Fault feature extraction and enhancement of rolling element bearing in varying speed condition
نویسندگان
چکیده
منابع مشابه
Fault Diagnosis of Rolling Bearing Based on Feature Extraction and Neural Network Algorithm
The rolling element bearing is a key part in many mechanical facilities and the diagnosis of its faults is very important in the field of predictive maintenance. Till date, the resonant demodulation technique (envelope analysis) has been widely exploited in practice. In complex machines, the vibration generated by a component is easily affected by the vibration of other components or is corrupt...
متن کاملFeature Extraction Method of Rolling Bearing Fault Signal Based on EEMD and Cloud Model Characteristic Entropy
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...
متن کاملDetermination of rolling element bearing condition via acoustic emission
Acoustic emission is an emerging technique for condition monitoring of rolling element bearings and potentially offers advantages for detection of incipient damage at an early stage of failure. Before such a technique can be applied with confidence for health monitoring, it is vital to understand the variation of acoustic emission generation with operating conditions in a healthy bearing. This ...
متن کاملWire Finishing Mill Rolling Bearing Fault Diagnosis Based on Feature Extraction and BP Neural Network
Rolling bearing is main part of rotary machine. It is frail section of rotary machine. Its running status affects entire mechanical equipment system performance directly. Vibration acceleration signals of the third finishing mill of Anshan Steel and Iron Group wire plant were collected in this paper. Fourier analysis, power spectrum analysis and wavelet transform were made on collected signals....
متن کاملAnn Based Fault Diagnosis of Rolling Element Bearing Using Time-frequency Domain Feature
This paper presents a methodology for an automation of fault diagnosis of ball bearings having localized defects (spalls) on the various bearing components. The system uses the wavelet packet decomposition using ‘rbio5.5’ real mother wavelet function for feature extraction from the vibration signal, recorded for various bearing fault conditions. The decomposition level is determined by the samp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mechanical Systems and Signal Processing
سال: 2016
ISSN: 0888-3270
DOI: 10.1016/j.ymssp.2016.02.021