技术领域technical field
本发明涉及电力领域，尤其涉及一种变压器运行状态振声检测信号的滤波方法和系统。The invention relates to the field of electric power, in particular to a filtering method and system for a vibration-acoustic detection signal of a transformer operating state.
背景技术Background technique
随着智能电网的高速发展，电力设备安全稳定运行显得尤其重要。目前，对超高压及以上电压等级的电力设备开展运行状态检测，尤其是对异常状态的检测显得愈加重要和迫切。电力变压器作为电力系统的重要组成部分，是变电站中最重要的电气设备之一，其可靠运行关系到电网的安全。一般而言，变压器的异常状态可分为铁芯异常与绕组异常。铁芯异常主要表现为铁芯饱和，绕组异常通常包括绕组变形、绕组松动等。With the rapid development of smart grid, the safe and stable operation of power equipment is particularly important. At present, it is more and more important and urgent to carry out the operation state detection of the power equipment with ultra-high voltage and above voltage level, especially the detection of abnormal state. As an important part of the power system, the power transformer is one of the most important electrical equipment in the substation, and its reliable operation is related to the safety of the power grid. Generally speaking, the abnormal state of the transformer can be divided into iron core abnormality and winding abnormality. Iron core abnormality mainly manifests as iron core saturation, and winding abnormality usually includes winding deformation, winding looseness, etc.
变压器异常状态检测的基本原理是提取变压器运行中的各特征量，分析、辨识并跟踪特征量以此监测变压器的异常运行状态。检测方法按照接触程度可分为侵入式检测和非侵入式检测；按照是否需停机检测可分为带电检测和停电检测；按照检测量类型可以分为电气量法和非电气量法等。相比而言，非侵入式检测可移植性强，安装更方便；带电检测不影响变压器运行；非电气量法与电力系统无电气连接，更为安全。当前变压器运行状态的常用检测方法中，包括检测局部放电的脉冲电流法和超声波检测法、检测绕组变形的频率响应法以及检测机械及电气故障的振动检测法等。这些检测方法主要检测变压器绝缘状况及机械结构状况，其中以变压器振动信号(振声)的检测最为全面，对于大部分变压器故障及异常状态均能有所反应。The basic principle of transformer abnormal state detection is to extract various characteristic quantities in the operation of the transformer, analyze, identify and track the characteristic quantities to monitor the abnormal operation state of the transformer. The detection method can be divided into intrusive detection and non-intrusive detection according to the degree of contact; it can be divided into live detection and power failure detection according to whether shutdown detection is required; according to the type of detection quantity, it can be divided into electrical measurement method and non-electric measurement method. In comparison, non-invasive detection has strong portability and is more convenient to install; live detection does not affect the operation of the transformer; non-electrical measurement method has no electrical connection with the power system, which is safer. The current commonly used detection methods for transformer operation status include pulse current method and ultrasonic detection method for partial discharge detection, frequency response method for detection of winding deformation, and vibration detection method for detection of mechanical and electrical faults. These detection methods mainly detect transformer insulation status and mechanical structure status, among which the detection of transformer vibration signal (vibration sound) is the most comprehensive, and can respond to most transformer faults and abnormal states.
变压器在运行过程中，铁芯硅钢片的磁致伸缩与绕组电动力引起的振动会向四周辐射不同幅值和频率的振声信号。变压器正常运行时对外发出的是均匀的低频噪声；如果发出不均匀声音，则属不正常现象。变压器在不同运行状态下会发出有区别性的声音，可通过对其发出声音的检测，掌握变压器的运行状况。值得关注的是，对变压器不同运行状态下发出声音的检测不仅可以检测很多种引起电气量变化的严重故障，还可以检测许多并未危及绝缘的没有引起电气量变化的异常状态，比如变压器内外部零部件松动等。During the operation of the transformer, the magnetostriction of the iron core silicon steel sheet and the vibration caused by the electromotive force of the winding will radiate vibration and sound signals of different amplitudes and frequencies to the surroundings. When the transformer is in normal operation, it emits uniform low-frequency noise; if it emits uneven sound, it is abnormal. The transformer will emit distinctive sounds under different operating conditions, and the operating status of the transformer can be grasped by detecting the sounds it emits. It is worth noting that the detection of the sound emitted by the transformer under different operating conditions can not only detect many serious faults that cause changes in electrical quantities, but also detect many abnormal conditions that do not endanger insulation and do not cause changes in electrical quantities, such as internal and external transformers. Loose parts, etc.
由于振声检测方法利用了变压器发出的震动信号，很容易受到环境噪声的影响，因此如何有效地识别振声与噪声，是此方法能否成功的关键。现在常用的方法，对此问题重视不够，还未采取有效的措施解决此问题。Since the vibration and sound detection method uses the vibration signal sent by the transformer, it is easily affected by environmental noise. Therefore, how to effectively identify the vibration and noise is the key to the success of this method. The commonly used methods do not pay enough attention to this problem, and no effective measures have been taken to solve this problem.
发明内容Contents of the invention
本发明的目的是提供一种基于小波变换的变压器运行状态振声检测信号滤波方法和系统，所提出的方法利用了不同运行状态下变压器振声信号与背景噪声(包括异常点)在连续小波变换域中的差异，并根据此差异进行滤波，提高了检测信号的信噪比，改善了状态监测的性能。所提出的方法具有较好的鲁棒性，计算简单。The object of the present invention is to provide a kind of wavelet transform-based method and system for filtering the vibration-acoustic detection signal of the transformer operating state. The difference in the domain is filtered according to the difference, which improves the signal-to-noise ratio of the detection signal and improves the performance of condition monitoring. The proposed method is robust and computationally simple.
为实现上述目的，本发明提供了如下方案：To achieve the above object, the present invention provides the following scheme:
一种基于小波变换的变压器运行状态振声检测信号滤波方法，包括：A wavelet transform-based filtering method for vibration-acoustic detection signals of a transformer operating state, comprising:
步骤1，输入实测的振声信号序列S；Step 1, input the measured vibration-acoustic signal sequence S;
步骤2，对所述振声信号序列S进行滤除噪声处理，生成滤除噪声后的数据序列SNEW；具体为：SNEW＝ΦXOPT；其中，Φ为由连续小波变换构成的投影矩阵；XOPT为最佳滤波矢量。Step 2, performing noise-filtering processing on the vibration-acoustic signal sequence S to generate a noise-filtering data sequence SNEW ; specifically: SNEW = ΦXOPT ; where Φ is a projection matrix composed of continuous wavelet transform; XOPT is the optimal filter vector.
一种基于小波变换的变压器运行状态振声检测信号滤波系统，包括：A wavelet transform-based vibration and sound detection signal filtering system for transformer operating status, including:
获取模块，输入实测的振声信号序列S；The acquisition module inputs the measured vibration-acoustic signal sequence S;
滤波模块，对所述振声信号序列S进行滤除噪声处理，生成滤除噪声后的数据序列SNEW；具体为：SNEW＝ΦXOPT；其中，Φ为由连续小波变换构成的投影矩阵；XOPT为最佳滤波矢量。The filter module is used to filter noise processing on the vibration-acoustic signal sequence S, and generate a data sequence SNEW after filtering noise; specifically: SNEW =ΦXOPT ; where, Φ is a projection matrix composed of continuous wavelet transform; XOPT is the optimal filter vector.
根据本发明提供的具体实施例，本发明公开了以下技术效果：According to the specific embodiments provided by the invention, the invention discloses the following technical effects:
虽然变压器振声检测方法在变压器运行状态监测中有着广泛的应用，且技术相对成熟，但是由于振声检测方法利用了变压器发出的振动信号，很容易受到环境噪声的影响，所以此方法在实际工作环境中应用时常常得不到令人满意的结果。本发明的目的是提供一种基于小波变换的变压器运行状态振声检测信号滤波方法和系统，所提出的方法利用了不同运行状态下变压器振声信号与背景噪声(包括异常点)在连续小波变换域中的差异，并根据此差异进行滤波，提高了检测信号的信噪比，改善了状态监测的性能。所提出的方法具有较好的鲁棒性，计算简单。Although the transformer vibration and sound detection method is widely used in the monitoring of transformer operation status, and the technology is relatively mature, but because the vibration and sound detection method uses the vibration signal sent by the transformer, it is easily affected by environmental noise, so this method is not suitable for practical work. Often unsatisfactory results are obtained when applied in the environment. The object of the present invention is to provide a kind of wavelet transform-based method and system for filtering the vibration-acoustic detection signal of the transformer operating state. The difference in the domain is filtered according to the difference, which improves the signal-to-noise ratio of the detection signal and improves the performance of condition monitoring. The proposed method is robust and computationally simple.
附图说明Description of drawings
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍。显而易见，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，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的附图。In order to illustrate the embodiments of the present invention or the technical solutions in the prior art more clearly, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to these drawings without creative efforts.
图1为本发明的流程示意图；Fig. 1 is a schematic flow sheet of the present invention;
图2为本发明的结构示意图；Fig. 2 is a structural representation of the present invention;
图3为本发明具体实施案例的流程示意图。Fig. 3 is a schematic flow chart of a specific implementation case of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述。显然，所描述的实施例仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
为使本发明的上述目的、特征和优点能够更加明显易懂，下面结合附图和具体实施方式对本发明作进一步详细的说明。In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.
图1一种基于小波变换的变压器运行状态振声检测信号滤波方法的流程示意图Fig. 1 Schematic flow chart of a wavelet transform-based filtering method for vibration and sound detection signals of transformer operating status
图1为本发明一种基于小波变换的变压器运行状态振声检测信号滤波方法的流程示意图。如图1所示，所述的一种基于小波变换的变压器运行状态振声检测信号滤波方法具体包括以下步骤：FIG. 1 is a schematic flow chart of a method for filtering vibration and sound detection signals of a transformer operating state based on wavelet transform according to the present invention. As shown in Figure 1, the described method for filtering the vibration and sound detection signal of transformer operating state based on wavelet transform specifically includes the following steps:
步骤1，输入实测的振声信号序列S；Step 1, input the measured vibration-acoustic signal sequence S;
步骤2，对所述振声信号序列S进行滤除噪声处理，生成滤除噪声后的数据序列SNEW；具体为：SNEW＝ΦXOPT；其中，Φ为由连续小波变换构成的投影矩阵；XOPT为最佳滤波矢量。Step 2, performing noise-filtering processing on the vibration-acoustic signal sequence S to generate a noise-filtering data sequence SNEW ; specifically: SNEW = ΦXOPT ; where Φ is a projection matrix composed of continuous wavelet transform; XOPT is the optimal filter vector.
所述步骤2之前，所述方法还包括：Before the step 2, the method also includes:
步骤3，求取所述投影矩阵Φ和最佳滤波矢量XOPT。Step 3, calculating the projection matrix Φ and the optimal filter vector XOPT .
所述步骤3包括：Said step 3 includes:
步骤301，确定所述投影矩阵的列数，具体为：Step 301, determine the number of columns of the projection matrix, specifically:
L＝[10～20]NL=[10～20]N
其中：in:
L：所述投影矩阵的列数L: the number of columns of the projection matrix
N：所述振声信号序列S中元素的个数N: the number of elements in the vibration-acoustic signal sequence S
步骤302，求取所述投影矩阵，具体为：Step 302, obtain the projection matrix, specifically:
其中：in:
ψ[*]：自变量为*的摩尔小波ψ[*]: Moore wavelet with independent variable *
ai：阶数为i的尺度因子ai : scale factor with order i
ai＝2-i,i＝1,2,…,Nai =2-i ,i=1,2,…,N
步骤303，求取所述最佳滤波矢量，具体为：Step 303, obtaining the optimal filter vector, specifically:
第一步：初始化滤波矢量，具体为：X0＝0Step 1: Initialize the filter vector, specifically: X0 =0
第二步：迭代更新滤波矢量，具体为：Step 2: iteratively update the filter vector, specifically:
Xk＝T[Φ*S]+Xk-1，k＝1,2,…Xk ＝T[Φ* S]+Xk-1 ，k＝1,2,...
其中：in:
T：阈值算子，运算T[Φ*S]表示Φ*S中小于阈值0.026的元素重置为0T: Threshold operator, the operation T[Φ* S] means that the elements in Φ* S that are less than the threshold 0.026 are reset to 0
Φ*：所述投影矩阵Φ的伪逆Φ* : the pseudo-inverse of the projection matrix Φ
第三步，不断重复第二步，直至相邻的两次迭代结果XK和XK-1相差小于0.0001，即时，迭代终止，得到所述最佳滤波矢量：XOPT＝XKThe third step is to repeat the second step until the difference between the two adjacent iteration results XK and XK-1 is less than 0.0001, that is , the iteration terminates, and the optimal filter vector is obtained: XOPT =XK
图2一种基于小波变换的变压器运行状态振声检测信号滤波系统的结构意图Fig. 2 Structural diagram of a wavelet transform-based vibration and sound detection signal filtering system for transformer operation
图2为本发明一种基于小波变换的变压器运行状态振声检测信号滤波系统的结构示意图。如图2所示，所述一种基于小波变换的变压器运行状态振声检测信号滤波系统包括以下结构：FIG. 2 is a structural schematic diagram of a wavelet transform-based vibration-acoustic detection signal filtering system for a transformer operating state according to the present invention. As shown in Fig. 2, said a kind of wavelet transform-based vibration-acoustic detection signal filtering system of transformer operating state includes the following structure:
获取模块401，输入实测的振声信号序列S；The acquisition module 401 inputs the measured vibration-acoustic signal sequence S;
滤波模块402，对所述振声信号序列S进行滤除噪声处理，生成滤除噪声后的数据序列SNEW；具体为：SNEW＝ΦXOPT；其中，Φ为由连续小波变换构成的投影矩阵；XOPT为最佳滤波矢量。The filtering module 402 performs noise-filtering processing on the vibration-acoustic signal sequence S to generate a data sequence SNEW after noise filtering; specifically: SNEW =ΦXOPT ; wherein, Φ is a projection matrix composed of continuous wavelet transform ; XOPT is the optimal filter vector.
所述的系统，还包括：The system also includes:
计算模块403，求取所述投影矩阵Φ和最佳滤波矢量XOPT。Calculation module 403, calculating the projection matrix Φ and the optimal filter vector XOPT .
下面提供一个具体实施案例，进一步说明本发明的方案A specific implementation case is provided below to further illustrate the solution of the present invention
图3为本发明具体实施案例的流程示意图。如图3所示，具体包括以下步骤：Fig. 3 is a schematic flow chart of a specific implementation case of the present invention. As shown in Figure 3, it specifically includes the following steps:
1.输入实测的振声信号序列1. Input the measured vibro-acoustic signal sequence
S＝[s1,s2,…,sN-1,sN]S＝[s1 ,s2 ,…,sN-1 ,sN ]
其中：in:
S：实测振声信号数据序列，长度为NS: The measured vibration and sound signal data sequence, the length is N
si,i＝1,2,…,N:序号为i的实测振声信号si ,i=1,2,…,N: measured vibro-acoustic signal with serial number i
2.确定投影矩阵列数2. Determine the number of projection matrix columns
L＝[10～20]NL=[10～20]N
其中：in:
L：所述投影矩阵的列数L: the number of columns of the projection matrix
N：所述振声信号序列S中元素的个数N: the number of elements in the vibration-acoustic signal sequence S
3.求取投影矩阵3. Find the projection matrix
其中：in:
ψ[*]：自变量为*的摩尔小波ψ[*]: Moore wavelet with independent variable *
ai：阶数为i的尺度因子ai : scale factor with order i
ai＝2-i,i＝1,2,…,Nai =2-i ,i=1,2,…,N
4.求取最佳滤波矢量4. Find the best filter vector
第一步：初始化滤波矢量，具体为：X0＝0Step 1: Initialize the filter vector, specifically: X0 =0
第二步：迭代更新滤波矢量，具体为：Step 2: iteratively update the filter vector, specifically:
Xk＝T[Φ*S]+Xk-1，k＝1,2,…Xk ＝T[Φ*S]+Xk-1 ，k＝1,2,...
其中：in:
T：阈值算子，运算T[Φ*S]表示Φ*S中小于阈值0.026的元素重置为0T: Threshold operator, the operation T[Φ* S] means that the elements in Φ* S that are less than the threshold 0.026 are reset to 0
Φ*：所述投影矩阵Φ的伪逆Φ* : the pseudo-inverse of the projection matrix Φ
第三步，不断重复第二步，直至相邻的两次迭代结果XK和XK-1相差小于0.0001，即时，迭代终止，得到所述最佳滤波矢量：XOPT＝XKThe third step is to repeat the second step until the difference between the two adjacent iteration results XK and XK-1 is less than 0.0001, that is , the iteration terminates, and the optimal filter vector is obtained: XOPT =XK
5.滤波5. Filtering
对所述振声信号序列S进行滤除噪声处理，生成滤除噪声后的数据序列SNEW；具体为：SNEW＝ΦXOPT；其中，Φ为由连续小波变换构成的投影矩阵；XOPT为最佳滤波矢量。Perform noise filtering processing on the vibration-acoustic signal sequence S to generate a data sequence SNEW after filtering noise; specifically: SNEW =ΦXOPT ; where, Φ is a projection matrix composed of continuous wavelet transform; XOPT is Best filtered vector.
本说明书中各个实施例采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似部分互相参见即可。对于实施例公开的系统而言，由于其与实施例公开的方法相对应，所以描述较为简单，相关之处参见方法部分说明即可。Each embodiment in this specification is described in a progressive manner, each embodiment focuses on the difference from other embodiments, and the same and similar parts of each embodiment can be referred to each other. As for the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and for relevant details, please refer to the description of the method part.
本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处。综上所述，本说明书内容不应理解为对本发明的限制。In this paper, specific examples have been used to illustrate the principle and implementation of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; meanwhile, for those of ordinary skill in the art, according to the present invention Thoughts, there will be changes in specific implementation methods and application ranges. In summary, the contents of this specification should not be construed as limiting the present invention.
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