| 1. |
- Georgoulas, Georgios, et al.
(författare)
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Automatic pattern identification based on the complex empirical mode decomposition of the startup current for the diagnosis of rotor asymmetries in asynchronous machines
- 2014
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Ingår i: IEEE Transactions on Industrial Electronics. - : Institution of Electrical Engineers of Japan (IEEJ). - 0278-0046 .- 1557-9948. ; 61:9, s. 4937-4946
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an advanced signal processing method applied to the diagnosis of rotor asymmetries in asynchronous machines. The approach is based on the application of complex empirical mode decomposition to the measured start-up current and on the subsequent extraction of a specific complex intrinsic mode function. Unlike other approaches, the method includes a pattern recognition stage that makes possible the automatic identification of the signature caused by the fault. This automatic detection is achieved by using a reliable methodology based on hidden Markov models. Both experimental data and a hybrid simulation-experimental approach demonstrate the effectiveness of the proposed methodology
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| 4. |
- Georgoulas, Georgios, et al.
(författare)
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A Multi-label Classification Approach for the Detection of Broken Bars and Mixed Eccentricity Faults Using the Start-up Transient
- 2017
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Ingår i: IEEE International Conference on Industrial Informatics (INDIN). - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 9781509028702 ; , s. 430-433
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Konferensbidrag (refereegranskat)abstract
- In this article a data driven approach for the classification of simultaneously occurring faults in an induction motor is presented. The problem is treated as a multi-label classification problem with each label corresponding to one specific fault, using the power-set approach. The faulty conditions examined, include the existence of a broken bar fault and the presence of mixed eccentricity with various degrees of static and dynamic eccentricity. For the feature extraction stage, the time-frequency representation, resulting from the application of the short time Fourier transform of the start-up current is exploited. The proposed approach is validated using simulation data with promising results.
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| 5. |
- Georgoulas, George, et al.
(författare)
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An exploratory approach to fetal heart rate–pH-based systems
- 2021
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Ingår i: Signal, Image and Video Processing. - : Springer. - 1863-1703 .- 1863-1711. ; 15:1, s. 43-51
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an exploratory approach of the fetal heart rate (FHR) analysis, aiming to highlight potential limitations of the current predictive modeling attempts. To do so, a set of features that are usually encountered in FHR analysis as well as features extracted using a variant of symbolic aggregate approximation were projected onto a lower-dimensional space where patterns can easily be discerned. The results show, both in a qualitative and a quantitative manner, that there is high overlap between the classes that are formed using solely the umbilical cord pH information, irrespective of the selected dimensionality reduction method. These findings suggest that there is probably a limit to the performance expectation of the current pH-based systems and that alternative approaches should be also pursued to enhance the utility of computer-based decision support technologies.
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| 6. |
- Georgoulas, Georgios, et al.
(författare)
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An ordinal classification approach for CTG categorization
- 2017
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Ingår i: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). - Piscataway, NJ : IEEE. - 9781509028092 ; , s. 2642-2645
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Konferensbidrag (refereegranskat)abstract
- Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.
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| 8. |
- Georgoulas, George, et al.
(författare)
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Automatizing the detection of rotor failures in induction motors operated via soft-starters
- 2016
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Ingår i: Annual Conference of the IEEE Industrial Electronics Society, IECON 2015. - Piscataway, NJ : IEEE Communications Society. - 9781479917624 ; , s. 3743-3748
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Konferensbidrag (refereegranskat)abstract
- Implementation of unsupervised induction motor condition monitoring systems has drawn an increasing attention recently among motor drives manufacturers. In the case of soft- starters the possibility of incorporating fault detection features to their conventional functions provides an added value to those elements. Design and development of advanced algorithms that are able to automatically detect and alert about possible failures without requiring continuous human inspection is an especially challenging research goal. In this paper, an algorithm for the automatic detection of rotor damages in induction motors in the case of soft starting is proposed. The twofold approach relies, first, on the application of a time-frequency transform to the starting current signal and, second, on a pattern recognition stage based on the treatment of the time-frequency representation as a symbolic sequence. The innovation of this work is the implementation of the proposed approach for the automatic detection of rotor cage faults in soft-started motors. The experimental results prove the usefulness of the approach for the automatic detection of such faults and its potential for possible future implementation in soft-started machines.
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