International Journal of Electrical & Computer Sciences IJECS-IJENS Vol:10 No:05 22 104605-9494 IJECS-IJENS © October 2010 IJENS I J E N S Abstract— The aim of this paper is to investigate and detect the multiple faults in machines using broken rotor bar and eccentricity fault frequencies techniques. It is proposed that using both current and instantaneous power signals simultaneously, will detect the multiple faults reliably, specifically using broken rotor bar fault frequencies and eccentricity fault frequencies under various load conditions. The analyses carried out in this paper show that the current spectra is able to detect multiple faults i.e. a combination of broken rotor bars and eccentricity faults either by using broken rotor bars fault frequency components (1±2s)f1 or using eccentricity fault frequency components (f1±fr) at any levels of loading. The results from the instantaneous power spectra using modified broken rotor bar fault frequency components (fp±4f2) show that it is preferable for estimating either the machines having multiple faults. It can be concluded from the results that flux signal is also not a useful source to detect multiple faults using both broken rotor bar and eccentricity fault frequency components. Index Term— Broken Rotor Bar, Eccentricity, Electric Machine, Multiple Faults. I. INTRODUCTION THE basis of any condition monitoring depends on understanding the electric, magnetic and mechanical behavior of a machine in both the healthy and faulty state [1]. An induction machine is highly symmetrical and the presence of any kind of fault modifies its symmetry and produces changes in the measured sensor signals, or more precisely, in the magnitude of certain fault frequencies [2]. In induction motor monitoring single sensor is normally used to detect a single fault. Previously, the correlation between different types of sensors and their ability to diagnose multiple faults has not been studied thoroughly enough in the literature. The most prevalent faults in machines are broken rotor bar, stator or armature, misalignment, eccentricity and bearing related faults (bearing fault can also cause rotor eccentricity [3, 4]. Therefore, characterization and accurate prediction of the 1 Dr. Intesar Ahmed, 1 Engr. Muhammad Shuja Khan and 1 Engr. Kashif Imran are with Department of Electrical Engineering, COMSATS Institute of Information Technology, Lahore PAKISTAN. (Emails: drintesarahmad@ciitlahore.edu.pk, shuja@ciitlahore.edu.pk, kashifimranciitlahore.edu.pk). 2 Engr. Manzar Ahmed is with Department of Electrical Engineering, University of South Asia, Lahore PAKISTAN. performance degradation for the induction machine under such conditions is of considerable importance. However, the technology in this field is still in permanent evolution and new techniques appear every year. The purpose of this trend is to be more efficient in fault detection and to provide a reliable method with low-cost sensors and simple numerical algorithms. It is the reason why most international conferences dedicated to electrical machines make room for sessions on monitoring and diagnosis. Condition monitoring of induction machines relies on being able to detect differences between healthy and faulty machines. An accurate interpretation of a motor’s condition requires knowledge of the effects of different operating conditions (including level of loading, non-ideal supplies), and typical variability between machines and test repeatability. The localized heating caused by the fault will gradually result in further insulation damage until the motor fails. It is useful to be able to detect such faults at an early stage so that a pre- planned shutdown can be arranged for the motor to be replaced by a healthy motor. Various causes of stator and rotor failures have been presented and discussed in detail. A specific methodology is proposed to facilitate an accurate analysis of these failures [5]. Although, condition monitoring is normally done for induction motors [6], and it can also be carried out for induction generators as-well [7]. A comprehensive literature review of more than 20 existing methods, including the most common methods to assess the phase-to-ground, phase-to-phase, and turn-to-turn insulation conditions are presented in [8 - 11]. The use of fault frequency components in the current, flux and vibration sensor signals to try to both detect and estimate the severity of static eccentricity faults in the presence of load variations and the detection of Eccentricity Fault in machine have been reported in [12, 13]. The purpose of this paper is to investigate fault frequencies in motors with multiple faults to be able to detect and to uncover the most prevalent that may occur in machines. The airgap between the rotor and stator of a healthy motor (2kW) used in this study is 0.4 mm (each side). Therefore, airgap of ±1, ±2 and ±3 mm at the driving and at non-driving-end are considered for the experiment. The investigation of multiple faults (combination of broken rotor bars and eccentricity faults) at different levels of loading will be involving the following: Investigation of Multiple Faults Detection in Electric Machine Using Broken Rotor Bar and Eccentricity Fault Frequencies Techniques Intesar Ahmed 1 , Manzar Ahmed 2 , M. Shuja Khan 1 , Kashif Imran 1