Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification
To deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC) is proposed. The wavelet packet is employed to decompose the vibratio...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/145807 |
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| _version_ | 1832548764227731456 |
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| author | Pengfei Li Yongying Jiang Jiawei Xiang |
| author_facet | Pengfei Li Yongying Jiang Jiawei Xiang |
| author_sort | Pengfei Li |
| collection | DOAJ |
| description | To deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC) is proposed. The wavelet packet is employed to decompose the vibration signal to obtain the energy ratio in each frequency band. Taking energy ratios as feature vectors, the pattern recognition results are obtained by the SVC. The rolling bearing and gear fault diagnostic results of the typical experimental platform show that the present approach is robust to noise and has higher classification accuracy and, thus, provides a better way to diagnose mechanical faults under the condition of small fault samples. |
| format | Article |
| id | doaj-art-5f407321960a4120be06bc47662dbc3a |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-5f407321960a4120be06bc47662dbc3a2025-02-03T06:13:05ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/145807145807Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector ClassificationPengfei Li0Yongying Jiang1Jiawei Xiang2College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, ChinaTo deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC) is proposed. The wavelet packet is employed to decompose the vibration signal to obtain the energy ratio in each frequency band. Taking energy ratios as feature vectors, the pattern recognition results are obtained by the SVC. The rolling bearing and gear fault diagnostic results of the typical experimental platform show that the present approach is robust to noise and has higher classification accuracy and, thus, provides a better way to diagnose mechanical faults under the condition of small fault samples.http://dx.doi.org/10.1155/2014/145807 |
| spellingShingle | Pengfei Li Yongying Jiang Jiawei Xiang Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification The Scientific World Journal |
| title | Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification |
| title_full | Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification |
| title_fullStr | Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification |
| title_full_unstemmed | Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification |
| title_short | Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification |
| title_sort | experimental investigation for fault diagnosis based on a hybrid approach using wavelet packet and support vector classification |
| url | http://dx.doi.org/10.1155/2014/145807 |
| work_keys_str_mv | AT pengfeili experimentalinvestigationforfaultdiagnosisbasedonahybridapproachusingwaveletpacketandsupportvectorclassification AT yongyingjiang experimentalinvestigationforfaultdiagnosisbasedonahybridapproachusingwaveletpacketandsupportvectorclassification AT jiaweixiang experimentalinvestigationforfaultdiagnosisbasedonahybridapproachusingwaveletpacketandsupportvectorclassification |