A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography

A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography

A novel systematic framework, infrared thermography- (IRT-) based method, for rotating machinery fault diagnosis under nonstationary running conditions is presented in this paper. In this framework, IRT technique is first applied to obtain the thermograph. Then, the fault features are extracted usin...

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Main Authors: Yongbo Li, Xianzhi Wang, Shubin Si, Xiaoqiang Du
Format: Article
Language:English
Published: Hindawi-Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/2619252
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spelling doaj-584d1cf13b86456c8b4877bde40b2db12020-11-25T01:25:39ZengHindawi-WileyComplexity1076-27871099-05262019-01-01201910.1155/2019/26192522619252A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared ThermographyYongbo Li0Xianzhi Wang1Shubin Si2Xiaoqiang Du3MIIT Key Laboratory of Dynamics and Control of Complex Systems, School of Aeronautics, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaA novel systematic framework, infrared thermography- (IRT-) based method, for rotating machinery fault diagnosis under nonstationary running conditions is presented in this paper. In this framework, IRT technique is first applied to obtain the thermograph. Then, the fault features are extracted using bag-of-visual-word (BoVW) from the IRT images. In the end, support vector machine (SVM) is utilized to automatically identify the fault patterns of rotating machinery. The effectiveness of proposed method is evaluated using lab experimental signal of rotating machinery. The diagnosis results show that the IRT-based method has certain advantages in classification rotating machinery faults under nonstationary running conditions compared with the traditional vibration-based method.http://dx.doi.org/10.1155/2019/2619252
collection DOAJ
language English
format Article
sources DOAJ
author Yongbo Li
Xianzhi Wang
Shubin Si
Xiaoqiang Du
spellingShingle Yongbo Li
Xianzhi Wang
Shubin Si
Xiaoqiang Du
A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography
Complexity
author_facet Yongbo Li
Xianzhi Wang
Shubin Si
Xiaoqiang Du
author_sort Yongbo Li
title A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography
title_short A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography
title_full A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography
title_fullStr A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography
title_full_unstemmed A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography
title_sort new intelligent fault diagnosis method of rotating machinery under varying-speed conditions using infrared thermography
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2019-01-01
description A novel systematic framework, infrared thermography- (IRT-) based method, for rotating machinery fault diagnosis under nonstationary running conditions is presented in this paper. In this framework, IRT technique is first applied to obtain the thermograph. Then, the fault features are extracted using bag-of-visual-word (BoVW) from the IRT images. In the end, support vector machine (SVM) is utilized to automatically identify the fault patterns of rotating machinery. The effectiveness of proposed method is evaluated using lab experimental signal of rotating machinery. The diagnosis results show that the IRT-based method has certain advantages in classification rotating machinery faults under nonstationary running conditions compared with the traditional vibration-based method.
url http://dx.doi.org/10.1155/2019/2619252
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AT shubinsi anewintelligentfaultdiagnosismethodofrotatingmachineryundervaryingspeedconditionsusinginfraredthermography
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