【摘要】 针对电液伺服作动器早期故障信号的微弱性和不易检测性,提出了一种基于故障特征概率分布相对熵的健康评估算法。采用离线训练对正常状态特征概率密度进行参数估计,在线监测作动器特征概率密度分布相对于正常状态的相对熵,通过判断相对熵的值对伺服作动器的进行健康评估。仿真结果证明了该方法的可行性和有效性。更多还原

【Abstract】 Aiming at that the electro-hydraulic servo actuator of early fault signal is weak and not easy to detect, a new arithmetic based on fault feature probability distribution relative entropy is put forward for flight health evaluation.The parameter of normal state feature probability density is estimated by off-line training,and the actuator feature probability density relative entropy between current status and normal state is monitored online. The health status of servo actuator is evaluated by relative entropy.The simulation results prove the feasibility and validity of the method.更多还原