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faulty insulator 故障絕緣子。

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In order to verify the effectiveness of steep - front impulse voltage test in finding the internal faults of composite insulator , some insulators with faults , including conductive channel , semi - conductive channels , airy channel , partial little air bubble that occur separately at different place , are modeled . steep - front wave impulse voltage test is made for these faulty insulator and normal insulator 為了檢驗陡波試驗對于發現合成絕緣子內部故障的有效性,分別模擬了絕緣子內部不同部位有導電性、半導電性通道,小氣泡,金屬雜質,長氣泡以及芯棒與護套間不粘連故障的絕緣子,并從三維靜電場計算和用不同陡度的陡波試驗兩個方面進行了驗證。

We took a lot of data of corona pulses from the laboratory and field by using the detecting device . we got the corona finger prints for both the good insulators and the faulty insulators by statistic of the data 本文利用檢測裝置,在實驗室和現場分別采集了大量電暈脈沖數據,統計分析了有、無不良絕緣子時電暈信號的譜圖特征。

But its accuracy of detecting is low in application . in this paper we try to find a method based on artificial neural network to improve the accuracy of detecting faulty insulators 本文力圖通過大量的實驗室和現場數據的分析,發展一種基于人工神經網絡的不良絕緣子診斷方法,提高脈沖電流法用于檢測不良絕緣子的準確性。

Corona pulses current method is a way which can be used to detect faulty insulators on ground 電暈脈沖電流法是一種地面檢測不良絕緣子的方法,但目前應用中其檢測的準確度較低。