A method to diagnose compound fault of rolling bearing with ITD-AF
نویسندگان
چکیده
منابع مشابه
A DWT and SVM based method for rolling element bearing fault diagnosis and its comparison with Artificial Neural Networks
A classification technique using Support Vector Machine (SVM) classifier for detection of rolling element bearing fault is presented here. The SVM was fed from features that were extracted from of vibration signals obtained from experimental setup consisting of rotating driveline that was mounted on rolling element bearings which were run in normal and with artificially faults induced conditio...
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This paper focuses on the problem of accurate Fault Characteristic Frequency (FCF) estimation of rolling bearing. Teager-Kaiser Energy Operator (TKEO) demodulation has been applied widely to rolling bearing fault detection. FCF can be extracted from vibration signals, which is pre-treatment by TEKO demodulation method. However, because of strong noise background of fault vibration signal, it is...
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The randomness and fuzziness that exist in rolling bearings when faults occur result in uncertainty in acquisition signals and reduce the accuracy of signal feature extraction. To solve this problem, this study proposes a new method in which cloud model characteristic entropy (CMCE) is set as the signal characteristic eigenvalue. This approach can overcome the disadvantages of traditional entro...
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ژورنال
عنوان ژورنال: Journal of Vibroengineering
سال: 2021
ISSN: 1392-8716,2538-8460
DOI: 10.21595/jve.2020.21476