MATEC Web Conf.
Volume 294, 20192nd International Scientific and Practical Conference “Energy-Optimal Technologies, Logistic and Safety on Transport” (EOT-2019)
|Number of page(s)||7|
|Section||Interoperability, Safety and Certification on Transport|
|Published online||16 October 2019|
Classification of quality conditions of a traction motor frame insulation of locomotives
Dnipro National University of Railway Transport named after Academician V. Lazaryan, Department of Locomotives, 49010 Dnipro, Lazaryan Street 2, Ukraine
2 Dnipro National University of Railway Transport named after Academician V. Lazaryan, Department of automation and telecommunications, 49010 Dnipro, Lazaryan Street 2, Ukraine
3 LLC “Applied Railway Technologies”, Head of Technical Projects, Department of Inspectors, Adam-Klein-Str. 26, Nürnberg D-90429s, Germany
* Corresponding author: firstname.lastname@example.org
The objective of the article is to determine the quality conditions of a locomotive traction motor frame insulation based on observations over the recovery voltage and classification of a tested insulation wear degree as well as to determine estimates of operating time until the insulation restoration or replacement with a new one. To classify the insulation quality conditions and to forecast its residual life until the restoration, a cluster analysis and discriminant analysis are used based on indicators reflecting the properties of an insulation recovery voltage curve. The study defines an information content received from frame insulation recovery voltage readings as compared with its resistance from the perspective of testing the insulation condition and predicting its residual life. Statistical characteristics of clusters corresponding to the insulation condition stages allow determining the limit values of predicting parameters and estimating the residual insulation life prior the restoration. To classify the insulation condition, an integrated evaluation of the insulation condition quality is proposed. Integrated evaluation is performed according to the recovery voltage curve and is used as an indicator during clustering. An experimental study of the proposed method practically confirmed its effectiveness.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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