A New Intelligent Fault Diagnosis Method of Rotating Machinery under Varying-Speed Conditions Using Infrared Thermography. (19th August 2019)

• Record Type: Journal Article
• Authors: Li, Yongbo; Wang, Xianzhi; Si, Shubin; Du, Xiaoqiang
• Other Names: Pratama Mahardhika Academic Editor.
• Is Part Of: Complexity. Volume 2019(2019)
• Publication Date: 2019-08-19
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2019/2619252
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : 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.