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Valve Train Dynamic Design and Verification
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作者 CAO Xu YIN Jiandong +1 位作者 LIU Shengqiang YAO Junwei 《International Journal of Plant Engineering and Management》 2022年第4期232-243,共12页
Valve train dynamic behaviors need to be considered at the beginning of the engine mechanical design,especially during choosing valve spring parameters.From parameter definition to simulation,the valve train parameter... Valve train dynamic behaviors need to be considered at the beginning of the engine mechanical design,especially during choosing valve spring parameters.From parameter definition to simulation,the valve train parameters around dynamic performance are determined step by step.The valve train dynamic test is done finally to verify the design result since it is a such important facet for valve train design.And reliability from mass production and product life view must be considered during whole design process too. 展开更多
关键词 valve train dynamic simulation dynamic verification
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Diesel Engine Valve Clearance Fault Diagnosis Based on Features Extraction Techniques and FastICA-SVM 被引量:9
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作者 Ya-Bing Jing Chang-Wen Liu +3 位作者 Feng-Rong Bi Xiao-Yang Bi Xia Wang Kang Shao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第4期991-1007,共17页
Numerous vibration-based techniques are rarely used in diesel engines fault diagnosis in a direct way, due to the surface vibration signals of diesel engines with the complex non-stationary and nonlinear time-varying ... Numerous vibration-based techniques are rarely used in diesel engines fault diagnosis in a direct way, due to the surface vibration signals of diesel engines with the complex non-stationary and nonlinear time-varying fea- tures. To investigate the fault diagnosis of diesel engines, fractal correlation dimension, wavelet energy and entropy as features reflecting the diesel engine fault fractal and energy characteristics are extracted from the decomposed signals through analyzing vibration acceleration signals derived from the cylinder head in seven different states of valve train. An intelligent fault detector FastICA-SVM is applied for diesel engine fault diagnosis and classification. The results demonstrate that FastlCA-SVM achieves higher classification accuracy and makes better general- ization performance in small samples recognition. Besides, the fractal correlation dimension and wavelet energy and entropy as the special features of diesel engine vibration signal are considered as input vectors of classifier FastlCA- SVM and could produce the excellent classification results. The proposed methodology improves the accuracy of fea- ture extraction and the fault diagnosis of diesel engines. 展开更多
关键词 Feature extraction Diesel engine valve train FastlCA PCA Support vector machine
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