Journal ArticleDOI
Monitoring of induction motor load by neural network techniques
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TLDR
In this paper, the effect of different load anomalies on current spectrum, in comparison with other machine problems like rotor asymmetries, are investigated, and a neural network approach can help the torque pattern recognition, improving the interpretation of machine anomalies effects.Abstract:
This paper deals with the electric tracing of the load variation of an induction machine supplied by the mains. A load problem, like a torque dip, affects the machine supply current and consequently it should be possible to use the current pattern to detect features of the torque pattern, using the machine itself as a torque sensor. But current signature depends on many phenomena and misunderstandings are possible. At first the effect of different load anomalies on current spectrum, in comparison with other machine problems like rotor asymmetries, are investigated. Reference is made to low frequency torque disturbances, which cause a quasistationary machine behavior. Simplified relationships, validated by simulation results and by experimental results, are developed to address the current spectrum features. In order to detect on-line anomalies, a current signature extraction is performed by the time-frequency spectrum approach. This method allows the detection of random faults as well. Finally it is shown that a neural network approach can help the torque pattern recognition, improving the interpretation of machine anomalies effects.read more
Citations
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Journal ArticleDOI
Advances in Diagnostic Techniques for Induction Machines
TL;DR: This paper investigates diagnostic techniques for electrical machines with special reference to induction machines and to papers published in the last ten years, and research activities are classified into four main topics.
Journal ArticleDOI
Recent developments of induction motor drives fault diagnosis using AI techniques
TL;DR: A review of the developments in the field of diagnosis of electrical machines and drives based on artificial intelligence (AI) covers the application of expert systems, artificial neural networks (ANNs), and fuzzy logic systems that can be integrated into each other and also with more traditional techniques.
Journal ArticleDOI
Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring
TL;DR: New models for the influence of rolling-element bearing faults on induction motor stator current are described, based on two effects of a bearing fault: the introduction of a particular radial rotor movement and load torque variations caused by the bearing fault.
Journal ArticleDOI
Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: A Critical Comparison
TL;DR: In this paper, a simple and effective signal processing technique for both current and vibration signals, and a theoretical analysis of the physical link between faults, modeled as a torque disturbance, and current components, are presented.
Proceedings ArticleDOI
Diagnosis of Bearing Faults of Induction Machines by Vibration or Current Signals: A Critical Comparison
TL;DR: The focus of the paper is on the theoretical development of the correlation between torque disturbances and the amplitude of the current components, together with a review of fault models used in the literature.
References
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Book
Self Organization And Associative Memory
TL;DR: The purpose and nature of Biological Memory, as well as some of the aspects of Memory Aspects, are explained.
Journal ArticleDOI
AI techniques in induction machines diagnosis including the speed ripple effect
TL;DR: Various applications of artificial intelligence (AI) techniques (expert systems, neural networks, and fuzzy logic) presented in the literature prove that such technologies are well suited to cope with on-line diagnostic tasks for induction machines.
Journal ArticleDOI
Monitoring of defects in induction motors through air-gap torque observation
TL;DR: In this article, the authors proposed a method to monitor defects such as cracked rotor bars and shorted stator coils in induction motors by measuring air-gap torque while the motor is running.
Journal ArticleDOI
Neural networks aided on-line diagnostics of induction motor rotor faults
TL;DR: In this article, an improvement of induction-machine rotor fault diagnosis based on a neural network approach is presented, which replaces the formulation of a trigger threshold, required in the diagnostic procedure based on the machine models.
Proceedings ArticleDOI
Evaluation and implementation of a system to eliminate arbitrary load effects in current-based monitoring of induction machines
R.R. Schoen,Thomas G. Habetler +1 more
TL;DR: In this paper, the authors present a method for removing the load effects from the monitored quantity of the machine, which is accomplished by comparing the actual stator current to a model reference value which includes the load effect.