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The present study delved into the effect of impactor diameter on low velocity impact response and damage characteristics of CFRP. Moreover, the phased array ultrasonic technique (PAUT) was adopted to identify the impact damages based on double-sided scanning. Low-velocity impact tests were carried out using three hemispherical impactors with different diameters. The relationship of impact response and impactor diameters was analyzed by ultrasonic C-scans and S-scans, combined with impact response parameters. Subsequently, the damage characteristics were assessed in terms of dent depth, delamination area and extension shape via the thickness, and the relationships between absorbed energy, impactor displacement, dent depth and delamination area were elucidated. As revealed from experiment results, double-sided PAUT is capable of representing the internal damage characteristics more accurately. Moreover, the impactor diameter slightly affects the impact response under small impact energy, whereas it significantly affects the impact response under large impact energy.

This paper presents a method based on signal correlation to detect delamination defects of widely used carbon fiber reinforced plastic with high precision and a convenient process. The objective of it consists in distinguishing defect and non-defect signals and presenting the depth and size of defects by image. A necessary reference signal is generated from the non-defect area by using autocorrelation theory firstly. Through the correlation calculation results, the defect signal and non-defect signal are distinguished by using Euclidean distance. In order to get more accurate time-of-flight, cubic spline interpolation is introduced. In practical automatic ultrasonic A-scan signal processing, signal correlation provide a new way to avoid problems such as signal peak tracking and complex gate setting. Finally, the detection results of a carbon fiber laminate with artificial delamination through ultrasonic phased array C-scan acquired from Olympus OmniScan MX2 and this proposed algorithm are compared, which showing that this proposed algorithm performs well in defect shape presentation and location calculation. The experiment shows that the defect size error is less than 4%, the depth error less than 3%. Compared with ultrasonic C-scan method, this proposed method needs less inspector’s prior-knowledge, which can lead to advantages in automatic ultrasonic testing.