退化模型确认试验是评估退化模型可信度的一种试验。为了得到低成本、高可信度的退化模型确认试验方案，提出了一种基于随机过程的退化模型确认试验设计方法。首先，提出了一种基于随机过程的退化模型确认度量指标，该度量指标采用仿真响应和试验观测数据的概率密度函数在时域内的重合率。其中，试验数据的概率密度采用核密度估计，以减小试验样本不充足时样本数量对确认结果的影响。然后，建立了退化模型确认试验优化设计模型，该优化模型以试验成本为优化目标，确认度量指标为约束，并且同时考虑了试验样本数量、试验观测时刻数量和试验观测时刻分布的影响。随后，提出一种求解该优化模型的协同优化方法。最后，通过复合材料层压板案例验证了提出方法在工程应用中的可行性和有效性。
Abstract
Validation experiment of degradation model is a new type of experiment, which is used to determine the credibility of the degradation model. In order to obtain low cost and high credibility of validation experiment for degradation model, a methodology of validation experiment design for degradation model based on stochastic process is proposed. Firstly, a validation metric for degradation model based on stochastic process is presented, in which the coincidence rate between the probability density functions (PDFs) of the results of the simulation model and the PDFs of the experimental observations in the time domain is applied. In particular, kernel density estimation is used to obtain the PDFs from experimental data, which reduces the error of the metric in small sample case. Furthermore, an optimization model of validation experiment design for degradation model is constructed, in which the experimental cost is the optimization objective, the validation metric is the constraint, while the influences of the number of experimental samples, the number and distribution of observation instants are considered. Meanwhile, a collaborative optimization algorithm is developed to solve the optimization model. Finally, the composite laminated plate is demonstrated to verify the feasibility and effectiveness of the proposed method in engineering applications.
关键词
确认试验 /
退化模型 /
随机过程 /
核密度估计
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Key words
validation experiment /
degradation model /
stochastic process /
kernel density estimation
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