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Application of artificial intelligence techniques to the monitoring of polluted insulators

机译:人工智能技术在污染绝缘子监测中的应用

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Leakage current data is utilised to investigate indicators of insulator surface degradation (ageing). An accelerated ageing test was developed to study the degradation of small samples of insulation materials (silicone rubber and EPDM). The computerised data acquisition system allows on-line capture of cycles of voltage and current every second. These data were then analysed to extract rms and mean values, FFT parameters and the instantaneous power absorbed during the test. The extracted data were then used as input to artificial intelligence software, based on the self-organising Kohonen maps, in order to identify trends in the surface ageing process. It was found that leakage current magnitude alone was not a suitable indicator of ageing hut maps combining data input from multiple parameters did show some trends in the ageing process.
机译:泄漏电流数据用于研究绝缘体表面降解(老化)的指标。开发了加速老化试验,以研究绝缘材料的小样本(硅橡胶和EPDM)的降解。计算机化数据采集系统允许每秒在线捕获电压和电流循环。然后分析这些数据以提取RMS和平均值,FFT参数和测试期间吸收的瞬时功率。然后基于自组织Kohonen地图将提取的数据用作人工智能软件的输入,以确定表面老化过程的趋势。结果发现,单独的漏电流幅度不是组合来自多个参数的数据输入的老化小屋地图的合适指标确实在老化过程中显示了一些趋势。

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