Fault detection and diagnosis of a gearbox in mari

Authors: Zhixiong Li Xinping Yan Chengqing Yuan Jiangbin Zhao Zhongxiao Peng

Publish Date: 2011/04/02

Volume: 10, Issue: 1, Pages: 17-24

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Abstract

A marine propulsion system is a very complicated system composed of many mechanical components As a result the vibration signal of a gearbox in the system is strongly coupled with the vibration signatures of other components including a diesel engine and main shaft It is therefore imperative to assess the coupling effect on diagnostic reliability in the process of gear fault diagnosis For this reason a fault detection and diagnosis method based on bispectrum analysis and artificial neural networks ANNs was proposed for the gearbox with consideration given to the impact of the other components in marine propulsion systems To monitor the gear conditions the bispectrum analysis was first employed to detect gear faults The amplitudefrequency plots containing gear characteristic signals were then attained based on the bispectrum technique which could be regarded as an index actualizing forepart gear faults diagnosis Both the back propagation neural network BPNN and the radialbasis function neural network RBFNN were applied to identify the states of the gearbox The numeric and experimental test results show the bispectral patterns of varying gear fault severities are different so that distinct fault features of the vibrant signal of a marine gearbox can be extracted effectively using the bispectrum and the ANN classification method has achieved high detection accuracy Hence the proposed diagnostic techniques have the capability of diagnosing marine gear faults in the earlier phases and thus have application importanceFoundation item Supported by the National Natural Sciences Foundation of China No 50975213 and No 50705070 Doctoral Fund for the New Teachers of Ministry of Education of China No 20070497029 and the Program of Introducing Talents of Discipline to Universities No B08031Zhixiong Li was born in 1983 He is a PhD candidate for vehicle application engineering at the School of Energy and Power Engineering of Wuhan University of Technology China His current research interests include condition monitoring and intelligent control systemXinping Yan was born in 1959 He is currently a professor at the School of Energy and Power Engineering Wuhan University of Technology China He received his PhD from Xi’an Jiaotong University China in 1997 His research interests include condition monitoring fault diagnosis and application research of tribologyChengqing Yuan was born in 1976 He is currently a professor at the School of Energy and Power Engineering Wuhan University of Technology China He received his PhD from Wuhan University of Technology China in 2005 His research interests include tribology condition monitoring and marine new energyJiangbin Zhao was born in 1976 He is currently a faculty member of Wuhan University of Technology He received PhD in mechanical engineering from Huazhong University of Science and Technology China in 2007 His research interests include automatic test and measurement system condition monitoring and intelligent maintenance systemZhongxiao Peng was born in 1968 She is currently an associate professor in mechanical engineering at James Cook University Australia She received PhD in mechanical engineering from the University of Western Australia Australia in 2000 Her research interests include tribology machine condition monitoring and fault diagnosis using wear debris and vibration analysis techniques and wear analysis of bioengineering systems

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