Model‐based exact technique to identify type and degree of eccentricity faults in induction motors

Abstract

In spite of numerous research activities performed so far, determination of type and exact degree of the eccentricity faults in induction motors is challenging yet. This study presents a model-based fault diagnosis technique for identifying all the three eccentricity fault types, including static, dynamic and mixed eccentricities, with their exact degrees in the mentioned motors. This technique uses a special analytic model prepared for simulating squirrel-cage induction motors under healthy and all eccentricity fault conditions as well as the particle swarm optimisation method. Correct performance and effectiveness of the proposed technique is verified by using simulation and experiments. Finally, an algorithm is introduced for the eccentricity fault treatment using the identified degrees of the fault components and their time trends.

Partial Inductance Model of Induction Machines for Fault Diagnosis

“…Some of these assumptions can be removed by using a modified inverse air-gap function which takes into account the saturation [ 55 ], the rotor eccentricity [ 30 ], or the slotting effects [ 69 ]. Nevertheless, as the focus of this paper is the introduction of the partial inductance model of the IM, a constant air-gap has been used to present the proposed approach, applied to the simulation and experimental test of an IM with a rotor asymmetry (broken bars fault), the same fault analyzed in [ 11 , 12 , 14 , 15 , 56 ], among many others.…”

“…Commonly, fault diagnostic systems that are based on the analysis of the current signal, such as MCSA, try to measure the amplitude of the harmonic components with frequencies given by Equations ( 1 )–( 4 ) in the spectrum of the stator current. These values are then compared with predefined threshold alarms, in data based diagnostic systems [ 5 ], or with the output of machine models, in model based diagnostic systems [ 5 , 20 , 29 , 30 , 31 ]. In both cases, accurate machine models are needed, for fixing the values of the threshold alarms, for running the model-based fault diagnostic system [ 32 ], or for developing new diagnostic algorithms [ 33 ].…”

Induction Motors Condition Monitoring System with Fault Diagnosis Using a Hybrid Approach

“…The study develops condition monitoring with fault diagnosis embedded system in the front end. studies focused on the relatively more common eccentricity problems, which were examined in References [19][20][21][22]. Recently, a motor diagnosis manner was generally used in industries, which is called time-based maintenance (TBM) [23].…”

“…Bearing breakdowns have been investigated using the root-multiple signal classification method and neural networks [17,18]. As for breakdowns in other components, recent studies focused on the relatively more common eccentricity problems, which were examined in References [19][20][21][22].…”

Induction Motor Broken Rotor Bar Detection Based on Rotor Flux Angle Monitoring

“…Nowadays, more and more industrial electrical drives tend to be supervised by such techniques [7]. Among possible IM faults, researchers mostly deal with stator winding faults [8][9][10], or different mechanical faults [11] like bearing faults [12,13], rotor eccentricities [14,15], and rotor electrical asymmetry due to broken rotor bars (BRB) or end-ring segments [16,17]. Some of the methods could also be used for the detection of mixed faults [18,19].…”