A novel systematic framework, infrared thermography- (IRT-) based method, for rotating machinery fault diagnosis under\nnonstationary running conditions is presented in this paper. In this framework, IRT technique is first applied to obtain the\nthermograph. Then, the fault features are extracted using bag-of-visual-word (BoVW) from the IRT images. In the end, support\nvector machine (SVM) is utilized to automatically identify the fault patterns of rotating machinery.The effectiveness of proposed\nmethod is evaluated using lab experimental signal of rotating machinery. The diagnosis results show that the IRT-based method\nhas certain advantages in classification rotating machinery faults under nonstationary running conditions compared with the\ntraditional vibration-based method.
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