DocumentCode :
3773613
Title :
Study on Fault Prediction of Vehicles Synchronous Generator
Author :
Yanwei Cheng;Cheng Yao;Di Wang;Xianggang Meng
Author_Institution :
Dept. Control, Acad. of Changchun Eng. Tech., Changchun, China
Volume :
2
fYear :
2015
Firstpage :
201
Lastpage :
203
Abstract :
Arming at the complex electromagneter relationship of synchronous generator, it can work with wrong. Using wavelet packet transform to reduce voice, extracting the unsteady feature of the output voltage. According to LSSVM can make nonlinear prediction and HMM has the explanative ability, the fault prediction model based on LSSVM+HMM is presented., training the HMM by the normal features. Then the fault likelihood of unknown signal feature and the predicted feature calculated by LSSVM can be getted by the trained HMM. Decided the state of generator by comparing the values. Effectiveness of the model was verified from the real example.
Keywords :
"Hidden Markov models","Generators","Wavelet packets","Feature extraction","Probability","Vehicles"
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2015 8th International Symposium on
Print_ISBN :
978-1-4673-9586-1
Type :
conf
DOI :
10.1109/ISCID.2015.266
Filename :
7469114
Link To Document :
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