The Elevator Fault Diagnosis Method Based on Sequential Probability Ratio Test (SPRT)
Automation, Control and Intelligent Systems
Volume 5, Issue 4, August 2017, Pages: 50-55
Received: Jun. 12, 2017; Accepted: Jun. 26, 2017; Published: Jul. 26, 2017
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Authors
Chang Liu, Department of Electrical and Information Engineering, Jinan University, Zhuhai, China
Shu Zhou, Department of Electrical and Information Engineering, Jinan University, Zhuhai, China
Xindong Liu, Department of Electrical and Information Engineering, Jinan University, Zhuhai, China
Can Chen, Guangdong Power Grid Company, Zhuhai Power Supply Bureau, Zhuhai, China
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Abstract
An elevator fault diagnosis method based on Sequential Probability Ratio Test (SPRT) is proposed in this paper. In order to verify the effectiveness of the method, this paper designed the fault diagnosis experiment for elevator mechanical system. Firstly, the wavelet transformation is used to filter the noise of the vibration signal collected in the experiment. Then the kurtosis value of the filtered signal is extracted as the index to represent the practical status of the elevator. Finally, the SPRT algorithm is used to diagnose the faults of the elevator mechanical system. Experimental results show that this method has high accuracy in practical applications. It is important to improve the performance of the fault diagnosis for the elevator mechanical system.
Keywords
Sequential Probability Ratio Test, Fault Diagnosis, Wavelet Transformation, Kurtosis
To cite this article
Chang Liu, Shu Zhou, Xindong Liu, Can Chen, The Elevator Fault Diagnosis Method Based on Sequential Probability Ratio Test (SPRT), Automation, Control and Intelligent Systems. Vol. 5, No. 4, 2017, pp. 50-55. doi: 10.11648/j.acis.20170504.11
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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