Journal of Signal and Information Processing, 2013, 4, 72-79 doi:10.4236/jsip.201343B013 Published Online August 2013 (http://www.scirp.org/journal/jsip) A Study of Motor Bearing Fault Diagnosis using Modulation Signal Bispectrum Analysis of Motor Current Signals Ahmed Alwodai 1 , Tie Wang 2 , Zhi Chen 2 , Fengshou Gu 1 , Robert Cattley 1 , Andrew Ball 1 1 Centre for Efficiency and Performance Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK; 2 Department of Vehicle Engineering, Taiyuan University of Technology Taiyuan, Shanxi Province, China Email: F.gu@hud.ac.uk Received April, 2013. ABSTRACT 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 race fault and inner race fault. Because the signals associated with faults produce small modulations to supply component and high nose levels, a modulation signal bispectrum (MSB) is used in this paper to detect and diagnose different motor bearing defects. The results show that bearing faults can induced a detest- able amplitude increases at its characteristic frequencies. MSB peaks show a clear difference at these frequencies whe- reas conventional power spectrum provides change evidences only at some of the frequencies. This shows that MSB has a better and reliable performance in extract small changes from the faulty bearing for fault detection and diagnosis. In addition, the study also show that current signals from motors with variable frequency drive controller have too much noise and it is unlikely to discriminate the small bearing fault component. Keywords: Induction Motor; Motor Current Signature; Power Spectrum Bispectrum; Motor Bearing 1. Introduction A general review of monitoring and fault diagnosis tech- niques are studied in [1, 2]. The different faults in an electrical machine can be classified as follows [3]: Figure 1. Components of the rolling ball bearing.  Stator faults, for example, short circuit, loss of a sup- ply phase.  Rotor faults, for example, broken bar, broken end- ring.  Static and dynamic eccentricities.  Bearing faults. Studies have shown that the common faults in induc- tion motors (about 40%–50%) happen in rolling bearings, depending on the type of installation, the motor size, and the supply voltage [4]. In general it is due to manufac- turing faults, lack of lubrication, installation errors and wear and tear. According to the affected elements, shown in Figure 1, bearing faults can be classified as inner ring, outer ring, ball element and cage faults. The inner ring is mounted on the shaft of the machine and is usually the rotating part whereas the outer ring is fixed in the housing of the machine and in most cases it does not rotate. The rolling elements may be balls, cylin- drical rollers, spherical rollers, tapered rollers or needle rollers. They rotate against the inner and outer ring race- ways and transmit the load acting on the bearing via small surface contacts separated by a thin lubricating film. The cage separates the rolling elements to prevent metal-to-metal contact between them during operation. Seals are important for protection of bearing from con- tamination and keep the lubricant inside the bearing sur- Copyright © 2013 SciRes. JSIP