自适应模糊系统在大坝安全监测故障诊断中的应用

Application of adaptive fuzzy system to fault auto-diagnosis in dam safety monitoring

为提高大坝安全自动化监测的稳定性与可靠性,提出一种基于模拟退火的自适应模糊系统(AFS:AdaptiveFuzzySystem)的学习算法,并根据此算法建立了大坝安全监测非线性监测器模型,同时利用该模型构造了大坝安全自动化监测故障自诊断系统.实例表明,该系统既具有模拟退火算法(SAA:SimulatedAnnealingAlgorithm)的全局优化搜索能力,又充分发挥了AFS的非线性逼近能力,并能够较好地实现故障的在线诊断和实时隔离.

A kind of learning algorithm of adaptive fuzzy system (AFS) based on the simulated annealing algorithm (SAA) was presented to improve the stability and reliability of dam safety automatic monitoring. According to the algorithm, a non-linear monitor model and a fault auto-diagnosis system for dam safety monitoring were developed. A case study shows that the present system, just as SAA, brings the nonlinear fitting of AFS into full play, and has the capacity of global optimal search, realizing the on-line diagnosis and real-time separation of faults effectively.