Vibration transmission through rolling element bearings, part I: Bearing stiffness formulation

1990 ◽  
Vol 139 (2) ◽  
pp. 179-199 ◽  
Author(s):  
T.C. Lim ◽  
R. Singh
Keyword(s):  
Rolling Element Bearings ◽  
Vibration Transmission ◽  
Rolling Element ◽  
Bearing Stiffness

Nonlinear Parameter Estimation in Rotor-Bearing System Using Volterra Series and Method of Harmonic Probing

2003 ◽  
Vol 125 (3) ◽  
pp. 299-306 ◽  
Author(s):  
Animesh Chatterjee ◽  
Nalinaksh S. Vyas
Keyword(s):  
Volterra Series ◽  
Parametric Identification ◽  
Harmonic Amplitude ◽  
Rolling Element Bearings ◽  
Identification Procedure ◽  
Rolling Element ◽  
Rotor Bearing ◽  
Bearing Stiffness ◽  
Recursive Evaluation ◽  
Bearing System

Volterra series provides a structured analytical platform for modeling and identification of nonlinear systems. The series has been widely used in nonparametric identification through higher order frequency response functions or FRFs. A parametric identification procedure based on recursive evaluation of response harmonic amplitude series is presented here. The procedure is experimentally investigated for a rotor-bearing system supported in rolling element bearings. The estimates of nonlinear bearing stiffness obtained from experimentation have been compared with analytical values and experimental results of previous works.

Experimental investigation on time-domain features in the diagnosis of rolling element bearings by acoustic emission

2021 ◽  
pp. 107754632110161
Author(s):  
Aref Aasi ◽  
Ramtin Tabatabaei ◽  
Erfan Aasi ◽  
Seyed Mohammad Jafari
Keyword(s):  
Acoustic Emission ◽  
Condition Monitoring ◽  
Time Domain ◽  
Central Moment ◽  
Rolling Element Bearings ◽  
Test Rig ◽  
Acoustic Emission Sensor ◽  
Outer Race ◽  
Common Time ◽  
Rolling Element

Inspired by previous achievements, different time-domain features for diagnosis of rolling element bearings are investigated in this study. An experimental test rig is prepared for condition monitoring of angular contact bearing by using an acoustic emission sensor for this purpose. The acoustic emission signals are acquired from defective bearing, and the sensor takes signals from defects on the inner or outer race of the bearing. By studying the literature works, different domains of features are classified, and the most common time-domain features are selected for condition monitoring. The considered features are calculated for obtained signals with different loadings, speeds, and sizes of defects on the inner and outer race of the bearing. Our results indicate that the clearance, sixth central moment, impulse, kurtosis, and crest factors are appropriate features for diagnosis purposes. Moreover, our results show that the clearance factor for small defects and sixth central moment for large defects are promising for defect diagnosis on rolling element bearings.

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