FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM
To solve the problem that the amplitude of the added white noise and the number of ensemble trials to the ensemble empirical mode decomposition algorithm depend too much on subjective experience or multiple attempts, which is more subjective and blind, a fault diagnosis method based on adaptive EEMD...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2022-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.05.02 |
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| _version_ | 1841534432097337344 |
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| author | XIANG Wei LI RuYu WANG Hui TIAN LiYong YU Ning |
| author_facet | XIANG Wei LI RuYu WANG Hui TIAN LiYong YU Ning |
| author_sort | XIANG Wei |
| collection | DOAJ |
| description | To solve the problem that the amplitude of the added white noise and the number of ensemble trials to the ensemble empirical mode decomposition algorithm depend too much on subjective experience or multiple attempts, which is more subjective and blind, a fault diagnosis method based on adaptive EEMD and Fast Kurtogram is proposed. Firstly, the collected vibration signals are preprocessed by EMD to obtain the key input parameters of EEMD adaptively, and then combined with the “double threshold criterion” of the kurtosis and cross-correlation coefficient quickly choose components for signal reconstruction to highlight the fault characteristic, and through the Fast Kurtogram select optimal band-pass filter parameters, finally, the signal after filtering do envelope spectrum analysis, realize the extraction of fault feature frequency and fault diagnosis.The validity of the proposed method is verified by simulation signal analysis and fault diagnosis engineering application of reducer gearbox and comparing with the EMD method and the traditional EEMD method.The results show that the proposed method can successfully extract the reducer gearbox’s early weak fault characteristics from the signal with strong background noise, and the timeliness and accuracy of fault diagnosis are improved. |
| format | Article |
| id | doaj-art-b4251fc820eb415aba5dc629a0145507 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2022-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-b4251fc820eb415aba5dc629a01455072025-01-15T02:39:35ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692022-01-01441024103131951626FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAMXIANG WeiLI RuYuWANG HuiTIAN LiYongYU NingTo solve the problem that the amplitude of the added white noise and the number of ensemble trials to the ensemble empirical mode decomposition algorithm depend too much on subjective experience or multiple attempts, which is more subjective and blind, a fault diagnosis method based on adaptive EEMD and Fast Kurtogram is proposed. Firstly, the collected vibration signals are preprocessed by EMD to obtain the key input parameters of EEMD adaptively, and then combined with the “double threshold criterion” of the kurtosis and cross-correlation coefficient quickly choose components for signal reconstruction to highlight the fault characteristic, and through the Fast Kurtogram select optimal band-pass filter parameters, finally, the signal after filtering do envelope spectrum analysis, realize the extraction of fault feature frequency and fault diagnosis.The validity of the proposed method is verified by simulation signal analysis and fault diagnosis engineering application of reducer gearbox and comparing with the EMD method and the traditional EEMD method.The results show that the proposed method can successfully extract the reducer gearbox’s early weak fault characteristics from the signal with strong background noise, and the timeliness and accuracy of fault diagnosis are improved.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.05.02GearboxEnsemble empirical mode decompositionFast kurtogramKurtosisCross-correlation coefficientFault diagnosis |
| spellingShingle | XIANG Wei LI RuYu WANG Hui TIAN LiYong YU Ning FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM Jixie qiangdu Gearbox Ensemble empirical mode decomposition Fast kurtogram Kurtosis Cross-correlation coefficient Fault diagnosis |
| title | FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM |
| title_full | FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM |
| title_fullStr | FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM |
| title_full_unstemmed | FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM |
| title_short | FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM |
| title_sort | fault diagnosis of gearbox based on adaptive eemd and fast kurtogram |
| topic | Gearbox Ensemble empirical mode decomposition Fast kurtogram Kurtosis Cross-correlation coefficient Fault diagnosis |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.05.02 |
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