Fault diagnosis of diesel engine valve clearance under variable operating condition based on soft interval SVM |
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Authors: | Jiang Zhinong Lai Yuehua Mao Zhiwei Zhang Jinjie Lai Zehua |
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Institution: | Key Laboratory of Engine Health Monitoring-Control and Networking of Ministry of Education,Beijing University of Chemical Technology,Beijing 100029,P.R.China;Beijing Key Laboratory of High-End Mechanical Equipment Health Monitoring and Self-Recovery,Beijing University of Chemical Technology,Beijing 100029,P.R.China;China Nuclear Control Systems Engineering Co.Ltd,Beijing 102401,P.R.China |
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Abstract: | The fault detection and diagnosis of diesel engine valve clearance can effectively improve the availability and safety of diesel engine and have extremely important value and significance.Diesel engines generally operate in various stable operating conditions,which have important influence on the fault diagnosis.However,many fault diagnosis methods have been put forward under specific stable operating condition based on vibration signal.As the result of great impact caused by operating conditions,corresponding diagnosis models cannot deal with the fault diagnosis under different operating conditions with required accuracy.In this paper,a fault diagnosis of diesel engine valve clearance under variable operating condition based on soft interval support vector machine(SVM) is proposed.Firstly,the fault features with weak condition sensitivity have been extracted according to the influence analysis of fault on vibration signal.Moreover,soft interval constraint has been applied to SVM algorithm to reduce the random influence of vibration signal on fault features.In addition,different machine learning algorithms based on different feature sets are adopted to conduct the fault diagnosis under different operating conditions for comparison.Experimental results show that the proposed method is applicable for fault diagnosis under variable operating condition with good accuracy. |
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