Armature Fault Diagnostics of a Commutator Motor using the Frequency Response Analysis

Retana, R.; Pavveletz, A.; Herzog, Hans Georg

doi:10.1109/demped.2007.4393108

Cited by 1 publication

(2 citation statements)

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“…Some papers applied neural networks or fuzzy inference systems as a classification method. [22] suggests replacing the surge test for armature fault identifications with the frequency response analysis method of the DC machine's impedance. Analyzing the impedance curve for all bars and frequencies, they realized that the faulty and healthy curves for the armature circuit presented some differences.…”

Section: Armature Faults Inspection Problemmentioning

confidence: 99%

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Armature fault diagnosis of universal motors using time-series data in neural networks

Silva,

Bertol

2023

Anais Do XVI Congresso Brasileiro De Inteligência Computacional

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A common issue of DC and universal motors is the quality of the armature circuit and the commutation process. Some faults that could happen during the final assembly process, such as a short circuit between two segments or a broken segment in the armatures commutator, may not be detected by a visual inspection or the regular no-load end-of-line test. A more detailed analysis, using the feedback of various auxiliary sensors, usually requires implementing systems with more complex and expensive hardware. It also may take longer to get a precise analysis, which may not be suitable for the production process. As a method to do a fast and accurate detection and classification of faults in the armatures circuit of universal motors, this paper suggests the analysis of the armature voltage and current waveform by an artificial neural network (ANN). The current and voltage signals acquired during the no-load test formed a time-series waveform that was applied to an ANN trained to classify the signal in three possible outcomes: healthy armature, armature with shortcircuited segments, and armature with a broken part. The results achieve effectiveness above 98% in the task of detection and classification of faults. The solution was tested in the production line of universal motors and proved to be fast, reliable, and efficient for the usual no-load test, proving to be suitable in an industrial context.

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Section: Armature Faults Inspection Problemmentioning

confidence: 99%

“…Many approaches have been developed through the years for the monitoring, detection, and identification of faults in the armature circuit [4], [7], [8], [12]- [16], [18], [20]- [22], [24], [29], [30].…”

Section: Introductionmentioning

confidence: 99%

Armature fault diagnosis of universal motors using time-series data in neural networks

Silva,

Bertol

2023

Anais Do XVI Congresso Brasileiro De Inteligência Computacional

View full text Add to dashboard Cite

show abstract

Armature Fault Diagnostics of a Commutator Motor using the Frequency Response Analysis

Abstract: Small commutator motors have much wider parameterAbstract--A diagnostic method for armatures of commutator tolerances than middle and large machines because the

Cited by 1 publication

References 2 publications

Armature fault diagnosis of universal motors using time-series data in neural networks

Armature fault diagnosis of universal motors using time-series data in neural networks

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