Fault Diagnosis for Rolling Element Bearing Using EMD-DFDA

摘要：

　　A new fault diagnosis method for rolling element bearing is proposed based on empirical mode decomposition(EMD)and fisher discriminant analysis(FDA).First,non-stationary vibration signals are processed by applying EMD technique,and stationary IMF components are obtained.Then,fault feature vectors with the moving time-lagged windows are composed using the absolute values of IMF components of healthy and detection bearings in order to consider the dynamic behavior.Finally,a DFDA model is construed and a linear discriminant matrix is obtained by which IMF components are projected into the low discriminant space.The diagnosis performance of the proposed method is tested using a dataset from bearing data center of Case Western Reserve University.

关键词： Vibration Signals EMD Rolling Element Bearing DFDA Fault Diagnosis

作者: Liying Jiang Yanpeng Zhang Guangting Gong Zhipeng Liu Jianguo Cui

作者单位: School of Automation,Shenyang Aerospace University,Shenyang 110136,China

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 3212-3216

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）