Systems with a hidden degradation process are perva- sive in the real world. Degrading critical components will under- mine system performance and pose potential failures in the future. Prognostic aims at predicting p...Systems with a hidden degradation process are perva- sive in the real world. Degrading critical components will under- mine system performance and pose potential failures in the future. Prognostic aims at predicting potential failures before it evolves into faults. A prognostic procedure based on expectation maxi- mization and unscented Kalman filter is proposed. System state, sensor measurement and hidden degradation process are viewed as data （incomplete or missing） in the expectation maximization method. System state and hidden degradation process are esti- mated by a unscented Kalman filter upon sensor measurements. Component-specific parameters in a degradation process are iden- tified on the estimation of the degradation process. Residual life is measured by the median of estimated residual life distribution. The proposed procedure is verified by simulations on a first-order capacitor-resistance circuit with degrading resistance. Residual life estimation consists conservatively with the trend and is evalu- ated in terms of relative errors. Simulation results are reasonable. The proposed prognostic method expects applications in practice.展开更多
文摘Systems with a hidden degradation process are perva- sive in the real world. Degrading critical components will under- mine system performance and pose potential failures in the future. Prognostic aims at predicting potential failures before it evolves into faults. A prognostic procedure based on expectation maxi- mization and unscented Kalman filter is proposed. System state, sensor measurement and hidden degradation process are viewed as data （incomplete or missing） in the expectation maximization method. System state and hidden degradation process are esti- mated by a unscented Kalman filter upon sensor measurements. Component-specific parameters in a degradation process are iden- tified on the estimation of the degradation process. Residual life is measured by the median of estimated residual life distribution. The proposed procedure is verified by simulations on a first-order capacitor-resistance circuit with degrading resistance. Residual life estimation consists conservatively with the trend and is evalu- ated in terms of relative errors. Simulation results are reasonable. The proposed prognostic method expects applications in practice.
