Abstract: Due to the strong uncertainty of degradation of relevant aviation components, a sequential inspection model based on real-time reliability evaluation is proposed to determine the interval of inspection and maintenance more scientifically. The Wiener process is used to describe the performance degradation of products. The analytical expression of real-time reliability distribution is obtained by use of the first-hitting time theory. And an adaptive method is proposed to evaluate the unknown parameters by using the strong tracking filtering algorithm, the optimal smoothing algorithm (RTS) and the expectation maximization algorithm (EM). Once the new degradation information is available, the parameters should be updated with Bayesian equation in real time. Moreover, the historical information of the same type product is integrated in the selection of the initial parameters to achieve the fast convergence of the updating algorithm. Thirdly, according to the real-time reliability requirements of the product, the optimized sequential inspection interval is determined. Finally, an example of fatigue crack growth in an aerospace aluminum alloy is given to illustrate the validity of the proposed model and the algorithm. The results have proved that the real-time data of aviation products during operation can be fully utilized by the model based on real-time reliability evaluation, and the accuracy of product reliability estimation can be improved effectively under uncertain conditions, so that the efficiency and practicability of the sequential inspection strategy are ensured.

Key words: Bayesian, expectation maximization algorithm, real-time reliability, sequential inspection, Wiener process