基于CoKriging代理模型的涡流无损检测模型辅助探测概率问题的研究  

Model-assisted probability of detection for eddy current nondestructive testing based on CoKriging surrogate model

作　　者：包扬[1] 仇家豪 Bao Yang;Qiu Jiahao(School of Electronic and Optical Engineering&School of Flexible Electronics(Future Technology),Nanjing University of Posts and Telecommunications,Nanjing 210003,China)

机构地区：[1]南京邮电大学电子与光学工程学院、柔性电子(未来技术)学院,南京210003

出　　处：《电子测量与仪器学报》2024年第9期136-143,共8页Journal of Electronic Measurement and Instrumentation

摘　　要：无损检测模型辅助探测概率问题的研究需要大量仿真数据,而高精度的物理模型计算模型响应需要大量时间,往往是无法实现的。代理模型是一种高效的数学模型,可以替代费时复杂的物理模型,广泛应用于设计优化问题。CoKriging模型可以融合高精度和低精度的数据,融合了大量计算成本低的低精度数据和少量计算成本高的高精度数据,提高了建模效率,是一种非常有应用潜力的代理模型。文中将CoKriging模型应用于涡流无损检测模型辅助探测概率的研究,在有限截面线圈探测金属平板表面槽缺陷算例中,利用物理模型计算部分训练点,构建CoKriging模型,精度验证通过后的CoKriging模型可以代替物理模型进行MAPoD分析,通过对比物理模型计算的MAPoD关键参数验证CoKriging模型的精度和效率。结果表明,相较于Kriging模型,CoKriging模型只需要更少的样本点训练模型就可以达到求解精度的要求,其构建元模型所需时间仅为Kriging元模型所需的7%,提高了涡流无损检测模型辅助探测概率研究的效率。The study of model assisted probability of detection in eddy current nondestructive testing requires a large amount of simulation data,while high-precision physical model calculations demand considerable time and are often impractical.The surrogate model is an efficient mathematical model that can replace time-consuming and complex physical models,and is widely used in design optimization problems.CoKriging,a model that fuses high and low-precision data,utilizes a large amount of low-cost and low-precision data,and a small amount of high-cost and high-precision data,which significantly improves the modeling efficiency over Kriging model.It is a very promising surrogate model.This article applies the CoKriging model to the study of the probability of detection aided by the eddy current nondestructive testing model.In the case of detecting groove defects on the surface of a metal plate using a finite-section coil,the CoKriging model is constructed using physical model calculations for some training points.After verifying the accuracy,the CoKriging model can replace the physical model for MAPoD analysis.By comparing the key parameters of MAPoD calculated by the physical model,the accuracy and efficiency of the CoKriging model are verified.The results show that compared with the Kriging model,the CoKriging model only requires fewer sample points to train the model to meet the defined accuracy requirements and in the best�performing example,its construction time is only 7%of that of the Kriging model,greatly improving the efficiency of the MAPoD.

关 键 词：涡流无损检测 代理模型 KRIGING模型 CoKriging模型 模型辅助探测概率 

分 类 号：TM93[电气工程—电力电子与电力传动]