A Fast Kurtogram Demodulation Method in Rolling Bearing Fault Diagnosis
نویسندگان
چکیده
منابع مشابه
Application of Resonance Demodulation in Rolling Bearing Fault Diagnosis Based on Electronic Resonant
The resonance demodulation is an important method in rolling bearing fault feature extraction and fault diagnosis. But in the traditional resonance demodulation method, the resonant frequency of the accelerometer sensing fault information is discrete to some degree due to processing, debugging and installing factors, and the parameters of the band-pass filter are in need for defining beforehand...
متن کاملA 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...
متن کاملFault severity diagnosis of rolling element bearings based on kurtogram and envelope analysis
Faults in rolling element bearing are among the main causes of breakdown in rotating machines. Vibration is an effective technique for machine condition monitoring. Vibration signals from a defective bearing with a localized fault contain a series of impulsive responses, which result from the impacts of the defective part(s) with other elements. Most researches carried out have focused on fault...
متن کاملFault Diagnosis Method Based on a New Supervised Locally Linear Embedding Algorithm for Rolling Bearing
In view of the complexity and nonlinearity of rolling bearings, this paper presents a new supervised locally linear embedding method (R-NSLLE) for feature extraction. In general, traditional LLE can capture the local structure of a rolling bearing. However it may lead to limited effectiveness if data is sparse or non-uniformly distributed. Moreover, like other manifold learning algorithms, the ...
متن کاملImproved Ensemble Empirical Mode Decomposition for Rolling Bearing Fault Diagnosis
Rolling bearing is an important part in mechanical system and faults occur frequently with vibration noise. Empirical mode decomposition (EMD) is a tool for nonlinear and non-stationary signals analysis. However, the major drawbacks of EMD are mode mixing problem, ensemble empirical mode decomposition (EEMD) provides a new tool for signal analysis, and it is an improved technique of EMD. In ord...
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: MATEC Web of Conferences
سال: 2016
ISSN: 2261-236X
DOI: 10.1051/matecconf/20167701003