A review of induction motor fault modeling

Singh, Arvind; Grant, Bevon; DeFour, Ronald; Sharma, Chandrabhan; Bahadoorsingh, S.

doi:10.1016/j.epsr.2015.12.017

Cited by 67 publications

(38 citation statements)

References 42 publications

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“…Khan et al [21] presented a multilevel design optimization framework to improve the efficiency of the proposed method by combining it with several techniques, such as design of experiments and approximate models.The electromagnetic vibration of electrical machines has always been a hot topic in the mechanical discipline and electrical discipline fields, and there exist rich research results. The existing reviews Energies 2018, 11, 1779 3 of 33 of electromagnetic vibration are basically summarized from the view of fault diagnosis [22][23][24][25][26][27], and summaries from the perspective of dynamics are rather insufficient. With the continuous progress of research, some new technologies and methods are emerging.…”

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confidence: 99%

Review of Electromagnetic Vibration in Electrical Machines

Han

Chu

2018

Energies

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Electrical machines are important devices that convert electric energy into mechanical work and are widely used in industry and people's life. Undesired vibrations are harmful to their safe operation. Reviews from the viewpoint of fault diagnosis have been conducted, while summaries from the perspective of dynamics is rare. This review provides systematic research outlines of this field, which can help a majority of scholars grasp the ongoing progress and conduct further investigations. This review mainly generalizes publications in the past decades about the dynamics and vibration of electrical machines. First the sources of electromagnetic vibration in electrical machines are presented, which include mechanical and electromagnetic factors. Different types of air gap eccentricity are introduced and modeled. The analytical methods and numerical methods for calculating the electromagnetic force are summarized and explained in detail. The exact subdomain analysis, magnetic equivalent circuit, Maxwell stress tensor, winding function approach, conformal mapping method, virtual work principle and finite element analysis are presented. The effects of magnetic saturation, slot and pole combination and load are discussed. Then typical characteristics of electromagnetic vibration are illustrated. Finally, the experimental studies are summarized and the authors give their thoughts about the research trends.Energies 2018, 11, 1779 2 of 33 vibration mechanism can be helpful for the design of electrical machines. Therefore, the study of the electromagnetic vibration of electrical machines has practical significance.Electromagnetic vibrations are usually generated by the distorted air-gap field of an eccentric rotor in electrical machines. The uneven air-gap is directly related to the eccentricity, which is common in rotating electrical machines. Eccentricity can be caused by several reasons, such as relative misalignment of the rotor and stator in the fixing stage, misalignment of the load axis and rotor shaft, elliptical stator inner cross section, wrong placement or rubbing of ball bearings, mechanical resonance, and unbalanced loads [1,2]. Eccentricities can be further subdivided into two categories: circumferential unequal air gaps and axial unequal air gaps. The former can be grouped into static eccentricity and dynamic eccentricity. In the case of static eccentricity, the rotor rotates around its own geometric axis, which is not the geometric axis of the stator. In the case of dynamic eccentricity, the rotor is not concentric and rotates around the geometric axis of the stator. In reality, both static eccentricity and dynamic eccentricity tend to coexist. An inherent static eccentricity exists, even in newly manufactured machines, due to the build-up of tolerances during the manufacturing and assembly procedure, as has been reported in [3]. Unequal air gaps cause unbalanced magnetic forces (UMFs) [4] on the rotor, which lead to mechanical stress on some part of the shaft and bearing. After prolonged operation, these fac...

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confidence: 99%

Review of Electromagnetic Vibration in Electrical Machines

Han

Chu

2018

Energies

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“…In recent years, the development of monitoring systems to assess the physical condition of rotatory machinery has been vital to guaranteeing the reliability of industrial processes [1][2][3]. Among the rotatory machinery, the three-phase induction motor (IM), representing~85% of the consumed power in the industry, is a default implementation in industrial processes [4] because it offers great benefits, such as low maintenance, low cost, high robustness to aggressive environments and easy control under different load conditions [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Among the rotatory machinery, the three-phase induction motor (IM), representing~85% of the consumed power in the industry, is a default implementation in industrial processes [4] because it offers great benefits, such as low maintenance, low cost, high robustness to aggressive environments and easy control under different load conditions [5,6]. Despite these great benefits, IMs are susceptible to present electrical and mechanical faults during their service-life, which are produced mainly by power quality problems, prolonged activity times and harsh operating conditions, among other factors [1][2][3]5,6]. Regarding electrical faults, stator winding faults (SWFs) are one of the most dangerous and common faults in IMs [7], representing about a 36-38% of faults that can take place [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…The obtained results demonstrate the effectiveness of the proposal, i.e., the SE index quantifies the fault severity, regardless of the mechanical load, and the proposed FL system achieves a positive classification rate of 98%.During the last 15 years, an important number of techniques and methodologies for SWF detection using the analysis of acoustic, current and vibration signals have been proposed [10][11][12][13][14]. Motor current signature analysis (MCSA) is one of the most used methods because of its advantages, such as possessing a non-invasive capacity, possible remote sensing, easy implementation and low implementation costs [2,9]. MCSA is mainly used to identify faults in the IM according to the analysis of frequency components found in the measured signal.…”

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Shannon Entropy Index and a Fuzzy Logic System for the Assessment of Stator Winding Short-Circuit Faults in Induction Motors

et al. 2019

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The induction motor (IM) is one of the most important elements in industry. Although IMs are robust machines, they are susceptible to faults, where the stator winding short-circuit fault is one of the most common ones. In this work, the Shannon entropy (SE) index and a fuzzy logic (FL) system are proposed to diagnose short-circuit faults, considering both different severity levels and different load conditions. In the proposed methodology, a filtering stage based on brick-wall band-pass filters is firstly carried out. After this stage, the SE index is computed to quantify the fault severity and a FL system is applied to diagnose the IM condition in an automatic way. Unlike other works that propose some types of space transformations, the proposal is only based on a filtering stage and a time domain index, requiring low computational resources. The obtained results demonstrate the effectiveness of the proposal, i.e., the SE index quantifies the fault severity, regardless of the mechanical load, and the proposed FL system achieves a positive classification rate of 98%.

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“…The presence of a broken bar in the cage rotor produces a geometric and electromagnetic asymmetry in the rotor circuit, and induced currents are created in direct rotating field, another field is turning around [6].…”

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confidence: 99%

Diagnosis of rotor fault using neuro-fuzzy inference system

Merabet¹,

Bahi²,

Drici³

et al. 2017

J. Fundam and Appl Sci.

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The three-phase induction machines (IM) is large importance and are being widely used as electromechanical system device regarding for their robustness, reliability, and simple design with well developed technologies. This work presents a reliable method for diagnosis and detection of rotor broken bars faults in induction machine. The detection faults are based on monitoring of the current signal. Also the calculation of the value of relative energy for each level of signal decomposition using package wavelet, which will be useful as data input of adaptive Neuro-Fuzzy inference system (ANFIS).In this method, fuzzy logic is used to make decisions about the machine state. The adaptive Neuro-Fuzzy inference system is able to identify the IM bearing state with high precision.This technique is applied under the MATLAB ® .

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A review of induction motor fault modeling

Cited by 67 publications

References 42 publications

Review of Electromagnetic Vibration in Electrical Machines

Review of Electromagnetic Vibration in Electrical Machines

Shannon Entropy Index and a Fuzzy Logic System for the Assessment of Stator Winding Short-Circuit Faults in Induction Motors

Diagnosis of rotor fault using neuro-fuzzy inference system

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