GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION
VMD has better band-pass filtering characteristic, which can non-recursively decomposition a real-valued multi-composition signal into a discrete number of quasi-orthogonal band-limited sub-signals with specific sparsity properties in the spectral. Modulation intensity distribution（MID） combined wit...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.02.003 |
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| author | ZHANG SuoFeng WANG YanXue HE ShuiLong HU ChaoFan JIANG ZhanSi |
| author_facet | ZHANG SuoFeng WANG YanXue HE ShuiLong HU ChaoFan JIANG ZhanSi |
| author_sort | ZHANG SuoFeng |
| collection | DOAJ |
| description | VMD has better band-pass filtering characteristic, which can non-recursively decomposition a real-valued multi-composition signal into a discrete number of quasi-orthogonal band-limited sub-signals with specific sparsity properties in the spectral. Modulation intensity distribution（MID） combined with VMD is applied to detect second-order cyclostationary components in gear fault diagnosis. Impulsive signatures generally represent the transients in the signals and are often caused by local defect in the gear of rotating machinery. Detecting these signatures is vital for mechanical signal processing and fault diagnosis. The impulsive signatures can be successfully extracted using VMD, meanwhile, Signal-noise can be separated to some extent. It is very useful tool to MID detects modulation components. However, when the analyzed signal contains multiple modulations usually mixed with other harmonic components, visual examination of the spectrum may not be accurate for identification of all carriers together with their modulation signals. Considering the shortcomings of MID in the analysis of multi-harmonic modulation signals, VMD is used as the signal preprocessing before MID analysis. Results of simulation and the experimental analysis have demonstrated the effectiveness of the method. |
| format | Article |
| id | doaj-art-f2a9ad8c4ffe4c2dbabec6d39c72b3a8 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-f2a9ad8c4ffe4c2dbabec6d39c72b3a82025-01-15T02:30:09ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014126727430604159GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTIONZHANG SuoFengWANG YanXueHE ShuiLongHU ChaoFanJIANG ZhanSiVMD has better band-pass filtering characteristic, which can non-recursively decomposition a real-valued multi-composition signal into a discrete number of quasi-orthogonal band-limited sub-signals with specific sparsity properties in the spectral. Modulation intensity distribution（MID） combined with VMD is applied to detect second-order cyclostationary components in gear fault diagnosis. Impulsive signatures generally represent the transients in the signals and are often caused by local defect in the gear of rotating machinery. Detecting these signatures is vital for mechanical signal processing and fault diagnosis. The impulsive signatures can be successfully extracted using VMD, meanwhile, Signal-noise can be separated to some extent. It is very useful tool to MID detects modulation components. However, when the analyzed signal contains multiple modulations usually mixed with other harmonic components, visual examination of the spectrum may not be accurate for identification of all carriers together with their modulation signals. Considering the shortcomings of MID in the analysis of multi-harmonic modulation signals, VMD is used as the signal preprocessing before MID analysis. Results of simulation and the experimental analysis have demonstrated the effectiveness of the method.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.02.003Variational mode decompositionModulation intensity distributionGearFault diagnosis |
| spellingShingle | ZHANG SuoFeng WANG YanXue HE ShuiLong HU ChaoFan JIANG ZhanSi GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION Jixie qiangdu Variational mode decomposition Modulation intensity distribution Gear Fault diagnosis |
| title | GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION |
| title_full | GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION |
| title_fullStr | GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION |
| title_full_unstemmed | GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION |
| title_short | GEAR FAULT DIAGNOSIS BASED ON THE VMD AND MODULATION SPECTRUM INTENSITY DISTRIBUTION |
| title_sort | gear fault diagnosis based on the vmd and modulation spectrum intensity distribution |
| topic | Variational mode decomposition Modulation intensity distribution Gear Fault diagnosis |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.02.003 |
| work_keys_str_mv | AT zhangsuofeng gearfaultdiagnosisbasedonthevmdandmodulationspectrumintensitydistribution AT wangyanxue gearfaultdiagnosisbasedonthevmdandmodulationspectrumintensitydistribution AT heshuilong gearfaultdiagnosisbasedonthevmdandmodulationspectrumintensitydistribution AT huchaofan gearfaultdiagnosisbasedonthevmdandmodulationspectrumintensitydistribution AT jiangzhansi gearfaultdiagnosisbasedonthevmdandmodulationspectrumintensitydistribution |