Fault diagnosis method for AC/DC charging equipment power device based on wavelet packet analysis

Abstract

The invention discloses a fault diagnosis method for an AC/DC charging equipment power device based on wavelet packet analysis, and the method comprises the steps: analyzing a charging equipment powermodule, and determining a fault class; obtaining output signals of the charging equipment power module under the normal condition and various fault conditions; carrying out the high-low frequency decomposition of the output signals, carrying out the multilayer wavelet packet decomposition of the high-low frequency signals obtained through decomposition, and carrying out the reconstruction of a wavelet packet decomposition coefficient; calculating the extracted signal energy at all frequency bands, carrying out the normalized calculation of the signal energy, and finally determining a centralized frequency band range of the signal energy; carrying out the power spectrum analysis of the reconstructed wavelet packet decomposition coefficient, determining the feature frequency and power spectrum value of a frequency band signal, comparing the comparison with the fault analysis, and determining the type of a fault; and carrying out the fault type coding of the type of the fault. The methodimproves the time-frequency resolution of a signal, achieves the precise fault positioning through the spectrum features, and improves the precision of the fault diagnosis of the AC/DC charging equipment power device.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis of charging equipment, in particular to a fault diagnosis method for power devices of AC and DC charging equipment based on wavelet packet analysis. Background technique [0002] In recent years, with the vigorous development of the electric vehicle industry, electric vehicle charging equipment has become a very hot research field. In AC and DC charging equipment, power devices are most prone to failures such as overvoltage, overcurrent, power tube short circuit and open circuit, etc., which seriously affect the safe and stable operation of electric vehicle charging. Therefore, it is of great significance to study the fault diagnosis of power devices of AC and DC charging equipment, and the fault diagnosis of charging equipment has also become an important research direction. [0003] The charging process of AC and DC charging equipment has three links: PWM rectification, filtering, and h...

AI Technical Summary

Problems solved by technology

Signal processing methods generally include Fourier transform, wavelet analysis, etc. Fourier transform is a global transformation with certain limitations and cannot describe information in the time domain and frequency domain at the same time, while wavelet analysis has multi-resolution The characteristics of frequency analysis, and the ability to characterize the local characteristics of the signal in both time and frequency domains. Although wavelet analysis can achieve rapid diagnosis, different wavelet functions must be selected for different types of faults to achieve ideal diagnostic results, which is not suitable for application. In systems that require high timeliness and accuracy

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