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Status Accepted
journal_subject Part A
Article Type Regular Paper (More than 4 pages)
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Article Title Structural Fault Detection on Bearing Operating in Early Stage
Keywords Intelligent diagnosis, support vector machine, optimal composition of symptom parameter, early-stage
Abstract This study presents a new intelligent diagnosis method for identifying early-stage structural faults of rotating machinery. The method is constructed on the basis of optimal composition of symptom parameters (SPOC) and support vector machines (SVMs). SPOC, as the objects of a follow-on process, is proposed to obtain from symptom parameters (SPs) of multi-direction. Moreover, the optimal hyper-plane of two states is automatically obtained using a SVM and SPOC, and then using multi-SVMs, the system of intelligent diagnosis is built to detect many faults and identify fault types from rotating machinery in early stage. The proposed method has been applied to detect structural faults from rotating machinery in early stage, and the efficiency of the method has been verified using practical examples.
First Name Middle Name Last Name E-Mail Corresponding
Xue Hongtao Yes
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