针对飞控系统早期故障信号的微弱性和不易检测性,提出了一种基于贝叶斯决策的飞控系统状态监测和健康管理新算法;采用最大似然估计法对故障特征向量概率密度函数进行参数估计,监测飞控系统故障特征概率密度分布相对于正常状态的偏离,将不易检测的故障信号转化为容易观测到的偏离信息,实现飞控系统状态的健康评估；以某型电液伺服作动器为例,采用上述方法对其进行状态监测和健康管理,仿真结果证明了该方法的可行性和有效性.%Aim at that early fault signal of the flight control system is weak and not easy to detect, a new arithmetic based on bayesian decision is put forward for flight control system state monitoring and health management. Maximum likelihood estimation method is used to estimate the parameter of fault feature vector probability density function, the probability density function distributing departure between current state and normal state of flight control system is detected, the fault signal which is not easy to detect is transformed to deviation information which is easy to observe, the health state of flight system is evaluated. Taking a certain type of electro-hydraulic servo actuator as an example, the method above carries on the status monitoring and health management and the simulation results prove the validity and feasibility of the method.
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