Fault Detection of Rolling Bearing Based on EMD-DPCA

摘要：

　　As one of the most widely used parts and components of rotating machineries,fault detection of rolling bearing is of great significance.In this paper,a new method named EMD-DPCA is proposed based on Empirical Mode Decomposition(EMD)and Dynamic Principal Component Analysis(DPCA).Firstly,the vibration signals are decomposed by EMD and Intrinsic Mode Functions(IMFs)are achieved.Then DPCA model is established by many selected IMFs and used to detect rolling bearings failures.The proposed scheme is verified with experimental data collected from deep groove ball bearing of a 2 hp motor driven mechanical system and the results show that the strategies can detect bearing faults efficiently.

关键词： Rolling Bearing Vibration Signals EMD DPCA Fault Detection

作者: Liying Jiang Guangting Gong Yanpeng Zhang 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: 3207-3211

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）