دانلود مقاله ISI انگلیسی شماره 57598
ترجمه فارسی عنوان مقاله

کسب دانش ارتعاشات در ترانسفورماتور با قدرت بالا با استفاده از تجزیه و تحلیل آماری و روش فازی - مطالعه موردی

عنوان انگلیسی
Knowledge acquisition of vibrations in high-power transformers using statistical analyses and fuzzy approaches – A case study
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
57598 2013 6 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Electric Power Systems Research, Volume 104, November 2013, Pages 110–115

ترجمه کلمات کلیدی
منطق فازی؛ ارتعاشات:اندازه گیری متغیر های برق
کلمات کلیدی انگلیسی
Electrical variables measurement; Fuzzy logic; Vibrations
پیش نمایش مقاله
پیش نمایش مقاله  کسب دانش ارتعاشات در ترانسفورماتور با قدرت بالا با استفاده از تجزیه و تحلیل آماری و روش فازی - مطالعه موردی

چکیده انگلیسی

This paper presents the results of a knowledge acquisition of vibrations in high-power transformers in two substations of an Electrical Power System in the Amazon region, Brazil. Radial graph areas were obtained, to enable the analyses of the vibrations at four sites at different measurement points in the transformer bodies. In certain cases, variations in vibrations non-justified by corrective maintenance were observed. The repeated measure analysis showed that the largest mean vibration area occurred in the front of the transformer. With these results, measurements on a sequential processor were made and the vibration behavior due to commutations analyzed. Statistical analyses and the repeated measure analysis were used in the process of knowledge acquisition, establishing the basis for the construction of a fuzzy inference system. Compared to other predictive maintenance methods, vibrations are a physical phenomena that can be used in the construction of non-invasive, low-cost analyses techniques, so this approach may become an important and valuable tool for use in solving problems in environments of uncertainty, as in the programming process of vibration monitoring in high-power transformers, providing a means to diagnose the physical operational states of transformers by the generated inspection alerts.