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Feature extraction method for distribution switch mechanical faults based on ceemdan and weighted time-frequency entropy

A technology for mechanical faults and power distribution switches, applied in the field of power distribution networks, can solve the problems of fatigue of disassembly and maintenance components, new faults, time-consuming and other problems, and achieve the effect of improving efficiency, reducing the number of additions, and being easy to select.

Active Publication Date: 2020-12-04
FUZHOU UNIV
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Problems solved by technology

Studies have shown that most distribution switch failures are caused by mechanical failures. Usually, the main method of diagnosis for distribution switch mechanical failures is regular maintenance. Regular maintenance is not only time-consuming and laborious, but also repeated disassembly and maintenance may cause component fatigue. New faults are generated during maintenance
In addition, the diagnostic results of regular maintenance depend on the experience evaluation of maintenance personnel, which has a certain degree of subjectivity

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  • Feature extraction method for distribution switch mechanical faults based on ceemdan and weighted time-frequency entropy
  • Feature extraction method for distribution switch mechanical faults based on ceemdan and weighted time-frequency entropy
  • Feature extraction method for distribution switch mechanical faults based on ceemdan and weighted time-frequency entropy

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Embodiment Construction

[0045] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and through specific implementation methods.

[0046] Such as figure 1 As shown, a distribution switch mechanical fault feature extraction method based on CEEMDAN and weighted time-frequency entropy mainly includes the following contents:

[0047] To acquire vibration signals using acceleration or velocity signal data acquisition systems, it is necessary to set the sampling frequency (not less than 20kHz), waveform start threshold, and signal interception time parameters.

[0048] The vibration signal is decomposed using the CEEMDAN (Complete Empirical Mode Decomposition) method. Suppose the original signal is , set the noise standard deviation ratio, the upper limit of EMD iterations, and the number of auxiliary noise additions. After CEEMDAN decomposition, we can get:

[0049]

[0050] in, is the k-th order IMF (Intrinsic Mode Functio...

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Abstract

The invention relates to the technical field of power distribution networks, and specifically relates to a power distribution switch mechanical fault feature extraction method based on CEEMDAN and weighted time-frequency entropy. The method comprises the following steps of: step 1, acquiring a vibration signal through an acceleration or speed signal data acquisition system; step 2, decomposing thevibration signal through a CEEMDAN method to obtain IMF components of each order of the vibration signal; step 3, obtaining instantaneous frequencies respectively corresponding to each order of IMF components through Hilbert transformation; step 4, carrying out equal frequency band division on the IMF component through a band-pass filtering method in combination with the instantaneous frequency to construct a time-frequency matrix with a specified bandwidth; and step 5, performing equal interval division on the time-frequency matrix in the time domain direction to obtain a block time-frequency matrix, and solving the energy value of each block time-frequency matrix to construct a block energy matrix. According to the method, in view of the complexity difference of time sequences of frequency bands, the normalized sample entropy of the frequency bands is taken as the weight, and the weighted time-frequency entropy is extracted from the normalized energy matrix in the time domain direction and the frequency domain direction respectively to enhance the characterization capability of the characteristics.

Description

technical field [0001] The invention relates to the technical field of distribution networks, in particular to a method for extracting mechanical fault features of distribution switches based on CEEMDAN and weighted time-frequency entropy. Background technique [0002] The distribution switch is an important switching device in the power system, which has the dual functions of controlling and protecting the power grid. Studies have shown that most distribution switch failures are caused by mechanical failures. Usually, the main method of diagnosis for distribution switch mechanical failures is regular maintenance. Regular maintenance is not only time-consuming and laborious, but also repeated disassembly and maintenance may cause component fatigue. New faults are generated during maintenance. In addition, the diagnostic results of regular maintenance depend on the experience and evaluation of maintenance personnel, which has a certain degree of subjectivity. In view of the...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G01M13/00
Inventor 杨耿杰乔苏朋郭谋发高伟翁秉钧
Owner FUZHOU UNIV
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