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Intelligent condition recognition of transmission line based on digital image processing

机译：基于数字图像处理的输电线路状态智能识别

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According to the remote monitoring requirements of smart grid construction, in this paper the condition recognition approach combining digital image processing with artificial neural networks is proposed for transmission lines. The digital image processing methods, including gray scale transformation, histogram modification, wavelet packet denoising and edge detection are used to process the images of transmission lines and make the characteristics more outstanding. After dividing the images into some regions the distribution of edge features of transmission line components is extracted as characteristic values. This method has good adaptability. At last, a three-layer back propagation (BP) artificial neural network (ANN) is constructed and applied recognize the typical transmission line conditions. The result shows that this approach has good recognition rate and popularization.
机译：根据智能电网建设的远程监控需求，提出了一种将数字图像处理与人工神经网络相结合的状态识别方法。数字图像处理方法包括灰度变换，直方图修改，小波包降噪和边缘检测等，用于处理传输线图像，使特征更加突出。在将图像划分成一些区域之后，提取传输线分量的边缘特征的分布作为特征值。该方法适应性强。最后，构建了三层反向传播（BP）人工神经网络（ANN）并应用于识别典型的传输线条件。结果表明，该方法具有较高的识别率和推广性。

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