摘要
风电机组的状态监测和故障诊断是保证机组长期稳定运行和安全发电的关键。基于风电机组的基本结构,介绍了机组的故障类型和机理,论述了实际应用中机组的状态监测和故障诊断技术;基于BP神经网络的原理和优点,深入讨论了如何应用人工神经网络构建风电机组智能诊断系统,并给出了可行的系统设计方案和软件实现流程图。
The condition monitoring and fault diagnosis is crucial in ensuring the long-term safe and stable operation of wind turbines. Considering the basic structure of the wind turbine, this paper introduces the type and mechanism of wind turbine failures, and expounds the condition monitoring and fault diagnosis technology actually applied. Based on principles and advantages of the BP neural network, the paper conducts presents an in-depth discussions on how to build the intelligent fault diagnosis system by means of the artificial neural networks, and then presents followed by a feasible system design scheme and a software flow chart.
出处
《电网与清洁能源》
2011年第2期61-66,70,共7页
Power System and Clean Energy
基金
国家自然科学基金(50907051)
关键词
风电机组
状态监测
故障诊断
神经网络
wind turbines
condition monitoring
fault diagnosis
neural networks
