车削颤振时变可靠性分析

考虑车削加工过程中刀具磨损对切削力系数的影响，用Gamma过程描述了切削力系数随时间的变化过程，并建立了车削颤振时变可靠性模型.提出了主动学习的Kriging模型与基于首次超越的子集模拟相结合的时变可靠性分析方法(AK-SSFP).对某一车床建立车削颤振稳定性模型，分别采用Monte Carlo方法(MCS)、基于主动学习Kriging的Monte Carlo方法(AK-MCS)和AK-SSFP方法计算车削颤振时变可靠度.AK-SSFP方法的结果与MCS方法的结果一致性很好，且AK-SSFP方法减少了真实极限函数的调用次数并缩短了运算时间.AK-SSFP在保证精度的同时提高了计算效率，解决了车削加工系统颤振时变可靠度的计算问题.

Time-Varying Reliability Analysis of Turning Chatter

Considering the influence of tool wear on the cutting force coefficient in turning， the Gamma process was used to describe the change of cutting force coefficient with time， and a time-varying reliability model of turning chatter was established. A time-varying reliability analysis method(AK-SSFP)combining the Kriging model of active learning with the subset simulation based on the first passage was proposed. A model of turning vibration stability was established for a lathe. The Monte Carlo method(MCS)， the Monte Carlo method based on active learning Kriging(AK-MCS)and the AK-SSFP method were used to calculate the time-varying reliability of turning chatter. The results of the AK-SSFP method are in good agreement with the results of the MCS method， and the AK-SSFP method reduces the number of calls to the real limit function and shortens the computation time. AK-SSFP improves the calculation efficiency while ensuring the accuracy， and solves the calculation problem of time-varying reliability in turning chatter.