摘要
制粉系统作为热力发电厂非常重要的子系统之一,其运行状况在一定程度上决定了电厂的经济性。由于制粉系统的复杂性,对其运行状态的判断非常困难。运用RBF神经网络来对制粉系统进行故障诊断,可使运行人员对当前制粉系统运行状况有所了解。
The state of operation of pulverizing systems, which are one of the important systems in a power plant, have, to a certain degree, a decisive influence on the plant＇s profitability. Because of its complexity, it is quite difficult to judge whether a pulverizing system is in a satisfactory state of operation. Application of RBF neural networks for diagnosing faults in pulverizing systems can make operators sense the present state of operation of pulverizing systems.
出处
《发电设备》
2006年第6期449-453,共5页
Power Equipment
关键词
自动控制
发电厂
制粉系统
故障诊断
RBF神经网络
automatic control
power plant
pulverizing system
fault diagnosis
RBF neural network
