An intelligent fault diagnosis system for newly assembled transmission |
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| Affiliation: | 1. Industry Control Network and Systems Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;2. College of Electronical Engineering, Xinjiang University, Xinjiang 830021, China;1. Department of Business and Entrepreneurial Management, Kainan University, 1, Kainan Road, Luchu Shiang, Taoyuan 33857, Taiwan;2. Graduate Institute of Management Science, National Chiao Tung University, 1001, Ta-Hsueh Road, Hsinchu 300, Taiwan;3. Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151, University Road, San Shia 237, Taiwan;1. School of Telecommunication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an, PR China;2. School of Computer Science, Shaanxi Normal University, Xi’an, PR China;1. Graduate Program in Computer Science, PPGI, UFES Federal University of Espirito Santo, Av. Fernando Ferrari, 514, CEP 29075-910 Vitória, Espírito Santo, ES, Brazil;2. Department of Production Engineering & Graduate Program in Computer Science, PPGI, UFES Federal University of Espirito Santo, Av. Fernando Ferrari, 514, CEP 29075-910 Vitória, Espírito Santo, ES, Brazil;1. School of Management Science and Engineering, Dongbei University of Finance & Economics, Jianshan Street 217, Dalian 116025, PR China;2. Graduate School of Management, Clark University, 950 Main Street, Worcester, MA 01610-1477, USA;3. School of Business, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609-2280, USA |
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| Abstract: | Newly assembled automobile transmission has its particular failure characteristic, strict quality testing working procedure on the assembly line is important for quality of automobile transmission. In this paper, we introduce a new automatic fault detection method for automobile transmission. A fault diagnosis expert system for newly assembled transmission is presented, related method of knowledge representation, feature extraction and fault classification is given. Order spectrum analysis method is used to analyze vibratory signal of automobile transmission. After initial feature vectors set are obtained, improved genetic search strategy is used to select fault features, so as to reduce the dimension of feature vector set. Selected feature vector sets are inputted into the BP neural network for fault identification and classification of the newly assembled automobile transmission. A large number of data are collected from industrial site and analyzed, proposed algorithm is verified to be effective and exact. |
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| Keywords: | Vibratory signal Feature extraction Fault classification Order spectrum analysis Genetic search algorithm BP neural network |
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