| 1. |
- Karvelis, Petros, et al.
(författare)
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A Symbolic Representation Approach for the Diagnosis of Broken Rotor Bars in Induction Motors
- 2015
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 11:5, s. 1028-1037
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Tidskriftsartikel (refereegranskat)abstract
- One of the most common deficiencies of currently existing induction motor fault diagnosis techniques is their lack of automatization. Many of them rely on the qualitative interpretation of the results, a fact that requires significant user expertise, and that makes their implementation in portable condition monitoring devices difficult. In this paper, we present an automated method for the detection of the number of broken bars of an induction motor. The method is based on the transient analysis of the start-up current using wavelet approximation signal that isolates a characteristic component that emerges once a rotor bar is broken. After the isolation of this component, a number of stages are applied that transform the continuous-valued signal into a discrete one. Subsequently, an intelligent icon-like approach is applied for condensing the relative information into a representation that can be easily manipulated by a nearest neighbor classifier. The approach is tested using simulation as well as experimental data, achieving high-classification accuracy.
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| 2. |
- Karvelis, Petros, et al.
(författare)
-
An automated thermographic image segmentation method for induction motor fault diagnosis
- 2015
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Ingår i: IECON 2014. - Piscataway, NJ : IEEE Communications Society. - 9781479940332 ; , s. 3396-3402
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Konferensbidrag (refereegranskat)abstract
- Eventual failures in induction machines may lead to catastrophic consequences in terms of economic costs for the companies. The development of reliable systems for fault detection that enable to diagnose a wide range of faults is a motivation of many researchers worldwide. In this context, non-invasive condition monitoring strategies have drawn special attention since they do not require interfering with the operation process of the machine. Though the analysis of the motor currents has proven to be a reliable, non-invasive methodology to detect some of the faults (especially when assessing the rotor condition), it lacks reliability for the diagnosis of other faults (e.g. bearing faults). The infrared thermography has proven to be an excellent, non-invasive tool that can complement the diagnosis reached with the motor current analysis, especially for some specific faults. However, there are still some pending issues regarding its application to induction motor faults diagnosis, such as the lack of automation or the extraction of reliable fault indicators based on the infrared data. This paper proposes a methodology that intends to provide a solution to the first issue: a method based on image segmentation is employed to detect several failures in an automated way. Four specific faults are analyzed: bearing faults, fan failures, rotor bar breakages and stator unbalance. The results show the potential of the technique to automatically identify the fault present in the machine.
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| 3. |
- Karvelis, Petros, et al.
(författare)
-
Symbolic time series analysis of the soft starting transient in induction machines
- 2015
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Ingår i: 2015 IEEE International Conference on Industrial Technology (ICIT 2015) to be held in Seville, Spain, March 17-19, 2015.. - Piscataway, NJ : IEEE Communications Society. - 9781479978007 ; , s. 3243-3248
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Konferensbidrag (refereegranskat)abstract
- Induction motors are in the heart of almost every production line especially due to their robustness under harsh environments. Nevertheless, even induction machines are prone to faults. Among them, the faults related to the breakage of rotor bars have received special attention by the research community with a number of methods proposed both for the case of steady state as well as for transient operation. For the latter, methods relying on the analysis of the start-up transient have proven to be able to effectively isolate the faulty component that is created by the asymmetry caused by the bar breakage. However, very little work has been done concerning the soft starting of induction machines. In this work, preliminary results of the application of a symbolic time series technique for the analysis of the transient, when the motor is controlled by a soft starter, will be presented and experimentally evaluated.
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