Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy
Aiming at the problem that it is difficult to identify the composite fault characteristics of gearboxes in the case of small samples, a local mean decomposition(LMD) gearbox fault diagnosis method based on energy entropy is proposed. The LMD method is used to process the gearbox vibration signal to...
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Format: | Article |
Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2022-10-01
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Series: | Jixie chuandong |
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Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.10.004 |
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author | Xu Le Li Wei Zhang Bo Zhu Yubin Lang Chaonan |
author_facet | Xu Le Li Wei Zhang Bo Zhu Yubin Lang Chaonan |
author_sort | Xu Le |
collection | DOAJ |
description | Aiming at the problem that it is difficult to identify the composite fault characteristics of gearboxes in the case of small samples, a local mean decomposition(LMD) gearbox fault diagnosis method based on energy entropy is proposed. The LMD method is used to process the gearbox vibration signal to obtain several PF components;the dispersion value of component energy in the frequency domain is calculated using the uneven distribution of gearbox vibration signals in different states, which is the LMD energy entropy; the gearbox fault classification is carried out through the distribution of LMD energy entropy in different states. The experimental results show that in the case of small samples, the feature extraction and fault diagnosis of gearbox fault types can be accurately carried out based on the LMD energy entropy method, which also shows the superiority of this method in gearbox fault diagnosis. |
format | Article |
id | doaj-art-70f6bdbb7aa2434e972390e6b5f73b8b |
institution | Kabale University |
issn | 1004-2539 |
language | zho |
publishDate | 2022-10-01 |
publisher | Editorial Office of Journal of Mechanical Transmission |
record_format | Article |
series | Jixie chuandong |
spelling | doaj-art-70f6bdbb7aa2434e972390e6b5f73b8b2025-01-10T14:47:09ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392022-10-0146242931572394Research on Gearbox Fault Diagnosis Based on LMD Energy EntropyXu LeLi WeiZhang BoZhu YubinLang ChaonanAiming at the problem that it is difficult to identify the composite fault characteristics of gearboxes in the case of small samples, a local mean decomposition(LMD) gearbox fault diagnosis method based on energy entropy is proposed. The LMD method is used to process the gearbox vibration signal to obtain several PF components;the dispersion value of component energy in the frequency domain is calculated using the uneven distribution of gearbox vibration signals in different states, which is the LMD energy entropy; the gearbox fault classification is carried out through the distribution of LMD energy entropy in different states. The experimental results show that in the case of small samples, the feature extraction and fault diagnosis of gearbox fault types can be accurately carried out based on the LMD energy entropy method, which also shows the superiority of this method in gearbox fault diagnosis.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.10.004GearboxLocal mean decompositionEnergy entropyFault diagnosis |
spellingShingle | Xu Le Li Wei Zhang Bo Zhu Yubin Lang Chaonan Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy Jixie chuandong Gearbox Local mean decomposition Energy entropy Fault diagnosis |
title | Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy |
title_full | Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy |
title_fullStr | Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy |
title_full_unstemmed | Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy |
title_short | Research on Gearbox Fault Diagnosis Based on LMD Energy Entropy |
title_sort | research on gearbox fault diagnosis based on lmd energy entropy |
topic | Gearbox Local mean decomposition Energy entropy Fault diagnosis |
url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.10.004 |
work_keys_str_mv | AT xule researchongearboxfaultdiagnosisbasedonlmdenergyentropy AT liwei researchongearboxfaultdiagnosisbasedonlmdenergyentropy AT zhangbo researchongearboxfaultdiagnosisbasedonlmdenergyentropy AT zhuyubin researchongearboxfaultdiagnosisbasedonlmdenergyentropy AT langchaonan researchongearboxfaultdiagnosisbasedonlmdenergyentropy |