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《Journal of Transcluction Technology》 2005-02
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Application of Support Vector Machine Based on Information Spectrum Entropy in Machine State Identification

PAN Ming-qing,ZHOU Xiao-jun,YANG Chen-long,PANG Mao( Institute of Modern Manufacture Engineering, Zhejiang University, Hangzhou 310027, China)  
Feature extraction is important to machine state identification. Two-dimension spectrum entropy is extracted as the character index of machine state by analyzing the frequency spectrum of vibration signals. With the application of bearing's condition measurement, normal and fault condition is distinguished directly. Then, inputting the two-dimension spectrum entropy into the SVM classification, the result shows that SVM has fine compute efficiency and classified ability. This combined model can be used in the field of on-line condition measurement.
【CateGory Index】: TH113.1;
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