A method of predicting visual detectability of low-velocity impact damage in composite structures based on logistic regression model
Fengyang Jiang, Zhidong Guan, Zengshan Li, Xiaodong Wang
Abstract
This paper proposed a new method for quantitative assessment of visual detectability of damage based on logistic regression, using the Probability of Detection (POD) as a criterion. Experiments were performed to establish the massive hit/miss data of visual inspection. Authoritative investigations verified the reliability of the data. The prediction function concluded comprises more than one flaw size parameters, including the depth and diameter of the dents. The results show that the depth and diameter of the dents are pivotal for the evaluation of detectability; the type of detection, the detection distance, and the qualifications of personnel are critical external factors to be considered. This function, with an accuracy rate of nearly 85%, is capable of predicting the visual detection probability of impact damage under various detection environments, which will provide a reference for the damage tolerance design of composite materials and field maintenance in the Non-Destructive Testing (NDT) field.