Diesel Engine Valve Clearance Fault Diagnosis Based on Features Extraction Techniques and FastICA-SVM

Author:

Jing Ya-Bing,Liu Chang-Wen,Bi Feng-Rong,Bi Xiao-Yang,Wang Xia,Shao Kang

Funder

National Science and Technology Support Program of China

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Reference48 articles.

1. Y Xia, Z R Zhang, B L Shang, et al. Fault diagnosis for ICE based on image processing and neural networks. Transactions of CSICE (Chinese Society for Internal Combustion Engines), 2001, 19(4): 356–360. (in Chinese).

2. Z Li, X C Cheng, Z B Liu. Study of diagnosis methods for diesel’s valve train faults based on picture processing and neural networks. Transactions of CSICE (Chinese Society for Internal Combustion Engines), 2001, 19(3): 241–244. (in Chinese).

3. H B Zheng, Z Y Li, X Z Chen, et al. Engine knock signature analysis and fault diagnosis based on time–frequency distribution. Transactions of CSICE (Chinese Society for Internal Combustion Engines), 2002, 20(3): 267–272. (in Chinese).

4. Z M Geng, J Chen, J B Hull. Analysis of engine vibration and design of an applicable diagnosing approach. International Journal of Mechanical Sciences, 2003, 45(8): 1391–1410.

5. Z Geng, J Chen. Investigation into piston-slap-induced vibration for engine condition simulation and monitoring. Journal of Sound and Vibration, 2005, 282(3–5): 735–751.

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