Residential College | false |
Status | 已發表Published |
A fusion approach for rotating machinery fault diagnosis using double sample K-S inspection and modified d-s algorithm | |
Jianbin Xiong1; Wenhao Liu1; Qi Wang1; Qiong Liang1; Long Chen2; Junwei Duan3 | |
2020-10 | |
Conference Name | 35th Youth Academic Annual Conference of Chinese-Association-of-Automation (YAC) |
Source Publication | Proceedings - 2020 35th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2020 |
Pages | 744-750 |
Conference Date | 16-18 October 2020 |
Conference Place | Zhanjiang, China |
Country | China |
Publisher | IEEE |
Abstract | In order to solve the problem that it is difficult to determine the basic probability distribution value in the evidence fusion of petrochemical rotary unit fault signals, this paper proposes a dimensionless index-based hybrid approach using the two-sample Kolmogorov-Smirnov (K-S) test. This method decreases the effect of the interference from the fault characteristic sensitivity and operating conditions through the dimensionless index's calculation. It can also find out the evidence needed for fusion basic probability assignment values by the two sample K-S test. Finally, it conducts evidence fusion using a modified D-S algorithm. The advantage of the proposed method that makes it superior to other methods is that it can deal with fuzzy, incomplete or accurate data. Therefore, the input signals of petrochemical rotary machinery equipment and sensor equipment can be processed directly. In this paper, experimental results prove the effectiveness of the proposed method, so the decision risk can be reduced. |
Keyword | Dimensionless Parameters Evidence Fusion Fault Diagnosis Kolmogorov-smirnov Rotary Machine |
DOI | 10.1109/YAC51587.2020.9337668 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Automation & Control Systems |
WOS Subject | Automation & Control Systems |
WOS ID | WOS:000659281900133 |
Scopus ID | 2-s2.0-85101080434 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | Faculty of Science and Technology DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Affiliation | 1.Guangdong Polytechnic Normal University, Guangzhou, China 2.Department of Computer and Information Science University of Macau, Taipa, Macau, China 3.Intelligent Science and Technology, College of Information Science and Technology, Jinan University, Guangzhou, China |
Recommended Citation GB/T 7714 | Jianbin Xiong,Wenhao Liu,Qi Wang,et al. A fusion approach for rotating machinery fault diagnosis using double sample K-S inspection and modified d-s algorithm[C]:IEEE, 2020, 744-750. |
APA | Jianbin Xiong., Wenhao Liu., Qi Wang., Qiong Liang., Long Chen., & Junwei Duan (2020). A fusion approach for rotating machinery fault diagnosis using double sample K-S inspection and modified d-s algorithm. Proceedings - 2020 35th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2020, 744-750. |
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