摘要
提出了一种主元分析与模糊聚类相结合的故障诊断方法,该方法首先用主元分析方法降维、提取故障特征,并计算出T2值和Q值,若超过阈值说明有故障发生,则用模糊聚类识别故障,具有诊断时间短、准确性高的优点。通过对田纳西-伊斯曼过程的仿真表明了该方法的有效性。
A kind of fault diagnosis method based on improved PCA and the fuzzy clustering is proposed, which use shorter diagnosis time and higher accuracy. We extract fault feature subset by PCA, then calculate values of T2 and Q, if they surpassed the threshold, identify the fault class using the fuzzy clustering, The application of Tennessee- Eastman Process （TEP） shows the validity of the proposed method.
出处
《沈阳航空工业学院学报》
2009年第2期54-57,共4页
Journal of Shenyang Institute of Aeronautical Engineering
