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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yanping Cai Shu Cheng Yanping He Ping Xu |
| Copyright Year | 2008 |
| Description | Author affiliation: Xi'an High-Tech Inst., Xi'an (Yanping Cai; Yanping He; Ping Xu) || No. 2 Heavy Machine Co. Ltd., Beijing (Shu Cheng) |
| Abstract | A new method of diesel engine fault diagnosis that uses image recognition technology based on fractal dimension is proposed. The Wigner-Ville distributions of six kinds of vibration acceleration signals which are acquired from diesel engine cylinder head are calculated by time-frequency analysis, and a series of time-frequency gray images can be obtained from above distributions by image processing. According to the theory of fractal, we can obtain a group of fractal texture characteristic parameters from these gray images. At the same time, in the process of pattern recognition, we adopt BP neural network to classify these image texture fractal characteristic parameters, and then we can identify diesel engine valve gap abnormal status. Experiment results show that the proposed method can distinguish different texture characteristic of time-frequency gray images which are generated from different valve gap status of diesel engine, and this method is worth for further study. |
| Starting Page | 2948 |
| Ending Page | 2953 |
| File Size | 518522 |
| Page Count | 6 |
| File Format | |
| ISBN | 9780769533988 |
| DOI | 10.1109/ICYCS.2008.265 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-11-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | image processing Image recognition Head fault diagnosis fractal dimension Time frequency analysis Valves Diesel engine Fractals neural network Fault diagnosis Diesel engines Signal processing Acceleration Engine cylinders |
| Content Type | Text |
| Resource Type | Article |
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