Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis
The detection of cyclic impulsive components, which serve as crucial indicators for extracting bearing faults, from vibration signals holds significant importance in fault diagnosis. The deconvolution methods have been demonstrated as a useful tool for highlighting cyclic impulsive components induce...
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IEEE
2024-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10756597/ |
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| author | Ying Ma Siming He Entie Qi Yu Wei |
| author_facet | Ying Ma Siming He Entie Qi Yu Wei |
| author_sort | Ying Ma |
| collection | DOAJ |
| description | The detection of cyclic impulsive components, which serve as crucial indicators for extracting bearing faults, from vibration signals holds significant importance in fault diagnosis. The deconvolution methods have been demonstrated as a useful tool for highlighting cyclic impulsive components induced by bearing faults. Recently, a novel deconvolution technique named Minimum Noise Amplitude Deconvolution (MNAD) was proposed to effectively enhance the periodic impulses from heavily corrupted signals. The challenges, however, exist in the application of the MNAD under harsh working conditions. The challenges primarily arise from the rigorous requirements for the multi-input parameters. To address these issues, an improved MNAD (IMNAD) is proposed in this study. First, the novel approach uses the autocorrelation analysis of the envelope signal to estimate a key parameter of the fault period, instead of depending on the given prior period. Moreover, an improved sparrow search algorithm combining sine-cosine and Cauchy mutation (SCC-SSA) is employed to determine the optimal values for the remaining two key parameters, namely the filter length, the number of iterations, and the noise ratio. The IMNAD, in comparison to the original MNAD, exhibits adaptability in parameter selection across diverse operational conditions, thereby demonstrating its efficacy and robustness. Finally, the effectiveness and superiority of IMNAD are validated through simulated and two real bearing fault signals. |
| format | Article |
| id | doaj-art-c0923339a47e4dcab56c61c66b117a5f |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-c0923339a47e4dcab56c61c66b117a5f2025-08-20T02:27:45ZengIEEEIEEE Access2169-35362024-01-011217418217419210.1109/ACCESS.2024.350158310756597Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault DiagnosisYing Ma0https://orcid.org/0009-0009-5801-7095Siming He1https://orcid.org/0000-0003-4845-6149Entie Qi2Yu Wei3School of Electrical and Information Engineering, Changchun Institute of Technology, Changchun, ChinaSchool of Electrical and Information Engineering, Changchun Institute of Technology, Changchun, ChinaBig Data and Information Technology Centre, Changchun Institute of Technology, Changchun, ChinaSchool of Automation, Xi’an University of Posts and Telecommunications, Xi’an, Shaanxi, ChinaThe detection of cyclic impulsive components, which serve as crucial indicators for extracting bearing faults, from vibration signals holds significant importance in fault diagnosis. The deconvolution methods have been demonstrated as a useful tool for highlighting cyclic impulsive components induced by bearing faults. Recently, a novel deconvolution technique named Minimum Noise Amplitude Deconvolution (MNAD) was proposed to effectively enhance the periodic impulses from heavily corrupted signals. The challenges, however, exist in the application of the MNAD under harsh working conditions. The challenges primarily arise from the rigorous requirements for the multi-input parameters. To address these issues, an improved MNAD (IMNAD) is proposed in this study. First, the novel approach uses the autocorrelation analysis of the envelope signal to estimate a key parameter of the fault period, instead of depending on the given prior period. Moreover, an improved sparrow search algorithm combining sine-cosine and Cauchy mutation (SCC-SSA) is employed to determine the optimal values for the remaining two key parameters, namely the filter length, the number of iterations, and the noise ratio. The IMNAD, in comparison to the original MNAD, exhibits adaptability in parameter selection across diverse operational conditions, thereby demonstrating its efficacy and robustness. Finally, the effectiveness and superiority of IMNAD are validated through simulated and two real bearing fault signals.https://ieeexplore.ieee.org/document/10756597/Bearing fault diagnosisautocorrelation analysisimproved sparrow search algorithmminimum noise amplitude deconvolutionimproved MNAD |
| spellingShingle | Ying Ma Siming He Entie Qi Yu Wei Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis IEEE Access Bearing fault diagnosis autocorrelation analysis improved sparrow search algorithm minimum noise amplitude deconvolution improved MNAD |
| title | Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis |
| title_full | Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis |
| title_fullStr | Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis |
| title_full_unstemmed | Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis |
| title_short | Application of an Improved Minimum Noise Amplitude Deconvolution for Bearing Fault Diagnosis |
| title_sort | application of an improved minimum noise amplitude deconvolution for bearing fault diagnosis |
| topic | Bearing fault diagnosis autocorrelation analysis improved sparrow search algorithm minimum noise amplitude deconvolution improved MNAD |
| url | https://ieeexplore.ieee.org/document/10756597/ |
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