A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis
Mathematical morphology (MM) is an efficient nonlinear signal processing tool. It can be adopted to extract fault information from bearing signal according to a structuring element (SE). Since the bearing signal features differ for every unique cause of failure, the SEs should be well tailored to ex...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2014/590875 |
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| _version_ | 1832564381317070848 |
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| author | Zhaowen Chen Ning Gao Wei Sun Qiong Chen Fengying Yan Xinyu Zhang Maria Iftikhar Shiwei Liu Zhongqi Ren |
| author_facet | Zhaowen Chen Ning Gao Wei Sun Qiong Chen Fengying Yan Xinyu Zhang Maria Iftikhar Shiwei Liu Zhongqi Ren |
| author_sort | Zhaowen Chen |
| collection | DOAJ |
| description | Mathematical morphology (MM) is an efficient nonlinear signal processing tool. It can be adopted to extract fault information from bearing signal according to a structuring element (SE). Since the bearing signal features differ for every unique cause of failure, the SEs should be well tailored to extract the fault feature from a particular signal. In the following, a signal based triangular SE according to the statistics of the magnitude of a vibration signal is proposed, together with associated methodology, which processes the bearing signal by MM analysis based on proposed SE to get the morphology spectrum of a signal. A correlation analysis on morphology spectrum is then employed to obtain the final classification of bearing faults. The classification performance of the proposed method is evaluated by a set of bearing vibration signals with inner race, ball, and outer race faults, respectively. Results show that all faults can be detected clearly and correctly. Compared with a commonly used flat SE, the correlation analysis on morphology spectrum with proposed SE gives better performance at fault diagnosis of bearing, especially the identification of the location of outer race fault and the level of fault severity. |
| format | Article |
| id | doaj-art-0e728d139e5b4b1a818613c31c7db03a |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-0e728d139e5b4b1a818613c31c7db03a2025-02-03T01:11:03ZengWileyShock and Vibration1070-96221875-92032014-01-01201410.1155/2014/590875590875A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault DiagnosisZhaowen Chen0Ning Gao1Wei Sun2Qiong Chen3Fengying Yan4Xinyu Zhang5Maria Iftikhar6Shiwei Liu7Zhongqi Ren8College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaCollege of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, ChinaMathematical morphology (MM) is an efficient nonlinear signal processing tool. It can be adopted to extract fault information from bearing signal according to a structuring element (SE). Since the bearing signal features differ for every unique cause of failure, the SEs should be well tailored to extract the fault feature from a particular signal. In the following, a signal based triangular SE according to the statistics of the magnitude of a vibration signal is proposed, together with associated methodology, which processes the bearing signal by MM analysis based on proposed SE to get the morphology spectrum of a signal. A correlation analysis on morphology spectrum is then employed to obtain the final classification of bearing faults. The classification performance of the proposed method is evaluated by a set of bearing vibration signals with inner race, ball, and outer race faults, respectively. Results show that all faults can be detected clearly and correctly. Compared with a commonly used flat SE, the correlation analysis on morphology spectrum with proposed SE gives better performance at fault diagnosis of bearing, especially the identification of the location of outer race fault and the level of fault severity.http://dx.doi.org/10.1155/2014/590875 |
| spellingShingle | Zhaowen Chen Ning Gao Wei Sun Qiong Chen Fengying Yan Xinyu Zhang Maria Iftikhar Shiwei Liu Zhongqi Ren A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis Shock and Vibration |
| title | A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis |
| title_full | A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis |
| title_fullStr | A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis |
| title_full_unstemmed | A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis |
| title_short | A Signal Based Triangular Structuring Element for Mathematical Morphological Analysis and Its Application in Rolling Element Bearing Fault Diagnosis |
| title_sort | signal based triangular structuring element for mathematical morphological analysis and its application in rolling element bearing fault diagnosis |
| url | http://dx.doi.org/10.1155/2014/590875 |
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