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Gear Intelligent Fault Diagnosis Based on Support Vector Machines

Lv Peng ; Liu Yibing ; Ma Qiang ; Wei Yufan

2007 Chinese Control Conference, 2007, p.496-500

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Título:
Gear Intelligent Fault Diagnosis Based on Support Vector Machines
Autor: Lv Peng ; Liu Yibing ; Ma Qiang ; Wei Yufan
Assuntos: Band pass filters ; Fault diagnosis ; fault intelligent diagnosis ; Feature extraction ; Frequency domain analysis ; gear ; Gears ; Machine intelligence ; Mathematics ; Physics ; Support vector machine classification ; Support vector machines ; SVM
É parte de: 2007 Chinese Control Conference, 2007, p.496-500
Descrição: Support vector machines (SVM) was used in fault intelligent diagnosis of gear. The main research in feature extraction and data preprocess. The feature value of time domain includes peak to peak value, absolute average, square root amplitude, mean square amplitude. The feature value of frequency domain is MSF. The SVM method was used for detecting the gear case. The feature of time and the feature of frequent was be used. Through designed a band-pass filter, the feature of gear case's signal was extracted, including feature of time and feature of frequent. The results showed that the reference and fault stations of fan can be distinguished clearly in the SVM diagram. The results showed that it was better than that signals which didn't use filter.
Editor: IEEE
Idioma: Inglês

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