobile terminal via wireless transmission equipment.
可选的，无人机在获取输电线路的金属部位腐蚀程度的图像数据时执行以下步骤：Optionally, the drone performs the following steps when acquiring image data of the corrosion degree of the metal part of the transmission line:
控制无人直升机飞行至目标金属部件的位置，并利用GPS和图像识别技术进行精确定位；Control the unmanned helicopter to fly to the location of the target metal part and use GPS and image recognition technology to accurately locate it;
使用高分辨率可见光相机拍摄金属部位的高清图像，捕捉腐蚀、锈蚀和表面损伤，并使用紫外相机进行图像数据的采集，最后使用多光谱相机采集不同波段的图像数据，分析金属部位的光谱特征；Use a high-resolution visible light camera to capture high-definition images of metal parts to capture corrosion, rust and surface damage, and use an ultraviolet camera to collect image data. Finally, use a multispectral camera to collect image data in different bands to analyze the spectral characteristics of metal parts.
将采集到的金属部位腐蚀程度的图像数据传输到地面站进行分析。The collected image data of the corrosion degree of metal parts are transmitted to the ground station for analysis.
将红外相机采集的图像数据传输至中央控制系统，利用温度分析算法，检测金属部件表面的温度分布情况，识别温度异常区域，初步判断腐蚀位置。The image data collected by the infrared camera is transmitted to the central control system, and the temperature analysis algorithm is used to detect the temperature distribution on the surface of the metal parts, identify the abnormal temperature areas, and preliminarily determine the corrosion location.
将紫外相机采集的图像数据传输至中央控制系统，利用电晕放电检测算法，识别金属部件表面的电晕放电现象，进一步确认腐蚀区域；The image data collected by the UV camera is transmitted to the central control system, and the corona discharge detection algorithm is used to identify the corona discharge phenomenon on the surface of the metal parts and further confirm the corrosion area;
将可见光相机采集的高分辨率图像传输至中央控制系统，利用边缘检测和纹理分析技术，识别金属表面的腐蚀斑点和腐蚀坑洞，精确定位腐蚀位置和程度；The high-resolution images collected by the visible light camera are transmitted to the central control system, and the corrosion spots and pits on the metal surface are identified using edge detection and texture analysis technology to accurately locate the location and extent of corrosion;
综合热成像、紫外成像和可见光图像的数据，通过多源数据融合技术，对不同波段的数据进行对齐和融合，生成金属部件的腐蚀检测模型。The data of thermal imaging, ultraviolet imaging and visible light images are integrated, and the data of different bands are aligned and fused through multi-source data fusion technology to generate a corrosion detection model for metal parts.
可选的，将无人机采集的表面的污染程度和金属部件腐蚀情况进行融合，并进行综合分析，生成更加全面的检测结果的步骤为：Optionally, the contamination level of the surface collected by the drone and the corrosion of the metal parts are integrated and analyzed comprehensively to generate more comprehensive test results:
将不同波段和不同检测对象的数据对齐；Align data from different bands and different detection objects;
综合不同传感器的数据，生成统一的检测模型，利用多源数据融合技术，将红外、紫外和可见光图像的数据融合；Integrate data from different sensors to generate a unified detection model, and use multi-source data fusion technology to fuse infrared, ultraviolet and visible light image data;
对融合后的数据进行全面分析，识别出潜在的故障点和风险区域，生成综合检测报告；Comprehensively analyze the fused data, identify potential fault points and risk areas, and generate a comprehensive inspection report;
根据综合检测报告，提供详细的维护建议，包括需要立即处理的故障点和长期监控的风险区域。Based on the comprehensive inspection report, detailed maintenance recommendations are provided, including fault points that require immediate attention and risk areas for long-term monitoring.
可选的，对检测结果进行历史数据对比分析，识别出长期趋势和潜在故障点，实现预测性维护的步骤为：Optionally, historical data comparison and analysis of the test results can be performed to identify long-term trends and potential failure points. The steps to achieve predictive maintenance are as follows:
将无人机采集到的当前检测结果存储到中央控制系统中的数据库中，并与历史检测数据进行整合，使用数据挖掘和统计分析方法，对比当前检测数据与历史数据，识别变化趋势；The current detection results collected by the drone are stored in the database of the central control system and integrated with the historical detection data. Data mining and statistical analysis methods are used to compare the current detection data with the historical data to identify the change trend.
提取污染面积Ap、腐蚀程度Ce、热点温度Th和电晕放电强度Dc，并将提取的特征表示为向量Xi，并选择聚类数k，随机选择k个初始聚类中心μj，对于每个向量Xi，通过迭代的方式计算向量Xi到所有聚类中心μj的距离，并将向量Xi分配到最近的聚类中心，其表达式为：最后根据获取的最近的聚类中心来识别数据中的模式和异常变化；Extract the contaminated areaAp , corrosion degreeCe , hot spot temperatureTh and corona discharge intensityDc , and express the extracted features as vectorXi , select the cluster number k, randomly select k initial cluster centersμj , and for each vectorXi , calculate the distance from vectorXi to all cluster centersμj in an iterative manner, and assign vectorXi to the nearest cluster center. The expression is: Finally, the patterns and abnormal changes in the data are identified based on the nearest cluster centers obtained;
使用时间序列分析模型预测未来可能发生故障的位置和时间；Use time series analysis models to predict where and when future failures may occur;
根据分析结果生成预测性维护建议，通过无线网络实时传送至相关人员的移动终端。Generate predictive maintenance recommendations based on the analysis results and transmit them to the mobile terminals of relevant personnel in real time via wireless networks.
可选的，使用时间序列分析模型预测未来可能发生故障的位置和时间的步骤为：Optionally, the steps to use the time series analysis model to predict the location and time of possible future failures are:
获取污染面积、腐蚀程度、热点温度、电晕放电强度的时间序列Yt，训练ARIMA模型以拟合历史数据，并使用训练好的模型进行对输电线路的数据进行预测，其表达式为：其中，h为预测步长。The time series Yt of pollution area, corrosion degree, hot spot temperature, and corona discharge intensity are obtained, and the ARIMA model is trained to fit the historical data. The trained model is used to predict the data of the transmission line. The expression is: Among them, h is the prediction step size.
采用上述技术方案后，本发明与现有技术相比具有以下有益效果，当然，实施本发明的任一产品并不一定需要同时达到以下所述的所有优点：After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art. Of course, any product implementing the present invention does not necessarily need to achieve all the advantages described below at the same time:
利用可见光相机、红外相机、紫外相机和多光谱相机，全面采集输电线路的污染程度和金属部件的腐蚀情况，并通过无线传输设备将数据实时传输至中央控制系统，实现对输电线路表面污染和金属部件腐蚀的综合分析。利用历史数据和卷积神经网络(CNN)进行图像处理和模式识别，通过多源数据融合技术对不同波段数据进行对齐和融合，生成统一的检测模型，识别潜在故障点和风险区域。最终，利用时间序列分析模型预测未来可能发生的故障位置和时间，并生成详细的预测性维护建议，实时传送至相关人员的移动终端，实现了对输电线路的高频次全面监控和预测性维护，降低了维护成本和故障风险。Visible light cameras, infrared cameras, ultraviolet cameras and multispectral cameras are used to comprehensively collect the pollution level of transmission lines and the corrosion of metal parts, and the data is transmitted to the central control system in real time through wireless transmission equipment to achieve a comprehensive analysis of the surface pollution of transmission lines and the corrosion of metal parts. Historical data and convolutional neural networks (CNN) are used for image processing and pattern recognition. Multi-source data fusion technology is used to align and fuse data from different bands to generate a unified detection model to identify potential fault points and risk areas. Finally, a time series analysis model is used to predict the location and time of possible future faults, and detailed predictive maintenance recommendations are generated and transmitted to the mobile terminals of relevant personnel in real time, achieving high-frequency comprehensive monitoring and predictive maintenance of transmission lines, reducing maintenance costs and fault risks.
下面结合附图对本发明的具体实施方式做进一步详细的描述。The specific implementation modes of the present invention are further described in detail below with reference to the accompanying drawings.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
下面描述中的附图仅仅是一些实施例，对于本领域普通技术人员来说，在不付出创造性劳动的前提下，还可以根据这些附图获得其他附图。在附The drawings described below are only some embodiments. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.
图中：In the figure:
图1为用于输电线路的光电检测方法流程图。FIG1 is a flow chart of a photoelectric detection method for a power transmission line.
需要说明的是，这些附图和文字描述并不旨在以任何方式限制本发明的构思范围，而是通过参考特定实施例为本领域技术人员说明本发明的概念。It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments.
具体实施方式DETAILED DESCRIPTION
现在结合附图对本发明做进一步详细的说明。The present invention will now be described in further detail with reference to the accompanying drawings.
请参阅图1所示，在本实施例中提供了一种用于输电线路的光电检测方法，包括如下步骤：Referring to FIG. 1 , in this embodiment, a photoelectric detection method for a power transmission line is provided, comprising the following steps:
a)提供无人机光电检测系统并使用无人机光电检测系统采集输电线路的图像数据；a) Provide a UAV photoelectric detection system and use the UAV photoelectric detection system to collect image data of the transmission line;
b)将无人机系统采集的图像数据通过无线传输设备传输至中央控制系统识别表面的污染程度和金属部件腐蚀情况；b) Transmit the image data collected by the UAV system to the central control system through wireless transmission equipment to identify the degree of surface contamination and corrosion of metal parts;
c)将无人机采集的表面的污染程度和金属部件腐蚀情况进行融合，并进行综合分析，生成更加全面的检测结果；c) Integrate the surface contamination level and metal component corrosion conditions collected by the drone and conduct a comprehensive analysis to generate more comprehensive test results;
d)对检测结果进行历史数据对比分析，识别出长期趋势和潜在故障点，实现预测性维护，并通过无线网络将检测结果和维护建议实时传送至移动终端。d) Conduct historical data comparison and analysis on the test results to identify long-term trends and potential failure points, implement predictive maintenance, and transmit the test results and maintenance recommendations to mobile terminals in real time via wireless networks.
需要说明的是：本申请使用无人机光电检测系统采集输电线路的图像数据并通过无线传输设备将数据传输至中央控制系统，以识别表面的污染程度和金属部件的腐蚀情况，然后将这些数据进行融合和综合分析，生成更加全面的检测结果，接着对检测结果进行历史数据对比分析，识别出长期趋势和潜在故障点，实现预测性维护，最终通过无线网络将检测结果和维护建议实时传送至移动终端，这一过程的好处在于能够显著提升输电线路的维护效率和准确性，通过实时和历史数据的综合分析，不仅可以及时发现并处理当前的故障，还能预测未来可能发生的问题，从而预防故障的发生，延长输电设备的使用寿命，同时减少停电时间和维护成本，提高电网的可靠性和稳定性，并确保维护人员能够在第一时间获取最新的检测信息和建议，从而更高效地开展维护工作。It should be noted that: this application uses a drone photoelectric detection system to collect image data of the transmission line and transmit the data to the central control system through wireless transmission equipment to identify the degree of surface contamination and corrosion of metal parts, and then integrates and comprehensively analyzes these data to generate more comprehensive detection results. The detection results are then compared and analyzed with historical data to identify long-term trends and potential fault points, and predictive maintenance is achieved. Finally, the detection results and maintenance suggestions are transmitted to the mobile terminal in real time through the wireless network. The benefit of this process is that it can significantly improve the maintenance efficiency and accuracy of the transmission line. Through the comprehensive analysis of real-time and historical data, not only can current faults be discovered and handled in a timely manner, but also possible problems in the future can be predicted, thereby preventing the occurrence of faults and extending the service life of transmission equipment. At the same time, it reduces power outage time and maintenance costs, improves the reliability and stability of the power grid, and ensures that maintenance personnel can obtain the latest detection information and suggestions as soon as possible, so as to carry out maintenance work more efficiently.
本实施例的所述无人机光电检测系统包括可见光相机、红外相机或紫外相机、多光谱相机，所述相机安装于机上稳定平台之中。The unmanned aerial vehicle photoelectric detection system of this embodiment includes a visible light camera, an infrared camera or an ultraviolet camera, and a multi-spectral camera, and the cameras are installed in a stable platform on the aircraft.
本实施例的无人机在获取输电线路的污染程度的图像数据时执行以下步骤：The drone of this embodiment performs the following steps when acquiring image data of the pollution degree of the power transmission line:
利用GIS和输电线路数据，确定需要检测的具体区域并识别关键点；Using GIS and transmission line data, determine specific areas that need to be inspected and identify critical points;
确定飞行路线的起点、终点和路径点，每个根据检测的输电线路设定飞行高度和速度和停留时间及其位置；Determine the starting point, end point and waypoints of the flight route, each setting the flight altitude and speed and dwell time according to the detected power transmission line and its location;
启动无人机，使用自动飞行模式按照预设路线进行飞行，地面站实时监控无人机的位置、速度、高度和传感器状态；Start the drone and use the automatic flight mode to fly along the preset route. The ground station monitors the drone's position, speed, altitude and sensor status in real time.
在达到取样地点后使用高分辨率摄像机采集输电线路的高清图像，并使用红外相机采集输电线路的温度分布图像，识别热点和温度异常区域，最后采用多光谱相机采集不同波段的反射数据；After reaching the sampling location, a high-resolution camera is used to collect high-definition images of the transmission line, and an infrared camera is used to collect temperature distribution images of the transmission line to identify hot spots and temperature anomaly areas. Finally, a multispectral camera is used to collect reflection data in different bands;
无人机飞行过程中，通过Wi-Fi、4G/5G实时将数据传输到地面站。本申请通过高分辨率图像和多光谱反射数据的综合使用，能够更准确地识别和定位污染和异常区域，确保数据的实时传输和监控，提高检测效率和数据的及时性，使得维护人员能够迅速获得全面的检测信息，从而进行及时和有效的维护，保障输电线路的稳定运行。During the flight of the drone, data is transmitted to the ground station in real time via Wi-Fi, 4G/5G. This application can more accurately identify and locate pollution and abnormal areas through the comprehensive use of high-resolution images and multi-spectral reflectance data, ensure real-time data transmission and monitoring, improve detection efficiency and data timeliness, and enable maintenance personnel to quickly obtain comprehensive detection information, thereby performing timely and effective maintenance and ensuring the stable operation of the transmission line.
本实施例的无人机对输电线路图像数据中的表面的污染程度进行检测时的步骤为：The steps for the drone of this embodiment to detect the degree of contamination on the surface of the power transmission line image data are as follows:
获取污染程度的历史数据并将历史数据分为训练集和测试集，构建卷积神经网络(CNN)并使用训练集训练卷积神经网络(CNN)；Obtain historical data on pollution levels and divide the historical data into a training set and a test set, build a convolutional neural network (CNN), and use the training set to train the convolutional neural network (CNN);
对接收到的图像数据进行噪声过滤，去除图像中的干扰噪声并增强图像对比度，突出输电线路表面的细节，使用Canny边缘检测算法识别图像中的显著边缘；Perform noise filtering on the received image data to remove interference noise in the image and enhance the image contrast, highlight the details of the transmission line surface, and use the Canny edge detection algorithm to identify significant edges in the image;
从预处理后的图像中提取输电线路表面的颜色特征、纹理特征和形状特征，将提取的特征向量输入到预先训练好的卷积神经网络(CNN)中；Extract color features, texture features, and shape features of the transmission line surface from the preprocessed image, and input the extracted feature vector into a pre-trained convolutional neural network (CNN);
从预处理后的图像中提取输电线路表面的特征，包括颜色、纹理和形状特征并将得到的特征输入到卷积神经网络(CNN)中，经过多层卷积、池化和全连接层，输出输电线路的污染区域掩码；Extract the surface features of the power transmission line from the preprocessed image, including color, texture and shape features, and input the obtained features into the convolutional neural network (CNN). After multiple layers of convolution, pooling and full connection layers, the contaminated area mask of the power transmission line is output;
根据识别出的污染区域，计算污染面积和污染程度，并将污染区域和污染程度的数据可视化，生成污染检测数据；According to the identified pollution areas, the pollution area and pollution degree are calculated, and the data of pollution area and pollution degree are visualized to generate pollution detection data;
将检测数据通过无线传输设备传输至移动终端。The detection data is transmitted to the mobile terminal via wireless transmission equipment.
需要说明的是：利用CNN对历史数据进行训练，能够实现高效准确的污染检测；图像预处理步骤有效地提高了检测的精确性，而对特征的提取和处理确保了CNN能够识别和量化污染区域；实时数据传输使得维护人员能够快速获取检测结果，从而及时采取必要的维护措施，提升输电线路的维护效率和可靠性。It should be noted that: using CNN to train historical data can achieve efficient and accurate pollution detection; the image preprocessing step effectively improves the accuracy of detection, and the extraction and processing of features ensure that CNN can identify and quantify polluted areas; real-time data transmission enables maintenance personnel to quickly obtain detection results, so as to take necessary maintenance measures in time and improve the maintenance efficiency and reliability of transmission lines.
本实施例的无人机在获取输电线路的金属部位腐蚀程度的图像数据时执行以下步骤：The drone of this embodiment performs the following steps when acquiring image data of the corrosion degree of the metal parts of the transmission line:
控制无人直升机飞行至目标金属部件的位置，并利用GPS和图像识别技术进行精确定位；Control the unmanned helicopter to fly to the location of the target metal part and use GPS and image recognition technology to accurately locate it;
使用高分辨率可见光相机拍摄金属部位的高清图像，捕捉腐蚀、锈蚀和表面损伤，并使用紫外相机进行图像数据的采集，最后使用多光谱相机采集不同波段的图像数据，分析金属部位的光谱特征；Use a high-resolution visible light camera to capture high-definition images of metal parts to capture corrosion, rust and surface damage, and use an ultraviolet camera to collect image data. Finally, use a multispectral camera to collect image data in different bands to analyze the spectral characteristics of metal parts.
将采集到的金属部位腐蚀程度的图像数据传输到地面站进行分析。The collected image data of the corrosion degree of metal parts are transmitted to the ground station for analysis.
将红外相机采集的图像数据传输至中央控制系统，利用温度分析算法，检测金属部件表面的温度分布情况，识别温度异常区域，初步判断腐蚀位置。The image data collected by the infrared camera is transmitted to the central control system, and the temperature analysis algorithm is used to detect the temperature distribution on the surface of the metal parts, identify the abnormal temperature areas, and preliminarily determine the corrosion location.
将紫外相机采集的图像数据传输至中央控制系统，利用电晕放电检测算法，识别金属部件表面的电晕放电现象，进一步确认腐蚀区域；The image data collected by the UV camera is transmitted to the central control system, and the corona discharge detection algorithm is used to identify the corona discharge phenomenon on the surface of the metal parts and further confirm the corrosion area;
将可见光相机采集的高分辨率图像传输至中央控制系统，利用边缘检测和纹理分析技术，识别金属表面的腐蚀斑点和腐蚀坑洞，精确定位腐蚀位置和程度；The high-resolution images collected by the visible light camera are transmitted to the central control system, and the corrosion spots and pits on the metal surface are identified using edge detection and texture analysis technology to accurately locate the location and extent of corrosion;
综合热成像、紫外成像和可见光图像的数据，通过多源数据融合技术，对不同波段的数据进行对齐和融合，生成金属部件的腐蚀检测模型。通过多源数据融合技术，对不同波段的数据进行对齐和融合，生成金属部件的腐蚀检测模型。这一过程的好处在于，通过多种传感器和成像技术的结合，实现了对输电线路金属部件腐蚀状况的全面、精准检测，能够及时发现并定位腐蚀区域，有助于提前采取维护措施，延长设备寿命，保障电网的安全稳定运行，同时多源数据融合技术的应用，提高了检测结果的准确性。The data of thermal imaging, ultraviolet imaging and visible light images are integrated, and the data of different bands are aligned and fused through multi-source data fusion technology to generate a corrosion detection model for metal parts. The advantage of this process is that through the combination of multiple sensors and imaging technologies, a comprehensive and accurate detection of the corrosion status of metal parts of the transmission line is achieved, which can timely detect and locate the corrosion area, help to take maintenance measures in advance, extend the life of equipment, and ensure the safe and stable operation of the power grid. At the same time, the application of multi-source data fusion technology improves the accuracy of the detection results.
本实施例的将无人机采集的表面的污染程度和金属部件腐蚀情况进行融合，并进行综合分析，生成更加全面的检测结果的步骤为：In this embodiment, the steps of integrating the surface pollution degree and the corrosion condition of metal parts collected by the drone and performing comprehensive analysis to generate a more comprehensive detection result are as follows:
将不同波段和不同检测对象的数据对齐；Align data from different bands and different detection objects;
综合不同传感器的数据，生成统一的检测模型，利用多源数据融合技术，将红外、紫外和可见光图像的数据融合；Integrate data from different sensors to generate a unified detection model, and use multi-source data fusion technology to fuse infrared, ultraviolet and visible light image data;
对融合后的数据进行全面分析，识别出潜在的故障点和风险区域，生成综合检测报告；Comprehensively analyze the fused data, identify potential fault points and risk areas, and generate a comprehensive inspection report;
根据综合检测报告，提供详细的维护建议，包括需要立即处理的故障点和长期监控的风险区域。Based on the comprehensive inspection report, detailed maintenance recommendations are provided, including fault points that require immediate attention and risk areas for long-term monitoring.
需要说明的是：通过数据对齐和多源数据融合技术的应用，能够综合不同传感器的数据，生成更加精准和全面的检测结果；对融合数据的全面分析，可以准确识别潜在的故障点和风险区域，生成的综合检测报告为维护提供了详细的指导，确保及时和有效的维护措施，提高输电线路的运行可靠性和维护效率，减少故障发生的概率，并延长设备的使用寿命。It should be noted that: through the application of data alignment and multi-source data fusion technology, the data from different sensors can be integrated to generate more accurate and comprehensive detection results; comprehensive analysis of fused data can accurately identify potential fault points and risk areas, and the generated comprehensive detection report provides detailed guidance for maintenance, ensuring timely and effective maintenance measures, improving the operational reliability and maintenance efficiency of transmission lines, reducing the probability of failures, and extending the service life of equipment.
本实施例对检测结果进行历史数据对比分析，识别出长期趋势和潜在故障点，实现预测性维护的步骤为：This embodiment performs historical data comparison and analysis on the detection results to identify long-term trends and potential failure points. The steps for implementing predictive maintenance are as follows:
将无人机采集到的当前检测结果存储到中央控制系统中的数据库中，并与历史检测数据进行整合，使用数据挖掘和统计分析方法，对比当前检测数据与历史数据，识别变化趋势；The current detection results collected by the drone are stored in the database of the central control system and integrated with the historical detection data. Data mining and statistical analysis methods are used to compare the current detection data with the historical data to identify the change trend.
提取污染面积Ap、腐蚀程度Ce、热点温度Th和电晕放电强度Dc，并将提取的特征表示为向量Xi，并选择聚类数k，随机选择k个初始聚类中心μj，对于每个向量Xi，通过迭代的方式计算向量Xi到所有聚类中心μj的距离，并将向量Xi分配到最近的聚类中心，其表达式为：最后根据获取的最近的聚类中心来识别数据中的模式和异常变化；Extract the contaminated areaAp , corrosion degreeCe , hot spot temperatureTh and corona discharge intensityDc , and express the extracted features as vectorXi , select the cluster number k, randomly select k initial cluster centersμj , and for each vectorXi , calculate the distance from vectorXi to all cluster centersμj in an iterative manner, and assign vectorXi to the nearest cluster center. The expression is: Finally, the patterns and abnormal changes in the data are identified based on the nearest cluster centers obtained;
使用时间序列分析模型预测未来可能发生故障的位置和时间；Use time series analysis models to predict where and when future failures may occur;
根据分析结果生成预测性维护建议，通过无线网络实时传送至相关人员的移动终端。Generate predictive maintenance recommendations based on the analysis results and transmit them to the mobile terminals of relevant personnel in real time via wireless networks.
需要说明的是：通过对检测结果进行历史数据对比分析，识别出长期趋势和潜在故障点，实现预测性维护的步骤，能够显著提升输电线路的维护效率和准确性。首先，将无人机采集到的当前检测结果存储并与历史检测数据整合，通过数据挖掘和统计分析方法识别变化趋势；然后，提取关键特征并通过聚类分析识别数据中的模式和异常变化，聚类分析有助于识别出设备健康状态的不同类别；接着，使用时间序列分析模型预测未来可能发生故障的位置和时间，提供故障发生的预警；最后，根据综合分析生成详细的预测性维护建议，并通过无线网络实时传送至相关人员的移动终端，使得维护团队能够提前采取预防措施，减少突发故障的发生，提高输电线路的运行可靠性。It should be noted that by comparing and analyzing the historical data of the test results, identifying long-term trends and potential fault points, and implementing predictive maintenance steps, the maintenance efficiency and accuracy of the transmission line can be significantly improved. First, the current test results collected by the drone are stored and integrated with the historical test data, and the trend of change is identified through data mining and statistical analysis methods; then, key features are extracted and patterns and abnormal changes in the data are identified through cluster analysis. Cluster analysis helps to identify different categories of equipment health status; then, the time series analysis model is used to predict the location and time of possible future failures and provide early warning of the occurrence of failures; finally, detailed predictive maintenance recommendations are generated based on the comprehensive analysis and transmitted to the mobile terminals of relevant personnel in real time through wireless networks, so that the maintenance team can take preventive measures in advance, reduce the occurrence of sudden failures, and improve the operational reliability of the transmission line.
本实施例的使用时间序列分析模型预测未来可能发生故障的位置和时间的步骤为：The steps of using the time series analysis model to predict the location and time of possible future failures in this embodiment are:
获取污染面积、腐蚀程度、热点温度、电晕放电强度的时间序列Yt，训练ARIMA模型以拟合历史数据，并使用训练好的模型进行对输电线路的数据进行预测，其表达式为：其中，h为预测步长。The time series Yt of pollution area, corrosion degree, hot spot temperature, and corona discharge intensity are obtained, and the ARIMA model is trained to fit the historical data. The trained model is used to predict the data of the transmission line. The expression is: Among them, h is the prediction step size.
需要说明的是：利用ARIMA模型能够捕捉时间序列数据中的规律和趋势，生成对未来故障发生位置和时间的预测。这样可以提前识别潜在的故障点，使维护人员能够及时采取预防措施，减少突发故障的发生，提高输电线路的运行可靠性和稳定性，并优化维护计划，降低维护成本，延长设备使用寿命。通过这种预测性维护方法，可以有效提升电力系统的整体效率和安全性。It should be noted that the ARIMA model can capture the rules and trends in time series data and generate predictions for the location and time of future faults. This can identify potential fault points in advance, allowing maintenance personnel to take preventive measures in a timely manner, reduce the occurrence of sudden faults, improve the operational reliability and stability of transmission lines, optimize maintenance plans, reduce maintenance costs, and extend the service life of equipment. This predictive maintenance method can effectively improve the overall efficiency and safety of the power system.
本发明不局限于上述实施方式，任何人应得知在本发明的启示下作出的结构变化，凡是与本发明具有相同或相近的技术方案，均落入本发明的保护范围之内。本发明未详细描述的技术、形状、构造部分均为公知技术。The present invention is not limited to the above-mentioned embodiments. Anyone should be aware that any structural changes made under the enlightenment of the present invention, and any technical solutions that are the same or similar to the present invention, fall within the protection scope of the present invention. The technology, shape, and structural parts not described in detail in the present invention are all well-known technologies.
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| CN119653322A (en)* | 2025-02-13 | 2025-03-18 | 山东轻智信息科技有限公司 | A data transmission method for a top-mounted ultraviolet pan-tilt camera based on a wireless communication network |
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