Gear Fault Detection Utilizing Adaptive Multi-scale Morphological Gradient Transform

摘要：

Vibration signals which carry the dynamic information of the machines are frequently used for mechanical fault diagnosis. Impulsive modulated signals often generated by the defected gear and how to extract the impulsive components from the raw vibration signal with strong background noise has become the most important tasks for gear fault diagnosis. An adaptive multi-scale morphological gradient (AMMG) filter, which can depress the noise at large scale and preserve the impulsive details at small scale, was presented in this work for extracting the impulsive characteristics from the vibration signals generated by defected gear. Both simulated and gear fault vibration signals were employed to evaluate the performance of the proposed technique. Results revealed that the AMMG method has demonstrated a more effective tool for feature extraction of gear compared with the traditional envelope analysis and the morphological close approach.

关键词： vibration signals gear fault diagnosis mathematical morphology adaptive multi-scale morphological gradient (AMMG)

作者: Bing Li Peilin Zhang Shuangshan Mi Dongsheng Liu Guoquan Ren

作者单位: First Department,Mechanical Engineering College He Ping Xi Lu 97#,050003,Shi Jia-zhuang,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 4173-4176

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）