A novel methodology for fault size estimation of ball bearings using stator current signal

Abstract Bearing fault diagnosis that utilizes motor current has shown great potential for industrial application. For estimating fault sizes, this paper develop an electromechanical-magnetic coupling computational model of induction motor (IM) based on modified winding function approach (MWFA) in order to extract the fault-excited harmonic components and amplitudes in stator current. A new evaluating indicator FHD (Fault-excited Harmonic Distortion) is then proposed to describe the specific relation between fault sizes and severity of fault-excited harmonic distortion. The statistical results show that there is a fixed functional relation curve between FHD and fault sizes in different IM. Finally, an experimental IM with a known size built-in faulted bearing is investigated. The 1 mm artificial damage on outer raceway is recognized by calculating FHD (0.5636 in average) value and comparing with the simulated relation curve. The results validate the accuracy and robustness of the proposed approach in fault size estimation.

[1]  Adel Ghoggal,et al.  Transient and steady‐state modelling of healthy and eccentric induction motors considering the main and third harmonic saturation factors , 2019, IET Electric Power Applications.

[2]  Anas Sakout,et al.  Single point bearing fault diagnosis using simplified frequency model , 2017 .

[3]  T.A. Lipo,et al.  Modelling of saturated AC machines including air gap flux harmonic components , 1990, Conference Record of the 1990 IEEE Industry Applications Society Annual Meeting.

[4]  Sukhjeet Singh,et al.  Detection of Bearing Faults in Mechanical Systems Using Stator Current Monitoring , 2017, IEEE Transactions on Industrial Informatics.

[5]  Zhaoheng Liu,et al.  A new approach based on OMA-empirical wavelet transforms for bearing fault diagnosis , 2016 .

[6]  Myeongsu Kang,et al.  Detection of Generalized-Roughness and Single-Point Bearing Faults Using Linear Prediction-Based Current Noise Cancellation , 2018, IEEE Transactions on Industrial Electronics.

[7]  Zhihao Liu,et al.  Application of Multi-Dimension Input Convolutional Neural Network in Fault Diagnosis of Rolling Bearings , 2019, Applied Sciences.

[8]  Lin Liang,et al.  Quantitative diagnosis of a spall-like fault of a rolling element bearing by empirical mode decomposition and the approximate entropy method , 2013 .

[9]  Qinkai Han,et al.  Nonlinear dynamic modeling of rotor system supported by angular contact ball bearings , 2017 .

[10]  Adam Glowacz,et al.  Early fault diagnosis of bearing and stator faults of the single-phase induction motor using acoustic signals , 2018 .

[11]  Hamid A. Toliyat,et al.  Transient analysis of cage induction machines under stator, rotor bar and end ring faults , 1995 .

[12]  Khanh T.P. Nguyen,et al.  Health monitoring of bearing and gear faults by using a new health indicator extracted from current signals , 2019, Measurement.

[13]  Thomas A. Lipo,et al.  Analysis of Synchronous Machines , 2008 .

[14]  H. Toliyat,et al.  Effect of Magnetic Saturation on Static and Mixed Eccentricity Fault Diagnosis in Induction Motor , 2009, IEEE Transactions on Magnetics.

[15]  Jan Desmet,et al.  The reflection of evolving bearing faults in the stator current’s extended park vector approach for induction machines , 2018, Mechanical Systems and Signal Processing.

[16]  H. W. Ngan,et al.  Detection of Motor Bearing Outer Raceway Defect by Wavelet Packet Transformed Motor Current Signature Analysis , 2010, IEEE Transactions on Instrumentation and Measurement.

[17]  Robert B. Randall,et al.  A comparison of methods for separation of deterministic and random signals , 2011 .

[18]  Zheng Chen,et al.  A new diagnosis of broken rotor bar fault extent in three phase squirrel cage induction motor , 2014 .

[19]  Jawad Faiz,et al.  An evaluation of inductances of a squirrel-cage induction motor under mixed eccentric conditions , 2003 .

[20]  Guolin He,et al.  Non-stationary vibration feature extraction method based on sparse decomposition and order tracking for gearbox fault diagnosis , 2018 .

[21]  Jawad Faiz,et al.  Estimation of induction machine inductances using three-dimensional magnetic equivalent circuit , 2015 .

[22]  Fardin Dalvand,et al.  A Novel Bearing Condition Monitoring Method in Induction Motors Based on Instantaneous Frequency of Motor Voltage , 2016, IEEE Transactions on Industrial Electronics.

[23]  Stefan Ericsson,et al.  Towards automatic detection of local bearing defects in rotating machines , 2005 .

[24]  Jianfeng Ma,et al.  Quantitative trend fault diagnosis of a rolling bearing based on Sparsogram and Lempel-Ziv , 2018, Measurement.

[25]  Fanrang Kong,et al.  Multiscale slope feature extraction for rotating machinery fault diagnosis using wavelet analysis , 2013 .

[26]  Zhengjia He,et al.  Wheel-bearing fault diagnosis of trains using empirical wavelet transform , 2016 .

[27]  Xiaofeng Liu,et al.  Bearing faults diagnostics based on hybrid LS-SVM and EMD method , 2015 .

[28]  Hubert Razik,et al.  An improved model of induction motors for diagnosis purposes – Slot skewing effect and air–gap eccentricity faults , 2009 .

[29]  A.M. Knight,et al.  Mechanical fault detection in a medium-sized induction motor using stator current monitoring , 2005, IEEE Transactions on Energy Conversion.

[30]  Robert B. Randall,et al.  Unsupervised noise cancellation for vibration signals: part II—a novel frequency-domain algorithm , 2004 .

[31]  Wei Zhou,et al.  Bearing Fault Detection Via Stator Current Noise Cancellation and Statistical Control , 2008, IEEE Transactions on Industrial Electronics.

[32]  T.G. Habetler,et al.  Incipient Bearing Fault Detection via Motor Stator Current Noise Cancellation Using Wiener Filter , 2009, IEEE Transactions on Industry Applications.

[33]  Robert B. Randall,et al.  Rolling element bearing diagnostics—A tutorial , 2011 .

[34]  T. Hamiti,et al.  Comparison Between Finite-Element Analysis and Winding Function Theory for Inductances and Torque Calculation of a Synchronous Reluctance Machine , 2007, IEEE Transactions on Magnetics.

[35]  Marco Cocconcelli,et al.  Experimental Investigation of Shaft Radial Load Effect on Bearing Fault Signatures Detection , 2017, IEEE Transactions on Industry Applications.

[36]  Yonghao Miao,et al.  Detection and recovery of fault impulses via improved harmonic product spectrum and its application in defect size estimation of train bearings , 2016 .

[37]  M. Sahraoui,et al.  A winding function-based model of air-gap eccentricity in saturated induction motors , 2012, 2012 XXth International Conference on Electrical Machines.

[38]  Amir Akbari,et al.  A method based on spindle motor current harmonic distortion measurements for tool wear monitoring , 2017 .

[39]  Bertrand Raison,et al.  Models for bearing damage detection in induction motors using stator current monitoring , 2008, 2004 IEEE International Symposium on Industrial Electronics.

[40]  Ying Zhang,et al.  Classification of fault location and performance degradation of a roller bearing , 2013 .

[41]  N. Sadowski,et al.  Study of Static and Dynamic Eccentricities of a Synchronous Generator Using 3-D FEM , 2010, IEEE Transactions on Magnetics.

[42]  Hamid A. Toliyat,et al.  A novel method for modeling dynamic air-gap eccentricity in synchronous machines based on modified winding function theory , 1998 .

[43]  Na Wu,et al.  Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary , 2016 .

[44]  Peyman Naderi,et al.  Modified magnetic-equivalent-circuit approach for various faults studying in saturable double-cage-induction machines , 2017 .

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