摘要
加速寿命试验方案的优劣,直接影响着试验的成本、效益和试验结果的准确性,因此有必要对试验方案进行优化设计,寻找最佳应力水平和试样分配比例,使加速寿命试验的结果最准确、代价最小。利用目标函数的连续性,提出一种基于离散数据的拟合方法,将加速寿命试验的优化设计转化为显函数的约束极值求解问题,然后将智能优化算法应用到加速寿命试验的优化设计中,给出的算例结果说明了此方法的可行性与正确性。它相对于解析优化方法,易于优化算法的简化和流程化,满足了工程应用的需求。
The good or bad of Accelerated Life Test（ALT） plan directly influence cost and benefit of test and the accuracy of test result,so it is necessary to optimize the ALT plan,that is to say finding the optimized stress level and samples proportion makes the test result more precise and the cost more little.Using the continuity of goal function,a method that is a function fitting based on discrete data,makes the problem of ALT plan optimization design changed into a resolution of peak value with constraint conditions,and then the intelligent optimization algorithms is used to the ALT plan optimization.The result of an example given proves that this method is feasible and precise.Comparing with analytical optimization this method has many advantages which meets application requirements,such as it is easier to make the optimization algorithms simpler and processing flow.
出处
《火力与指挥控制》
CSCD
北大核心
2011年第9期203-206,共4页
Fire Control & Command Control
基金
国家自然科学基金资助项目(60472009)
关键词
加速寿命试验
试验优化设计
数据拟合
智能优化
Accelerated Life Tost（ALT）
optimization design of test plan
data fitting
intelligent optimization
