非迭代动态多故障诊断方法研究

摘要

由于传感器噪声和故障判决规则的不可靠,故障检测系统难免出现检测错误.不同的测试之间具有一定的冗余关系,利用这些关系就可以纠正一定的错误.基于迭代的动态多故障诊断(DMFD)算法在系统中有测试错误的情况下具有较高的诊断正确率,但当系统规模较大时,它的迭代过程并不必要,且有时迭代并不能收敛到最优值.针对这一问题,文章在详细分析迭代拉格朗日松弛方法和维特比算法原理的基础上,提出了利用故障和测试结果之间的关系来估计拉格朗日乘子的非迭代动态多故障诊断方法.该方法避免了迭代过程,减少了计算时间并提高了诊断正确率.对航天器电源系统的诊断表明,非迭代动态多故障诊断方法的诊断速度快,且其正确率高于以前的算法.%Because the sensors have noises and, the failure discrimination rule is sometimes unreliable, the fault detection result of a machine is not always correct. A good fault diagnosis method should contain redundancy among different test points and instants to increase the fault isolation rate. The dynamic multiple fault diagnosis (DMFD) method is shown to have a good diagnostic performance in testing unreliable conditions. But when the system is large in scale, the iteration would be unnecessary, and it does not always reach the optimal value. In this paper, the principles of Lagrange relaxation and Viterbi algorithm are analyzed first, then a method is proposed to make use of the relationship between faults and test results to estimate the Lagrange multiplier. By leaving out the iteration process, the computation time is reduced and the real-time performance of the algorithm is enhanced. Simulation results show that the new algorithm gives much faster calculation speed with a higher fault isolation rate.