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Modelling the effects of the environment on wind turbine failure modes using neural networks

机译:用神经网络建模环境对风力涡轮机破坏模式的影响

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Neural networks were used to investigate if any relationship existed between maximum daily gust speed, average daily wind speed and temperature and wind turbine failure modes. Using five years of weather station data a typical site characteristic was determined using the neural network. This was then compared to a characteristic produced using only weather data for days when failures occurred. These failure and normal characteristics were then compared to determine if any relationships existed. It was found that several relationships existed, most notably between gearbox failures and changeable weather conditions.
机译:神经网络用于调查最大每日阵风速度,平均日风速和温度和风力涡轮机故障模式之间是否存在任何关系。使用五年的气象站数据,使用神经网络确定典型的站点特性。然后将其与仅在发生故障发生的天气数据产生的特征进行比较。然后比较这些故障和正常特性,以确定是否存在任何关系。发现有几个关系存在,最值得注意的是,齿轮箱故障和可变天气条件之间。

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