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《China Mechanical Engineering》 2016-24
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An Engine Fault Diagnosis Method Based on PCL and SVM

Zhang Yufei;Yao Ziyun;Tang Songlin;Zhu Lina;Zhang Jinjie;Beijing Key Laboratory of Health Monitoring Control and Fault Self-recovery for High-end Machinery,Beijing University of Chemical Technology;Petro China Yunnan Petrochemical Company Limited;  
A new method was proposed based on PCA and SVM.First of all,the fault characteristics of vibration signals in time domain and frequency features were extracted by wavelet packet decomposition.Then the sensitive characteristics were selected with PCA to achieve dimensionality reduction and to decrease the complexity of data processing.Finally,SVM was used for training and testing of the feature subsets,and realizing the fault separation.Appling this method to typical faults of diesel engine such as misfire,cylinder collision and small head tile wear,the diagnosis accuracy rate is up to 98%,which confirmed the validity of this method.
【Fund】: 国家重点基础研究发展计划(973计划)资助项目(2012CB026005);; 国家高技术研究发展计划(863计划)资助项目(2014AA041806);; 中央高校基本科研业务费专项资金资助项目(JD1506)
【CateGory Index】: TK428;TP181
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