یک سیستم خبره برای تشخیص صوتی قطع کننده مدار قدرت و تعویض شیر در بار
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|52610||2015||8 صفحه PDF||سفارش دهید||5838 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 42, Issue 24, 30 December 2015, Pages 9426–9433
Most of the faults on power Circuit Breakers (CBs) and On-Load Tap Changers (OLTCs) on high voltage transformers are of mechanical origin. Mechanical malfunction, mechanical wear and other types of abnormal behaviors can be detected as changes in the acoustic signatures. In this paper, an Expert System (ES) with the addition of a signal processor module and factual database module to the conventional ES has been proposed for the diagnosis of CBs and OLTCs. The feature extraction of the acoustic signatures has been done by decomposing them into voiced and silent portions in time domain and through FFT spectrum analysis in frequency domain. The OLTC's motor current has been decomposed into inrush, steady-state and extended currents to locate the cause of different anomalies in the OLTCs and acoustic-current pair has been used for the synchronization testing. Each extracted feature of the testing signal has been compared to the similar feature of a reference signal to not only identify the health of the testing device but also to locate the cause of each anomaly. Several test signals have been compared against the reference signature and the proposed expert system has proved to be a suitable, effective and reliable system for the acoustic diagnosis of OLTCs and CBs.