期刊
IEEE SENSORS JOURNAL
卷 18, 期 11, 页码 4704-4714出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2018.2820170
关键词
The order statistics correlation coefficient (OSCC); Pearson's product moment correlation coefficient (PPMCC); fault diagnosis; correlation measure; correlation coefficient; dimensionless index
资金
- National Natural Science Foundation of China [61473331, 61471133, 61174113, 61272382]
- Science and Technology Plan of Guangdong Province of China [2017A070712024]
- Fundamental Research Funds for the Central Universities [x2jqD2170480]
- Sail Plan Training High-Level Talents of Guangdong Province of China
- Annual Scientific and Technological Innovation Special Fund [pdjh2016b0341]
- Guangdong University of Petrochemical Technology College Students' Innovation Incubation Project [2015pyA006]
- Science and Technology Project of Guangzhou [201604010099, 2016B030306002, 2016B030308001]
In this paper, the advantages of dimensionless indices and two types of correlation coefficients are combined and two methods are proposed to enhance the efficiency and accuracy of fault diagnosis in the petrochemical rotating machinery. The order statistic correlation coefficient and Pearson's correlation coefficient are used to calculate the correlation coefficients of dimensionless indices, which are given by dimensionless algorithms after preprocessing the raw data. Different fault types are recognized by comparing the correlation coefficient and each dimensionless indicator. The numerical results revealed that the proposed method has the highest accuracy of 80% while the average of 50%, and an overall accuracy improvement of 10.89% compared with the conventional method. The results clearly indicate that the accuracy of the proposed fault diagnosis method is superior compared with its counterpart.
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