The vibration of high voltage circuit breakers is superimposed by the impact vibration generated by the action of its components. When the operating states of the components change, the vibration waveform will be dist...
详细信息
The vibration of high voltage circuit breakers is superimposed by the impact vibration generated by the action of its components. When the operating states of the components change, the vibration waveform will be distorted. To extract the state information contained in the vibration signals, in this paper we propose a new method for the mechanical fault identification of circuit breakers based on the joint analysis of time-frequency domain features. Firstly, a new time-reference-distance algorithm (TRD) which employs feature space to grab information is proposed to get the time-domain features in detail. The feature space is constructed by the kurtosis, crest factor, and peak divergence degree of the time-domain waveform. Further, we propose another new algorithm, the shape entropy algorithm (SE), to extract the frequency-domain features. Through converting the power spectrum of the vibration signals to polar coordinates via the divergence factor, the SE features are then obtained by combining with the information entropy formula. Finally, the TRD and SE features are combined and input into the support vector machine (SVM) model for fault identification. The test results verify the efficiency of the methodology and the identification process takes less time. It has a practical application value.
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