@inproceedings{2997dd45d6cd4955b3b6717f50155216,
title = "A Fault Diagnosis Method for Rotating Machinery under Variable Speed Condition Based on Infrared Thermography",
abstract = "Rotating machinery always works under variable speed and heavy load, resulting in difficulty in fault diagnosis. To avoid the influence caused by variable speed and noise, a novel fault diagnosis framework based on infrared thermography (IRT) is proposed in this paper. First, the IRT technique is introduced to acquire thermal images. Second, Bag-of-visual-word (BoVW) is used to extract visual features from the thermal images. In the end, the extracted visual features are taken into Softmax regression classifier to recognize the fault types of rotating machinery. The effectiveness of the proposed method is validated using the experimental data. Results show that the performance of proposed method is superior to the vibration based method in identifying ten health conditions of rotating machinery under variable speed condition.",
keywords = "BoVw, fault diagnosis, infrared thermography, rotating machinery, Softmax, variable speed conditions",
author = "Xianzhi Wang and Shubin Si and Yongbo Li and Yifan Li",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2018 ; Conference date: 15-08-2018 Through 17-08-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/SDPC.2018.8664850",
language = "英语",
series = "Proceedings - 2018 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "30--34",
editor = "Chuan Li and Dian Wang and Diego Cabrera and Yong Zhou and Chunlin Zhang",
booktitle = "Proceedings - 2018 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2018",
}