Modeling the Effect of Environmental Conditions on Reliability of Wind Turbines  

作　　者：蒋仁言 黄睿智 黄超群 

机构地区：[1]Faculty of Automotive and Mechanical Engineering,Changsha University of Science and Technology [2]Xinjiang Gold-Wind Science & Technology Co.,Ltd.

出　　处：《Journal of Shanghai Jiaotong university(Science)》2016年第4期462-466,共5页上海交通大学学报（英文版）

基　　金：the National Natural Science Foundation of China(No.71371035)

摘　　要：The climate condition of a wind farm has a significant influence on the reliability of wind turbines. The climate condition varies with season in a year and hence the reliability changes in a complex way. The purpose of this paper is to model the effect of climate condition on field reliability of wind turbines. The reliability is measured by monthly-averaged mean time between failures(MTBF), and the climate conditions are described by variables of monthly-averaged temperature, relative humidity, rainfall and wind speed. Referring to the physicsof-failure models in accelerated life testing(ALT), we develop a quantitative relation between the MTBF and the climate variables. For a set of field data, the model parameters are estimated by regression, and the insignificant variables are gradually deleted based on the P-value of the regression coefficients. The resulting model is useful for maintenance workload forecasting and preventive maintenance planning, and has a potential to be used in online failure prediction.The climate condition of a wind farm has a significant influence on the reliability of wind turbines. The climate condition varies with season in a year and hence the reliability changes in a complex way. The purpose of this paper is to model the effect of climate condition on field reliability of wind turbines. The reliability is measured by monthly-averaged mean time between failures （MTBF）, and the climate conditions are described by variables of monthly-averaged temperature, relative humidity, rainfall and wind speed. Referring to the physics- of-failure models in accelerated life testing （ALT）, we develop a quantitative relation between the MTBF and the climate variables. For a set of field data, the model parameters are estimated by regression, and the insignificant variables are gradually deleted based on the P-value of the regression coefficients. The resulting model is useful for maintenance workload forecasting and preventive maintenance planning, and has a potential to be used in online failure prediction.

关 键 词：RELIABILITY maintenance management wind turbine climate condition regression 

分 类 号：TK83[动力工程及工程热物理—流体机械及工程]