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

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 in some sub-assemblies the failure trends differed to the normal conditions trend, suggesting that there may be relationships.