Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing
The defect characteristics of rolling bearing are difficult to excavate at the incipient injury phase; in order to effectively solve this issue, an original strategy fusing recursive singular spectrum decomposition (RSSD) with optimized cyclostationary blind deconvolution (OCYCBD) is put forward to...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/5424236 |
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| author | Xiaolong Wang Guiji Tang Yuling He |
| author_facet | Xiaolong Wang Guiji Tang Yuling He |
| author_sort | Xiaolong Wang |
| collection | DOAJ |
| description | The defect characteristics of rolling bearing are difficult to excavate at the incipient injury phase; in order to effectively solve this issue, an original strategy fusing recursive singular spectrum decomposition (RSSD) with optimized cyclostationary blind deconvolution (OCYCBD) is put forward to achieve fault characteristic enhanced detection. In this diagnosis strategy, the data-driven RSSD method without predetermined component number is proposed. In addition, a new morphological difference operation entropy (MDOE) indicator, which takes advantage of morphological transformation and Shannon entropy, is developed for confirming the influencing parameters of cyclostationary blind deconvolution (CYCBD). During the process of fault detection, RSSD is firstly adopted to preprocess the original signal, and the most sensitive singular spectrum component (SSC) is selected by the envelope spectrum peak (ESP) indicator. Then, the grid search algorithm is adopted to precisely confirm the optimal parameters and OCYCBD is further performed as a postprocessing technology on the most sensitive component to suppress the residual interferences and amplify the fault signatures. Finally, the enhanced fault detection of rolling bearing is able to achieve by analyzing the envelope spectrum of deconvolution signal. The feasibility of the proposed strategy is verified by the simulated and the measured signals, respectively, and its superiority is also demonstrated through several comparison methods. The results manifest this novel strategy has praisable advantages on weak characteristic extraction and intensification. |
| format | Article |
| id | doaj-art-498d0f90d9a94588a817f4d1ce7b99f4 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-498d0f90d9a94588a817f4d1ce7b99f42025-02-03T01:20:27ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/54242365424236Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling BearingXiaolong Wang0Guiji Tang1Yuling He2Department of Mechanical Engineering, North China Electric Power University, Baoding 071000, ChinaDepartment of Mechanical Engineering, North China Electric Power University, Baoding 071000, ChinaDepartment of Mechanical Engineering, North China Electric Power University, Baoding 071000, ChinaThe defect characteristics of rolling bearing are difficult to excavate at the incipient injury phase; in order to effectively solve this issue, an original strategy fusing recursive singular spectrum decomposition (RSSD) with optimized cyclostationary blind deconvolution (OCYCBD) is put forward to achieve fault characteristic enhanced detection. In this diagnosis strategy, the data-driven RSSD method without predetermined component number is proposed. In addition, a new morphological difference operation entropy (MDOE) indicator, which takes advantage of morphological transformation and Shannon entropy, is developed for confirming the influencing parameters of cyclostationary blind deconvolution (CYCBD). During the process of fault detection, RSSD is firstly adopted to preprocess the original signal, and the most sensitive singular spectrum component (SSC) is selected by the envelope spectrum peak (ESP) indicator. Then, the grid search algorithm is adopted to precisely confirm the optimal parameters and OCYCBD is further performed as a postprocessing technology on the most sensitive component to suppress the residual interferences and amplify the fault signatures. Finally, the enhanced fault detection of rolling bearing is able to achieve by analyzing the envelope spectrum of deconvolution signal. The feasibility of the proposed strategy is verified by the simulated and the measured signals, respectively, and its superiority is also demonstrated through several comparison methods. The results manifest this novel strategy has praisable advantages on weak characteristic extraction and intensification.http://dx.doi.org/10.1155/2020/5424236 |
| spellingShingle | Xiaolong Wang Guiji Tang Yuling He Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing Complexity |
| title | Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing |
| title_full | Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing |
| title_fullStr | Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing |
| title_full_unstemmed | Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing |
| title_short | Application of RSSD-OCYCBD Strategy in Enhanced Fault Detection of Rolling Bearing |
| title_sort | application of rssd ocycbd strategy in enhanced fault detection of rolling bearing |
| url | http://dx.doi.org/10.1155/2020/5424236 |
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