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dc.contributor.authorJohn, P.M.
dc.contributor.authorDe Kock, J.A.
dc.date.accessioned2017-02-09T11:34:07Z
dc.date.available2017-02-09T11:34:07Z
dc.date.issued2007
dc.identifier.citationJohn, P.M. & De Kock, J.A. 2007. Data mining: a technique used to extract information from tan delta measurements on medium voltage induction motors. IEEE AFRICON 2007, 26-28 Sept: Article no 4401639. [http://ieeexplore.ieee.org/document/4401639/]en_US
dc.identifier.isbn978-1-4244-0986-0
dc.identifier.issn2153-0025
dc.identifier.issn2153-0033 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/20273
dc.identifier.urihttp://dx.doi.org/10.1109/AFRCON.2007.4401639
dc.identifier.urihttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4401639
dc.description.abstractThe study attempted to understand the condition of the insulation system and to classify the data according to its condition. Data mining processes were used to gain insight into the data and the condition of the insulation system. The different stages of data mining are explained. An analysis was done using self-organizing maps, which is an unsupervised neural network technique. Hierarchical and K-mean clustering techniques were used to classify the data. The results of the different techniques were compared to an expert's assessment. A comparison was done between the different techniques used. The patterns in the different features of the data due to ageing were observed. The data was qualitatively assessed and classified into groups according to the deterioration of the insulation system using the classification techniques. Finally the results correlated well with the expert's assessmenten_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectAssessment of insulation systemsen_US
dc.subjectMotor Insulation testsen_US
dc.subjectTan delta testsen_US
dc.subjectData miningen_US
dc.subjectSelf-organizing mapsen_US
dc.subjectNeural networksen_US
dc.titleData mining: a technique used to extract information from tan delta measurements on medium voltage induction motorsen_US
dc.typePresentationen_US
dc.contributor.researchID12405442 - De Kock, Jan Abraham


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