Evaluation of probability of detection (POD) studies with multiple explanatory variables
Evaluation of probability of detection (POD) studies with multiple explanatory variables
复制标题
使用多个解释变量评估检测概率 (POD) 研究
DOI：
10.1080/00223131.2015.1064332
复制
发表时间：
2016
影响因子：
1.2
通讯作者：
J. Knopp
中科院分区：
文献类型：
--
作者：
N. Yusa;J. Knopp
这项研究提出了一种新的方法来评估检测概率(POD)作为一个以上的缺陷参数的函数。该方法的主要思想是假设由给定参数描述的缺陷引起的信号具有均值和标准差的正态分布，并使用通过数值模拟计算的信号和实验数据的组合来分别估计和。该方法不假定传统方法中发现的闭合形式，它使用最大似然分析来计算POD来评估表征分布的几个参数。这允许对不满足线性假设或恒方差假设的数据进行POD评估，而无需转换。通过对316L不锈钢焊缝缺陷产生的模拟涡流信号的分析，验证了该方法的有效性。验证结果表明，该方法可以给出缺陷深度和长度的置信限。结果还表明，与传统的分析方法相比，该方法不需要大量的实验数据。
This study proposes a new method to evaluate a probability of detection (POD) as a function of more than one flaw parameter. The main idea of the method is to assume that signals due to flaws described with a given parameter have a normal distribution of a mean of and a standard deviation of , and to use a combination of signals calculated by numerical simulations and experimental data to evaluate and , respectively. The method does not postulate a closed-form of found in conventional approaches, and it evaluates a few parameters that characterize the distribution using maximum likelihood analysis to calculate POD. This allows POD evaluation for data that does not satisfy linearity or constant variance assumptions without transformation. The proposed method is demonstrated through analyzing simulated eddy current signals due to flaws appearing in type 316L stainless steel welds. The results of the demonstration confirm that the proposed method can provide the POD with its confidence bounds as a function of the depth and the length of a flaw. The results also showed that the proposed method does not require a large amount of experimental data compared to conventional â vs. a analysis.