Theoretical and experimental studies to predict vibration responses of defects in spherical roller bearings using dimension theory

Abstract A frictionless force transmission between the mechanical components of high production volume systems was accomplished by Rolling Element Bearings, which leads to being an imperative item of the condition-based maintenance (CBM). A prominent fault would cause malfunction, and its substantial growth may lead to catastrophic failure of such machinery ultimately give rise to unscheduled maintenance, and in extreme cases turns into a quite expensive shut down of the same. These decisive situations explore a growing demand for a robust failure diagnosis scheme for bearings. The present work demonstrates a novel approach to develop a dynamic model for vibration response of spherical roller bearings using dimensional analysis with Buckingham’s pi theorem (BPT) by considering significant geometric, operating and thermal parameters of the system. The results obtained have been validated with experiments performed on the developed test rig under diverse operating conditions. Vibration amplitudes considerably enhanced in the presence of rotating speed, applied load, bearing temperature, and volume of defect. Multivariable regression analysis is performed to reveal the effectiveness of the model for precise detection of impending bearing failure. The vibration response obtained by the DA model, experimental runs and MVRA are agreeing with physical perceptive and potentials. Results indicate the simplicity and reliability of the approach.

[1]  Yuh-Tay Sheen,et al.  An analysis method for the vibration signal with amplitude modulation in a bearing system , 2007 .

[2]  D. P. Vakharia,et al.  A novel approach integrating dimensional analysis and neural networks for the detection of localized faults in roller bearings , 2016 .

[3]  R. G. Desavale,et al.  Antifriction Bearings Damage Analysis Using Experimental Data Based Models , 2013 .

[4]  H. Karagülle,et al.  Vibration analysis of rolling element bearings with various defects under the action of an unbalanced force , 2006 .

[5]  Jose Mathew,et al.  A theoretical model to predict the effect of localized defect on vibrations associated with ball bearing , 2010 .

[6]  Y. Ueno,et al.  Prediction of spalling on a ball bearing by applying the discrete wavelet transform to vibration signals , 1996 .

[7]  Ramchandra Ganapati Desavale Dynamics Characteristics and Diagnosis of a Rotor-Bearing's System Through a Dimensional Analysis Approach: An Experimental Study , 2019 .

[8]  N. Tandon,et al.  Vibration Response of Rolling Element Bearings in a Rotor Bearing System to a Local Defect Under Radial Load , 2006 .

[9]  Xi Zhang,et al.  Mechanical analysis of spherical roller bearings due to misalignments between inner and outer rings , 2017 .

[10]  Hao Wu,et al.  Vibration analysis on the rolling element bearing-rotor system of an air blower , 2012 .

[12]  A. Mohanty,et al.  APPLICATION OF DISCRETE WAVELET TRANSFORM FOR DETECTION OF BALL BEARING RACE FAULTS , 2002 .

[13]  N. Tandon,et al.  A theoretical model to predict the vibration response of rolling bearings in a rotor bearing system to distributed defects under radial load , 2000 .

[14]  Aki Mikkola,et al.  Simple and Versatile Dynamic Model of Spherical Roller Bearing , 2013 .

[15]  Aki Mikkola,et al.  Modeling and Dynamic Analysis of Spherical Roller Bearing with Localized Defects: Analytical Formulation to Calculate Defect Depth and Stiffness , 2016 .

[16]  N. Tandon,et al.  A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings , 1999 .

[17]  Hamid Moeenfard,et al.  Nonlinear dynamic modeling of surface defects in rolling element bearing systems , 2009 .

[18]  David,et al.  A New Model for Estimating Vibrations Generated in the Defective Rolling Element Bearings of the vibration response due to defects on rolling element bearings requires , 2011 .

[19]  S. Harsha,et al.  Non-linear dynamic behaviors of rolling element bearings due to surface waviness , 2004 .

[20]  M. Pacas,et al.  Rolling Bearing Condition Monitoring Based on Frequency Response Analysis , 2007, 2007 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[21]  V. N. Patel,et al.  A Dynamic Model for Vibration Studies of Deep Groove Ball Bearings Considering Single and Multiple Defects in Races , 2010 .

[22]  V. Purushotham,et al.  Multi-fault diagnosis of rolling bearing elements using wavelet analysis and hidden Markov model based fault recognition , 2005 .

[23]  P. D. McFadden,et al.  Vibration monitoring of rolling element bearings by the high-frequency resonance technique — a review , 1984 .

[24]  Nizami Aktürk,et al.  An Investigation of Rolling Element Vibrations Caused by Local Defects , 2008 .

[25]  P. D. McFadden,et al.  Model for the vibration produced by a single point defect in a rolling element bearing , 1984 .

[26]  B. C. Nakra,et al.  Detection of defects in rolling element bearings by vibration monitoring , 1993 .

[27]  Minel J. Braun,et al.  Vibration Monitoring and Damage Quantification of Faulty Ball Bearings , 2005 .

[28]  Giorgio Dalpiaz,et al.  Effectiveness and Sensitivity of Vibration Processing Techniques for Local Fault Detection in Gears , 2000 .

[29]  Giovanni Miragliotta,et al.  Physics for Managers? The power of Dimensional Analysis in production systems design , 2011 .