Acta Metrologica Sinica  2016, Vol. 37 Issue (5): 515-519    DOI: 10.3969/j.issn.1000-1158.2016.05.13
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Elevator Fault Stop Diagnosis Based on Wavelet Packet Energy Spectrum and Evidences Fusion Reasoning
ZHANG Bin,SHEN Guo-yang,JIN Ying-lian,WANG Bin-rui
College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China
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Abstract  The feature vector will be got by using the kurtosis coefficient of time domain signal and the entropy spectral of the frequency domain signal after wavelet packet transformation, and this is defined as DS evidence. The eigenvalues interval through sample statistics will be obtained. The similarity based on the eigenvalues and the length between the intervals of the test sample was designed, and the basic probability assignment function by normalization will be obtained. Then the DS combination rule by spatio-temporal combination of the evidence was got. And the DS diagnosis results by using reliability allocation function can be obtained. Finally, the experiments will be carried out and diagnosis results by using sym8 for three-layer wavelet packet transformation and 9 evidences are received. The experimental results show that the diagnostic accuracy of this method about elevator fault stop is more than 98%.
Key wordsmetrology      elevator fault diagnosis      Dempster-Shafer evidence reasoning      feature extraction     
Received: 23 June 2015      Published: 29 July 2016
PACS:  TB93  
Corresponding Authors: WANG BinRui     E-mail: wangbinrui@cjlu.edu.cn
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ZHANG Bin
SHEN Guo-yang
JIN Ying-lian
WANG Bin-rui
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ZHANG Bin,SHEN Guo-yang,JIN Ying-lian, et al. Elevator Fault Stop Diagnosis Based on Wavelet Packet Energy Spectrum and Evidences Fusion Reasoning[J]. Acta Metrologica Sinica, 2016, 37(5): 515-519.
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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2016.05.13     OR     http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2016/V37/I5/515
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