Bearing Fault Diagnosis Method Using Envelope Analysis and Euclidean Distance
نویسندگان
چکیده
Bearings are widely used in rotating machines. Its health status is a significant index to indicate whether machines run continually or not. Detecting the bearing faults timely is very important for the maintenance decision making. In this paper, a new fault diagnosis method based on envelope analysis and Euclidean Distance is developed. Envelope analysis is used to enable the fault frequencies clearly. Then, amplitudes of fault frequencies are used as the fault features. Finally, Euclidean Distance is used to identify the different fault types. This method can identify the fault locations intelligently even if the bearings are under different fault levels. The effectiveness of this methodology is demonstrated using the bearing data sets of Case Western Reserve Univerity.
منابع مشابه
Rolling Bearing Fault Analysis by Interpolating Windowed DFT Algorithm
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...
متن کاملFault Diagnosis Method Based on Kurtosis Wave and Information Divergence for Rolling Element Bearings
Fault diagnosis depends largely on feature analysis of vibration signals. However, feature extraction for fault diagnosis is difficult because the vibration signals often contain a strong noise component. Noises stronger than the actual fault signal may interfere with diagnosis and ultimately cause misdiagnosis. In order to extract the feature from a fault signal highly contaminated by the nois...
متن کاملDiagnosis of Rolling Element Bearing Fault in Bearing-gearbox Union System Using Wavelet Packet Correlation Analysis
The failure of rotating machinery sometimes involves several faulty components. Existence of both bearing fault and gearbox fault is widely observed and in this situation the vibration feature of the bearing fault can be masked by the faulty gearbox vibration signals. In this research, a method is proposed based on wavelet packet transform and envelope analysis to extract fault features of the ...
متن کاملMulti-Scale Hermitian Wavelet Order Envelope Spectrum Based Bearing Fault Detection and Diagnosis
The multi-scale Hermitian wavelet order envelope spectrum based bearing fault detection and diagnosis method under run-up condition is presented in this paper. This new approach based on the fusion of the computed order tracking, Hermitian wavelet transform and envelope spectrum is used for detection defects in roller element bearings. Firstly, Non-stationary vibration signal under run-up condi...
متن کاملA Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery
This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information...
متن کامل