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Study of Key Technology and Mechanism of HV Contaminated Insulators Flashover for Online Monitoring and Risk Prediction

Author: HeBo
Tutor: LinHui
School: Northwestern Polytechnical University
Course: Detection technology and automation devices
Keywords: flashover arc online monitor risk predict statistics analysis wavelet analysis signal disposal mode recognition model and simulation
CLC: TM855
Type: PhD thesis
Year: 2006
Downloads: 592
Quote: 11
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Abstract


Detecting and recognizeing flashover characters from HV contaminated insulators and developing effective flashover predicting and evaluating technology on the basis of measured signial is important for improving the ability for preventing flashover. As the electric power capacity and transmission voltage getting more and more increased, flashover from contaminated insulators became the most important factors affecting the reliability of high-voltage transmission system seriously. For the transmission system at present voltage level, the harm and losing from flashover is far more than that from thunderstroke and operation overvoltage. It can be asserted that the flashover will be more serious in the future as the ultra-voltage gets used more and more widely. In this paper, the problem about online monitoring method, risk predicting method of flashover occurring, flashover mechanism and modeling, artificial pollution test were explored with the aim of benefiting the advanced study for setting up the effective predicting and monitoring system of flashover in the future. The problem studied in this paper is listed as follow:1. The limited element method and optimization algorithm was introduced for calculating the arc voltage, arc length, leakage current (LC), electric field distribution during the period of arc extending and flashover development of insulator model, which can deal with complex object with uneven dirty distribution or anomalous shape more conveniently than traditional method such as charge simulation and circuit analysis.2. The statistics theory such as analysis of variance (ANOVA), correlation analysis, partial correlation analysis were used for analyzing the data from artificial pollution test and the notable factors affecting the LC were determined. All this is

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CLC: > Industrial Technology > Electrotechnical > High Voltage Engineering > High - voltage insulation technology > Insulation test and inspection
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