基于相关矩阵与概率模型的故障模糊诊断  

Fault fuzzy diagnosis based on correlation matrix and probability model

作　　者：张弢 王金波[2] 张涛[2] 

机构地区：[1]中国科学院大学,北京100049 [2]中国科学院空间应用工程与技术中心,北京100094

出　　处：《系统工程与电子技术》2018年第2期346-352,共7页Systems Engineering and Electronics

基　　金：国家重大专项(Y3140731RN)资助课题

摘　　要：针对复杂系统故障快速模糊诊断问题,提出了一种基于相关矩阵和概率模型的故障模糊诊断方法。通过建立故障-测试相关矩阵,在概率空间中获取故障判据,并考察非理想测试条件下故障出现某种征兆的概率值,继而利用概率最值原则推理故障、利用最小模原则进行故障筛选以降低虚警,实现了对复杂系统故障的高效便捷诊断。以阿波罗飞船发射前测试数据为对象对该方法进行了验证。实验结果表明,该方法具有足够的诊断精度,以及较低的运算复杂度,并且支持图形化快速诊断、便于现场应急使用。A fault fuzzy diagnosis method based on correlation matrix and probability model is proposed to deal with complicated system fault diagnosis problems. A fault-test correlation matrix is established and the fault criterion in probability space is obtained. By investigating the probabilities of fault features in non-ideal test conditions, and using the principles of reasoning, a fault fuzzy diagnosis can be done. Faults filtering according to minimum norm can further reduce the false alarm, which contributes to achieve an efficient and convenient diagno- sis for complicated system. The proposed method is validated by using the test data of Apollo before launching. Experi- mental results show that the proposed method has sufficient diagnostic accuracy, as well as low computational complex- ity, which can support rapid diagnosis and be convenient for on-site emergency use.

关 键 词：模糊诊断 概率模型 相关矩阵 复杂系统 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]