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中文摘要：
针对气阀故障异常自动检测迫切需求，针对气阀故障在温度数据的表现特点，即同类气阀正常工作时温度波动一致，故障时温度波动存在差异，采用主成分分析（ PCA）从气阀阀盖温度数据中提取故障特征参数，建立基于径向基函数的故障异常监测模型，实现了故障异常自动检测，并可进一步对故障气阀进行自动定位，为故障早期快速报警奠定了基础。
英文摘要：
In order to satisfy the pressing needs of valve fault automatically detection, and according to the characteristic of valves’ temperature data,it’ s found that the suction （ or exhaust） valves’ temperature is consistent when the valves work,other-wise it’ s not.From this fact,the authors use the PCA （ Principal Component Analysis） to extract features to reflect the perform-ance based on valves’ temperature data.Simultaneously,with the establishment of radial basis model,it can achieve valve fault a-nomaly detection and automatic location of abnormal valve,and lay the foundation of early and quick warning of valve fault.
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