摘要
随着中国风力发电的比重及机组容量的不断增大,机组一旦发生故障,不仅影响风电场自身的安全,而且对电网的稳定运行造成重大影响。故障分析与智能诊断技术是降低大型风力发电机组故障率与运维费用的主要手段之一。文中详细分析了风力发电机组主要部件的故障,在对风力发电机组状态监测和故障诊断技术深入研究的基础上,提出了基于小波包和BP神经网络的智能诊断方法,以此开发了风力发电机组状态监测与故障诊断系统,通过系统在大型风力发电场的成功应用,验证了其对风电机组故障诊断的有效性。
With the proportion of wind power and capacity of the unit are increasing in China,If the unit is in the event of accident, which not only affect the safety of wind farm itself, but also will have a significant impact to the stability of the operation of power grids. Fault analysis and intelligent diagnosis technology is one of the primary means in reducing the failure rate and the cost of operation and maintenance of large wind turbines. The main components＇ faults of wind turbine generator set are analyzed in detail. On the basis of further research about condition monitoring and diagnosis technologies of wind turbine, the new method of intelligent diagnosis based on wavelet packets and BP neutral network is proposed, which is responsible for the development of the condition monitoring and malfunction of the condition monitoring and malfunction diagnosis system of wind turbine. Then the validity of the whole system is verified by the system＇s successful application in a large scale wind turbine generator field.
出处
《高压电器》
CAS
CSCD
北大核心
2016年第10期176-181,共6页
High Voltage Apparatus
基金
国家电网科技项目(522722140031
5227221350B)~~
关键词
风电机组
小波包
BP神经网络
状态监测
故障诊断
wind turbine generator set
wavelet packets
BP neural network
condition monitoring
fault diagnosis
