Research on an Identification Method of Post Porcelain Insulator Damage Based on Variational Modal Algorithm

Abstract

In view of the difficulty in signal identification in vibration acoustic detection of post porcelain insulators， A BP （backpropagation） neural network identification method based on variational mode decomposition （VMD） is proposed to identify the damage of post porcelain insulators. First， the acoustic vibration test system is built and the acoustic vibration signals of intact and defective porcelain insulators are collected； then， the decomposition and reconstruction are carried out using the variational modal method to eliminate the noise and redundant components of the signals； finally， the original signals and the reconstructed acoustic signals after the variational modal decomposition are reinput into the BP neural network for damage identification， and the recognition rate of the reconstructed signals after the variational modal decomposition is found significantly improved. The proposed method， as shown by the analysis， can automatically extract and identify acoustic signals， is highly accurate and less susceptible to noise interference. The research will provide a feasible technical solution to the damage identification of post porcelain insulators.

Keywords

• porcelain insulators
• damage identification
• variational mode decomposition
• bp neural network