Bibliography on induction motors faults detection and diagnosis

Benbouzid, Mohamed

doi:10.1109/60.815029

Cited by 191 publications

(65 citation statements)

References 164 publications

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“…Some of the technology used for monitoring includes sensors, which may measure speed, output torque, vibrations, temperature, flux densities, etc. These sensors are together coupled with algorithms and architectures, which allows for efficient monitoring of the machines condition [17]. Fig.…”

Section: A Electrical System (Dfig) Condition Monitoringmentioning

confidence: 99%

A brief status on condition monitoring and fault diagnosis in wind energy conversion systems

Amirat

Benbouzid

Al-Ahmar

et al. 2009

Renewable and Sustainable Energy Reviews

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352

192

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Section: A Electrical System (Dfig) Condition Monitoringmentioning

confidence: 99%

A brief status on condition monitoring and fault diagnosis in wind energy conversion systems

Amirat

Benbouzid

Al-Ahmar

et al. 2009

Renewable and Sustainable Energy Reviews

Self Cite

352

192

View full text Add to dashboard Cite

“…Since 20 years ago, a continue effort has been devoted to the investigation of faults of ac drives which have been reported in [3]. There are different methods for analysis of a faulty motor; however application of these methods requires revision of the proposed assumptions and basic equations.…”

Section: Introductionmentioning

confidence: 99%

Static Eccentricity Fault Diagnosis in an Accelerating No-Load Three-Phase Saturated Squirrel-Cage Induction Motor

Faiz¹,

Ebrahimi²

2008

PIER B

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Abstract-A no-load induction motor under static eccentricity is modeled using time stepping finite element (TSFE) method; current, torque, and speed signals of the motor are obtained by finite element method (FEM) and used for static eccentricity fault diagnosis and analysis. The frequency spectrum analysis of the stator current around fundamental frequency component is used to predict the static eccentricity. Noise, unbalanced magnetic pull (UMP) and arc occur during the starting of the faulty motor, therefore, performance of the motor over the period of starting up to the steady-state is investigated. It is shown that the rate of obtained signals from the constant permeability based analysis is very larger than that of the real case. It is indicated that in order to obtain accurate results the saturation must be taken into account in the analysis of the motor. Simulation results for a 3 hp, three-phase, 230 V, 36 stator slots induction motor with 28 rotor slots are given in this paper. Experimental results for the motor confirm the simulation results very well.

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“…During the past twenty years, there have been continuing efforts at studying and diagnosing of induction motor faults and associated performance characteristics [1]. As stated in [1] "performing reliable and accurate fault detection and diagnosis requires understanding the cause and effect of motor faults to motor performance." Accordingly, this paper demonstrates a method for detection of faults in induction machine adjustable speed drives (IMASDs).…”

Section: Introductionmentioning

confidence: 99%

Diagnostics of bar and end-ring connector breakage faults in polyphase induction motors through a novel dual track of time-series data mining and time-stepping coupled FE-state space modeling

Povinelli

Bangura²,

Demerdash

et al. 2002

IEEE Trans. On Energy Conversion

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Abstract-This paper develops the fundamental foundations of a technique for detection of faults in induction motors that is not based on the traditional Fourier transform frequency domain approach. The technique can extensively and economically characterize and predict faults from the induction machine adjustable speed drive design data. This is done through the development of dual-track proof-of-principle studies of fault simulation and identification. These studies are performed using our proven Time Stepping Coupled Finite Element-State Space method to generate fault case data. Then, the fault cases are classified by their inherent characteristics, so-called "signatures" or "fingerprints." These fault signatures are extracted or mined here from the fault case data using our novel Time Series Data Mining technique. The dual-track of generating fault data and mining fault signatures was tested here on three, six, and nine broken bar and broken end-ring connectors in a 208-volt, 60-Hz, 4-pole, 1.2-hp, squirrel cage 3-phase induction motor.

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Bibliography on induction motors faults detection and diagnosis

Abstract: This paper provides a comprehensive list of books, workshops, conferences, and journal papers related to induction motors faults detection and diagnosis.

Cited by 191 publications

References 164 publications

A brief status on condition monitoring and fault diagnosis in wind energy conversion systems

A brief status on condition monitoring and fault diagnosis in wind energy conversion systems

Static Eccentricity Fault Diagnosis in an Accelerating No-Load Three-Phase Saturated Squirrel-Cage Induction Motor

Diagnostics of bar and end-ring connector breakage faults in polyphase induction motors through a novel dual track of time-series data mining and time-stepping coupled FE-state space modeling

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