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Research on Optimization of Feature Extracting Based on PD Fingerprints in Pattern Recognition

机译:基于PD指纹在模式识别中的特征提取优化研究

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In order to investigate the effect of feature extraction on pattern classification for partial discharge (PD) signals appearing potential insulating failures in high voltage apparatus while operation, the PD-fingerprints acquired by Hipotronics DDX-7000 digital PD detector are taken as database and method on the feature extracting from the database is carried out, and its practicability is demonstrated by the mathematics and experiment, respectively. The BP neural network is made of three layers and the transfer function of hidden layer and output layer are tansig, then the influence of the structure of neural network on recognition results is studied at the same time. As a result, the optimal characteristic vector with obvious separability and the number of hidden layer are obtained, and achievements of research show that the network convergence is not only quickly, but also the recognition rate very high so much as up to 100%.
机译:为了研究特征提取对局部放电(Pd)信号的图案分类的影响,在操作时出现在高压装置中的潜在绝缘故障的潜在绝缘故障,由Hipotronics DDX-7000数字PD检测器获取的PD指纹被视为数据库和方法从数据库中提取的特征提取,分别通过数学和实验证明其实用性。 BP神经网络由三层组成,并且隐藏层和输出层的传递函数是坦率的,然后在同一时间研究了神经网络结构对识别结果的影响。结果,获得了具有明显可分离性和隐藏层的最佳特征的传染媒介,以及研究的成就表明,网络融合不仅快速,而且识别率非常高,高达100%。

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