基于相关矩阵与概率模型的故障模糊诊断

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。

Fault fuzzy diagnosis based on correlation matrix and probability model

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 diagnosis for complicated system. The proposed method is validated by using the test data of Apollo before launching. Experimental results show that the proposed method has sufficient diagnostic accuracy, as well as low computational complexity, which can support rapid diagnosis and be convenient for on-site emergency use.