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基于神經(jīng)網(wǎng)絡(luò )的高壓輸電線(xiàn)路單端測距方法
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蘭州交通大學(xué)自動(dòng)化與電氣工程學(xué)院,蘭州交通大學(xué)自動(dòng)化與電氣工程學(xué)院

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TM773

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Single Terminal Fault Location Method for High Voltage Transmission Line Based on ANN
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College of Automation and Electrical Engineering,Lanzhou Jiaotong University,College of Automation and Electrical Engineering,Lanzhou Jiaotong University

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    摘要:

    針對單端行波故障測距第二個(gè)行波波頭性質(zhì)辨識問(wèn)題,提出一種將小波模極大值方法和神經(jīng)網(wǎng)絡(luò )算法相結合的測距方法。采集故障波頭時(shí)間差和極性等信息作為樣本,利用神經(jīng)網(wǎng)絡(luò )的非線(xiàn)性擬合能力對樣本進(jìn)行訓練、測試,從而建立相應的故障測距神經(jīng)網(wǎng)絡(luò )模型。將故障信息代入神經(jīng)網(wǎng)絡(luò )模型得到初步測距結果,根據初測結果和波頭極性、時(shí)間差等性質(zhì)的關(guān)系,對第二個(gè)行波波頭進(jìn)行正確辨識,從而得到優(yōu)化的測距結果。經(jīng)Matlab/Simulink仿真驗證,該方法有較高的可靠性和精確性。

    Abstract:

    Aming at the question that the second traveling wave head for the single terminal fault location is difficult to be identified,a new fault location method combined with wavelet modulus maxima and artificial neutral network(ANN) is put forward.The time lag of the first three wave heads and their polarity are selected as the characteristic of ANN to establish fault diagnosis model by using the nonlinear fitting ability of neural network to train and test samples.Make the fault information into the ANN model to get the initial result.According to the intial result and the polarity , time lag of the wave heads,identify the second traveling wave head and obtained the accurate fault distance.Matlab/Simulink simulation results show that the presented method is efficient in fault location and the accuracy is high.

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毛元,張斌.基于神經(jīng)網(wǎng)絡(luò )的高壓輸電線(xiàn)路單端測距方法計算機測量與控制[J].,2015,23(10):18.

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歷史
  • 收稿日期:2015-04-03
  • 最后修改日期:2015-05-04
  • 錄用日期:2015-05-05
  • 在線(xiàn)發(fā)布日期: 2015-10-28
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