Research on circuit breaker operating mechanism feature extraction method combining ICEEMDAN-MRSVD denoising and VMD-PSE

Abstract

Abstract The vibration signal associated with the operating process of circuit breakers(CBs) includes a detailed operating status in the formation of the operating mechanism. To effectively extract the characteristic information of vibration effectively for diagnosis and analysis, a new feature extraction method for the CBs operating mechanism is proposed. First, a new denoising method, the improved complete ensemble empirical mode decomposition with adaptive noise-multi-resolution singular value decomposition (ICEEMDAN-MRSVD), is introduced, which can effectively remove the influence of noise on faults. Then, a quantitative method is proposed to extract the characteristic information of the CB, i.e. the variational mode decomposition (VMD)-power spectrum entropy (PSE) is proposed. By using this method, the difference of CB vibration signals in different fault states can be quantified. Through comparative analysis of different recognition models, experiments show that the support vector machine model based on ICEEMDAN-MRSVD noise reduction and VMD-PSE features has a high recognition accuracy of 98.61%, which has high application value.