摘要
最优多故障诊断问题是一个NP-hard问题。针对平台罗经这一复杂系统,采用有向图描述元件与测试点间的因果依赖关系,并建立系统的多信号模型。在考虑元件发生故障的先验概率的前提下,提出一种基于拉格朗日算法(LRA)和子梯度优化算法(SOA)近最优多故障诊断算法,并在某型平台罗经的方位稳定系统多故障诊断中得到应用。结果表明:该方法相对于传统的单故障诊断方法诊断速度快,适用于平台罗经这类大型复杂系统的多故障诊断。
The exact computation of conditional probabilities for the multiple fault diagnosis （MFD） is NP-hard. The multi-signal model for complex stabilized gyrocompass is presented which uses diagram to subscribe the causal dependency relationship among components and test nodes. A heuristic algorithm to find approximately the most likely candidate fault set was introduced which is based on Lagrangian relaxation algorithm （LRA） and Subgradient optimization algorithm （SOA） under the consideration for prior probability of the components failure of system and the test nodes. The proposed method is validated in one test for the azimuth-stabilized system of stabilized gyrocompass. The results show that the reasoning process is faster than the traditional method using single-fault diagnosis. This novel method can be applied in MFD for the stabilized gyrocompass system.
出处
《中国惯性技术学报》
EI
CSCD
2005年第5期73-77,共5页
Journal of Chinese Inertial Technology
基金
国家杰出青年科学基金项目(40125013)
关键词
多故障诊断
拉格朗日松弛算法
子梯度优化法
平台罗经
multiple fault diagnosis
Lagrangian relaxation algorithm
subgradient optimization
stabilized gyrocompass
