Mechanical Vibration Fault Monitoring Method of Intelligent Doubly-fed Fan Based on Multi-source Sensing
Aiming at the problems of low signal-to-noise ratio,poor fault monitoring classification and long time in the mechanical vibration fault monitoring of doubly fed fans,a method for monitoring the mechanical vibration fault of the intelligent DFIG based on multi-source sensing is proposed.Firstly,in-formation entropy is used to measure the change of the vibration signal of the intelligent doubly-fed fan,the information entropy characteristics of the signal in the time-frequency domain are obtained,and the information characteristics of multi-source sensor signals are fused;then a global search factor is intro-duced to improve the artificial bee colony method,and the support vector machine is optimized by the im-proved artificial bee colony method;finally,the extracted and fused vibration signal features are input into the trained support vector machine to complete the mechanical vibration fault monitoring of the intelligent doubly-fed fan.The experimental results show that the proposed method has good denoising effect and fault monitoring classification effect,and the monitoring time is short.
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