Current monitoring for detecting inter-turn short circuits in induction motors

Stavrou, Andréas; Sedding, H.G.; Penman, J.

doi:10.1109/iemdc.1999.769110

Cited by 34 publications

(20 citation statements)

References 13 publications

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“…MCSA focuses its efforts on the spectral analysis of stator current. A few MCSA-based techniques for inter-turn stator fault detection have been reported [24]- [27]. Both low and high-frequency components, almost similar to those observed with eccentricity-related faults, are shown to be present.…”

Section: Higher Order Statisticsmentioning

confidence: 71%

Non-invasive on-line detection of winding faults in induction motors—A review

Behbahanifard

Karshenas

Sadoughi

2008

2008 International Conference on Condition Monitoring and Diagnosis

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This paper is a review and evaluation of different on-line methods for diagnosing winding fault in induction motors presented in literature. Many methods can be found in literature; in some references, frequency analysis of motor signals such as current , speed, instantaneous power , Park's vector modulus and so on are introduced. Evaluation of negative sequence of current is also among the proposed methods. Supply voltage unbalance and some other phenomena may be confused with the winding fault. Therefore, the monitoring and fault detection of electrical machines have moved in recent years from traditional techniques to artificial intelligence based techniques. There are many other techniques that will be introduced and investigated in the detailed paper. A comparison of Different methods introduced in literature is the main objective of this paper.

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Section: Higher Order Statisticsmentioning

confidence: 71%

Non-invasive on-line detection of winding faults in induction motors—A review

Behbahanifard

Karshenas

Sadoughi

2008

2008 International Conference on Condition Monitoring and Diagnosis

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“…The all stages of feature extraction are realized in Altera Quartus II 9.1 software environment [6]. A window size should be determined to calculate the magnitude of each phase current.…”

Section: A Fpga Implementation Of the Feature Extractionmentioning

confidence: 99%

A fast fuzzy stator condition monitoring algorithm using FPGA

2011

2011 IEEE 3rd International Conference on Communication Software and Networks

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This paper presents a new methodology for realtime detection of stator faults in induction motors. It is based on the evaluation of the magnitudes of three phase current signals. The severity of fault is indicated by designed fuzzy system. The algorithm consists of two stages: feature extraction and classification. All acquired current signals are based on IEEE-754 single precision floating point format. In the feature extraction stage, floating point based features were obtained and then converted to the integer format. In the classification stage, all coding are written in VHDL using integer data type format. The proposed method classifies the stator related faults at higher level speed with better accuracy than conventional offline method. This is the first time that FPGA based fuzzy system has been employed to induction motor faults. With the proposed method, it is clearly identified the motor condition as either healthy or damaged, allowing one to perform a simple real time detection. A light computation load is required in order to perform the calculation of the algorithm. In addition, the implemented FPGA design allows the system reconfiguration to attain specific measurement conditions on different types of motors without hardware modifications.

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“…Most of these techniques are only valid for line fed motors or open-loop AC motor-drive systems [1][2][3][4][5][6][7][8]. The main objective of this paper is to extend the application of the socalled magnetic field pendulous oscillation phenomenon, which has been introduced and utilized for the diagnosing of inter-turn short circuit faults in open-loop drives and line-fed induction machines in [5], to the case involving closed-loop vector-controlled drives.…”

Section: Introductionmentioning

confidence: 98%

“…Meanwhile, motor and drive fault diagnostics have become a major concern from the industrial point of view, particularly in critical applications where motor-drive failure can be costly, catastrophic or life threatening. This remains the major incentive for a considerable amount of research in the area of motor-drive system fault diagnostics [1][2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of Inter-Turn Short Circuit for a Polyphase Induction Motor in Closed-Loop Vector-Controlled Drives

Sayed-Ahmed

Sizov

Demerdash

2007

2007 IEEE Industry Applications Annual Meeting

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The main objective of this paper is to develop and experimentally verify a new technique to detect an inter-turn short circuit in one phase of a stator winding of an induction motor energized from a vector-controlled drive. This is in order to overcome the fault masking difficulties associated with the concept of depending on the actual magnetic field pendulous oscillation between the conventional voltage and current space vectors with respect to a reference that is unaltered by the compensation action of the drive. This technique is based on the flux pendulous oscillation phenomenon. This flux pendulous oscillation is also described in this paper, this in addition to the magnetic field pendulous oscillation previously addressed in prior publications. The new approach has been verified through experimental results which are represented here.Index Terms-magnetic field pendulous oscillation, flux pendulous oscillation, stator fault diagnostics, inter-turn shorts, induction motor winding faults, closed-loop adjustable speed drives.

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Current monitoring for detecting inter-turn short circuits in induction motors

Cited by 34 publications

References 13 publications

Non-invasive on-line detection of winding faults in induction motors—A review

Non-invasive on-line detection of winding faults in induction motors—A review

A fast fuzzy stator condition monitoring algorithm using FPGA

Diagnosis of Inter-Turn Short Circuit for a Polyphase Induction Motor in Closed-Loop Vector-Controlled Drives

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Current monitoring for detecting inter-turn short circuits in induction motors

Cited by 34 publications

References 13 publications

Non-invasive on-line detection of winding faults in induction motors&#x2014;A review

Non-invasive on-line detection of winding faults in induction motors&#x2014;A review

A fast fuzzy stator condition monitoring algorithm using FPGA

Diagnosis of Inter-Turn Short Circuit for a Polyphase Induction Motor in Closed-Loop Vector-Controlled Drives

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Product

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Non-invasive on-line detection of winding faults in induction motors—A review

Non-invasive on-line detection of winding faults in induction motors—A review