Porcelain post insulator fault identification method and device

Abstract

The embodiment of the invention provides a porcelain post insulator fault identification method and device. According to the method, vibration data of porcelain post insulator vibration acoustic detection equipment is used as a data source; the method includes: firstly, converting collected time domain data into a frequency domain; then, constructing a Gaussian mixture model for the processed signal by utilizing an expectation maximum algorithm, and solving important parameters of the Gaussian mixture model by utilizing the expectation maximum algorithm, namely an average value mu, a standarddeviation sigma and a weight coefficient alpha, wherein the average value mu can reflect the central frequency position of each modal component, the standard deviation sigma can reflect the frequencybandwidth, and the weight coefficient alpha can be used for representing the proportion occupied by each modal component; and finally, importing the obtained important parameters as characteristic data into an ELM for training, judging the fault characteristics of the porcelain post insulator through machine learning, and compared with the traditional spectral analysis, the porcelain post insulator fault identification method based on the Gaussian mixture model and the expectation maximum algorithm improves the fault identification efficiency.

Description

technical field [0001] The present application relates to the field of electric power technology, in particular to a fault identification method and device for porcelain post insulators. Background technique [0002] Porcelain post insulators have many fracture accidents due to their harsh working environment, quality deterioration and natural aging, which seriously affect the safe operation of power systems. Therefore, it is of great application value to study insulator in-service detection. [0003] The vibration signal collected by the porcelain post insulator belongs to the random vibration signal, the frequency spectrum of the vibration signal is complex, and there are many interferences. Traditional spectrum analysis methods require multiple comparative analyzes to remove interference and obtain detection results. [0004] A fault identification method for porcelain post insulators based on the Gaussian mixture model and the expected maximum algorithm is helpful for b...

AI Technical Summary

Problems solved by technology

[0002] Due to the harsh working environment, quality deterioration and natural aging of porcelain post insulators, there are many fracture accidents, which seriously affect the safe operation of the power system. Therefore, it is of great application value to study insulator in-service detection.

[0003] The vibration signal collected by the porcelain post insulator is a random vibration signal, the frequency spectrum of the vibration signal is complex, and there are many interferences

Traditional spectrum analysis methods require multiple comparative analyzes to remove interference and obtain detection results

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