首页> 外文会议>37th International Universities Power Engineering Conference (UPEC 2002) >APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO THE MONITORING OF POLLUTED INSULATORS
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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 but 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子表面退化(老化)的指标。开发了加速老化测试来研究少量绝缘材料(硅橡胶和EPDM)样品的降解。计算机化的数据采集系统允许每秒捕获电压和电流周期。然后分析这些数据以提取均方根值和平均值,FFT参数以及测试期间吸收的瞬时功率。然后,基于自组织的Kohonen映射,将提取的数据用作人工智能软件的输入,以识别表面老化过程中的趋势。已经发现,仅泄漏电流幅度不是老化的合适指标,但是结合了来自多个参数的数据输入的映射图确实显示了老化过程中的一些趋势。

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