Methods of sequential test optimization in dynamic environment

In this paper, sequential test problem with assumption of varying test cost and failure rate is considered. Due to varied operation environment and maintain history of electronic equipment, the cost of measurement and/or failure rate of fault source may change throughout the life cycle. Under these circumstances, instead of rerunning the whole AO* algorithm thoroughly, we make trivial adjustments on previous decision tree to accommodate the new circumstance. This method is much more efficient than the traditional AO* algorithm. Besides, the decision tree can evolve with varying environment and maintain history. Without loss of accuracy, the time efficiency is improved. The effectiveness of the proposed approach is proved by simulation and comparison with other methods.