The existing remaining useful life (RUL) prediction method with random shock, is not suitable for the situation that uneven measurement intervals and inconsistent measurement frequencies. And this type of method ignores the variability of adaptive drift in the future degradation process. In view of this, based on the adaptive Wiener process, this paper propos-es a RUL prediction method with random shock. Firstly, the normal distribution is used to describe the influence of ran-dom shock on equipment degradation, and it’s establishing an adaptive Wiener process degradation model with random shock. Then, the analytical expression of RUL is derived in the sense of first arrival time. Considering the variability of degradation drift and the influence of random impact on degradation rate, this paper constructs the state space model to realize the online update of equipment RUL. And a model parameter estimation based on expectation maximization algo-rithm is proposed. Finally, Numerical simulation, inertial navigation system gyroscope and lithium battery examples veri-fied the effectiveness and practicability of the proposed method from different angles.
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