Optimal design of constant-stress accelerated degradation test with multiple stresses for motorized spindle

In order to effectively shorten the cycle of electric spindle acceleration degradation test, control the test cost, and improve the accuracy of reliability evaluation, an improved multiple stresses constant acceleration degradation test optimization design method is proposed. By using the experimental cost as a constraint condition and adopting the A and D dual optimization criteria, an optimization model is established. Firstly, the particle swarm algorithm is used to construct a candidate set of experimental schemes, and then the Monte Carlo simulation method is used to generate simulated fault data for accelerated degradation experiments. Finally, the ADT optimal experimental scheme is obtained through statistical analysis. By comparing and analyzing the optimization design results of a certain model of electric spindle with existing common optimization methods, it has been proven that this method can effectively reduce testing time, improve testing efficiency, reduce testing costs, and have reliability and effectiveness.