Multi-objective optimization design for accelerated degradation test based on game theory.

Accelerated degradation test is an effective way for the rapid reliability assessment of mechanical systems. Most of the existing optimization methods for accelerated degradation tests aim to optimize objective functions with a single objective, which leads to inappropriate optimization results. To solve the problem, a multi-objective optimization design method is presented for accelerated degradation tests based on game theory in this work. First, the multi-objective optimization model is established to optimize the prediction precision of lifetime distribution, the estimation precision of model parameters, and the robustness of model parameter deviation under the constraint that the total experimental cost does not exceed the predetermined budget. Based on game theory, the multi-objective optimization model is transformed into a cooperative game problem. The fuzzy clustering method is applied to calculate the strategy space owned by each player. Each player considers the benefits of other players in the construction of its benefit function to form a collusive cooperation model. Under the condition of maximizing the collective interest, the multi-objective optimization model is solved to obtain a compromised optimal test plan which balances the multiple optimization objectives. Finally, the necessity and effectiveness of the proposed method have illustrated a group of examples of motorized spindles.