A Study of the Diagnostic Amplitude of Rolling Bearing under Increasing Radial Clearance Using Modulation Signal Bispectrum
نویسندگان
چکیده
The rolling element bearing is a key part of machines. The accurate and timely diagnosis of its faults is critical for predictive maintenance. Most researches have focused on the fault location identification. To estimate the fault severity accurately, this paper focuses on the study of roller bearing vibration amplitude under increasing radial clearances due to inevitable wear using the modulation signal bispectrum (MSB). The experiment is carried out for bearings with two different clearances for the inner race fault and the outer race fault cases. The results show that the vibration amplitudes at fault characteristic frequencies exhibit significant changes with increasing clearances. However, the amplitudes of vibrations tend to increase with the severity of the outer race fault and decrease with the severity of the inner race fault. Therefore, it is necessary to take into account these effects in diagnosing the size of defect.
منابع مشابه
The fault detection and severity diagnosis of rolling element bearings using modulation signal bispectrum
The rolling element bearing is a key part in many mechanical equipment. The accurate and timely diagnosis of its faults is critical for predictive maintenance. 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 and inevitable noise. Most researches carried out have ...
متن کاملA Study of Motor Bearing Fault Diagnosis using Modulation Signal Bispectrum Analysis of Motor Current Signals
Failure of induction motors are a large concern due to its influence over industrial production. Motor current signature analysis (MCSA) is common practice in industry to find motor faults. This paper presents a new approach to detection and diagnosis of motor bearing faults based on induction motor stator current analysis. Tests were performed with three bearing conditions: baseline, outer rac...
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 کاملRolling 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 کاملIdentification of rotor bearing parameters using vibration response data in a turbocharger rotor
Turbochargers are most widely used in automotive, marine and locomotive applications with diesel engines. To increase the engine performance nowadays, in aerospace applications also turbochargers are used. Mostly the turbocharger rotors are commonly supported over the fluid film bearings. With the operation, lubricant properties continuously alter leading to different load bearing capacities. T...
متن کامل