A method for evaluating the mechanical failure degree of frame circuit breakers based on vibration signals

Abstract

The invention discloses a method for evaluating the degree of a mechanical fault of a frame-type circuit breaker based on a vibration signal. The vibration signal in the method is a mechanical vibration signal collected by a frame-type circuit breaker mechanical fault detection system in the switching process of the frame-type circuit breaker. The method comprises the steps: employing a wavelet packet to carry out the denoising preprocessing of the vibration signal; carrying out the adaptive decomposition of a denoised vibration signal through employing a local mean decomposition algorithm; screening out the former d PF components with the maximum correlation with an original vibration signal; carrying out the improved multiscale arrangement entropy analysis of al PF components, and carrying out the dimension reduction of a feature vector formed by the above improved multiscale arrangement entropy values through the PCA method; building a fault feature vector; constructing a multi-class supporting vector machine, and carrying out the pattern recognition; carrying out the quantitative evaluation of the severity of the mechanical fault happening in the switching process of the circuit breaker through referring to the fault degree characteristic curves in different fault modes. The method is stable, is reliable and is effective.

Description

technical field [0001] The invention relates to the technical field of evaluating the mechanical failure degree of a circuit breaker, in particular to a vibration signal-based method for evaluating the mechanical failure degree of a frame type circuit breaker. Background technique [0002] Smart grid is currently a research hotspot at home and abroad. Intelligent power supply system is an important part of smart grid. Power distribution system feeder lines at all levels, power control of various mechanical equipment and control and protection of power terminals. Research and statistical institutions at home and abroad have found that most of the faults of circuit breakers are mechanical faults, and opening and closing faults are the most common among mechanical faults. In recent years, fault diagnosis technology has been deeply studied and widely used, and many intelligent diagnosis methods have appeared in the existing circuit breaker mechanical fault diagnosis technology....

AI Technical Summary

Problems solved by technology

The current research on the fault degree only realizes the classification of the fault degree, that is, it can only diagnose the fixed fault degree according to the intelligent identification algorithm, which is a discrete correspondence, but it does not fundamentally reveal the relationship between the signal characteristics and the fault degree. Variation law, that is, the quantitative analysis of the fault degree based on the characteristic relationship between some fault degree characteristics and the severity of the fault is easy to produce wrong judgment of the fault degree, which will affect the judgment of the mechanical state of the circuit breaker in the slightest, and cause a power outage in severe cases Accidents and major economic losses

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