塔式太阳能热电站故障诊断系统研究

Research on Fault Diagnosis System of Tower Solar Thermal Power Station

根据塔式太阳能热电站的系统结构和运行特点,开发了塔式太阳能热发电站的故障诊断系统,采用模糊综合评价方法建立了故障等级评价体系。故障诊断系统采用以专家系统为主、径向基函数(Radial Basis Function,RBF)神经网络为辅的故障诊断结构。专家系统综合运行专家知识、模糊数学和小概率识别法量化表示故障征兆,建立故障评价体系。进行故障实例验证分析,结果表明:该故障诊断系统结构设计合理、诊断方法可行、故障诊断准确以及故障等级评价结果可信,具有较大的实用价值。

Based on the system structure and operational characteristics of tower solar thermal power plants,a fault diagnosis system for tower solar thermal power plants has been developed,and a fault level evaluation system has been established using fuzzy comprehensive evaluation method.The fault diagnosis system adopts a fault diagnosis structure mainly composed of expert systems and supplemented by Radial Basis Function(RBF)neural networks.The expert system integrates expert knowledge,fuzzy mathematics,and small probability identification methods to quantitatively represent fault symptoms and establish a fault evaluation system.The validation analysis of fault examples shows that the structural design of the fault diagnosis system is reasonable,the diagnostic method is feasible,the fault diagnosis is accurate,and the fault level evaluation results are reliable,which has great practical value.