Opening-closing fault diagnosis method for air circuit breaker based on vibration signals

Abstract

The invention provides an opening-closing fault diagnosis method for an air circuit breaker based on vibration signals, wherein an acceleration sensor is used to collect machine body vibration signals generated during opening-closing courses of the air circuit breaker. The method comprises the steps that firstly, the acceleration sensor is used to collect the machine body vibration signals generated during opening-closing actions of the air circuit breaker and transform the vibration signals into digital signals, so that initial vibration signals are obtained; secondly, an improved wavelet packet threshold de-noising algorithm is used to process the collected vibration signals; thirdly, a complementary ensemble-average empirical mode decomposition algorithm is used to extract intrinsic mode function components from the de-noising vibration signals; fourthly, the quantity Z of the intrinsic mode function components is determined; fifthly, the intrinsic mode function components of the first Z orders are selected and extracted as sample entropies of a characteristic quantity; sixthly, binary tree multi-classifiers based on a relevance vector machine are established; and seventhly, the binary tree multi-classifiers based on the relevance vector machine obtained at the sixth step are used to establish a fault recognition model of the air circuit breaker.

Description

technical field [0001] The technical solution of the invention relates to the fault diagnosis of circuit breakers, in particular to a method for diagnosing the opening and closing faults of universal circuit breakers based on vibration signals. Background technique [0002] According to the country's plan for smart grid construction, smart substations are an important part and key link of smart grids. Intelligent universal circuit breakers are an important part of smart substations, so it is necessary to ensure their reliable operation. However, at this stage, scholars at home and abroad have mostly studied the fault diagnosis of circuit breakers on high-voltage circuit breakers, while there are few studies on low-voltage circuit breakers, especially universal circuit breakers. At present, the fault diagnosis technology for circuit breakers generally includes three links: signal acquisition, feature extraction, and fault identification. [0003] The signals collected in the...

AI Technical Summary

Problems solved by technology

[0004] In the feature extraction process of the second link, in view of the nonlinear and non-stationary characteristics of vibration signals, wavelet analysis, empirical mode decomposition (empirical modedecomposition, EMD), and overall Average empirical mode decomposition (ensemble EMD, EEMD), Hilbert-Huang transform (Hilbert-Huang transform, HHT), etc., but wavelet has its own defects in fault signal decomposition, and its decomposition effect depends on wavelet base and decomposition scale The selection of is not self-adaptive. In addition, there is energy leakage in wavelet decomposition

However, the matching effect with the existing feature extraction method is poor, and the fault recognition rate cannot be effectively improved. Therefore, on the basis of the existing fault recognition method, by improving the feature extraction link and the fault recognition method, it will produce a better fault after matching. Effect, to achieve a higher recognition rate of faults, and on this basis, to provide an improved vibration signal-based universal circuit breaker opening and closing fault diagnosis method has become an urgent problem to be solved in the existing technology

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