Fault Detection and Diagnosis of a Gearbox in Marine Propulsion Systems Using Bispectrum Analysis and Artificial Neural Networks  

船舶动力系统中齿轮箱故障特征提取与模式识别方法研究(英文)

作　　者：李志雄 严新平 袁成清 赵江滨 彭中笑 

机构地区：[1]Reliability Engineering Institute,School of Energy and Power Engineering,Wuhan University of Technology [2]Key Lab.of Marine Power Eng.and Tech.(Ministry of Transport),Wuhan University of Technology [3]School of Engineering and Physical Sciences,James Cook University

出　　处：《Journal of Marine Science and Application》2011年第1期17-24,共8页船舶与海洋工程学报（英文版）

基　　金：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);the Program of Introducing Talents of Discipline to Universities (No. B08031)

摘　　要：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 amplitude-frequency 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 radial-basis 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 importance.

关 键 词：marine propulsion system fault diagnosis vibration analysis BISPECTRUM artificial neural networks Article 

分 类 号：U672.2[交通运输工程—船舶及航道工程]