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Forecasting of polluted insulator flashover based on multivariate nonlinear time series analysis

机译:基于多元非线性时间序列分析的绝缘子污秽闪络预测

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To solve the problem of the flashover forecasting of contaminated or polluted insulator, a flashover forecasting model of contaminated insulators based on multivariate nonlinear time series analysis is proposed in the paper. The equivalent salt deposit density (ESDD) is the key of flashover on polluted insulator. The ESDD value of insulator can be forecasted by the method of nonlinear time series analysis of the ESDD time series and a forecasting model of polluted insulator flashover is proposed in the paper. The forecasting model consists of two artificial neural networks that reflect relationship of environment, ESDD and flashover probability. The first is used to estimate the ESDD time series of insulator and the second is employed to calculate the probability of the flashover. A series of artificial pollution tests show that the results of the forecasting model is acceptable.
机译:为解决绝缘子被污或被污物闪络预测问题,提出了一种基于多元非线性时间序列分析的绝缘子被污物闪络预测模型。等效盐沉积密度(ESDD)是被污染绝缘体闪络的关键。可以通过对ESDD时间序列进行非线性时间序列分析的方法来预测绝缘子的ESDD值,并提出了污染绝缘子闪络的预测模型。该预测模型由两个人工神经网络组成,它们反映了环境,ESDD和闪络概率之间的关系。第一个用于估计绝缘子的ESDD时间序列,第二个用于计算闪络的可能性。一系列的人工污染测试表明,该预测模型的结果是可以接受的。

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