Journal Published Online: 21 May 2024
Volume 52, Issue 4

Optimization of Weak Ultrasonic Defect Signal Detection of Carbon Fiber Composites Based on Double-Sided Pulse Reflection Scanning

CODEN: JTEVAB

Abstract

This paper presents a signal correlation–based two-sided detection method to detect delamination defects in widely used carbon fiber reinforced plastics with high accuracy and a convenient process. This method can improve the accuracy of ultrasonic testing and distinguish non-defective signals from defective signals, especially those with small amplitude, and to present the depth and size of defects by images. We combined the echo signals from both sides of ultrasonic detection at the same location to extract the weak defect signals and achieved the detection of materials with high ultrasonic attenuation. First, empirical mode decomposition filtering is performed on the ultrasonic raw signal. Then, the defect echoes are identified by smart thresholding and combined with the results of ultrasonic detection on both sides. Next, the defect depth and size are calculated, and the defect image is drawn. Finally, the ultrasonic phased array C-scan obtained by the ultrasonic phased array equipment was compared with the detection results of carbon fiber laminates with artificial delamination by the algorithm of the present invention, showing that the proposed algorithm defect depth calculation error is less than 4 %, the defect size calculation error is less than 0.5 mm, and it performs well in defect shape presentation and position calculation.

Author Information

Ma, Mengyuan
School of Control Science and Engineering, Shandong University, Jinan, Shandong, China
Jiang, Mingshun
School of Control Science and Engineering, Shandong University, Jinan, Shandong, China
Zhang, Lei
School of Control Science and Engineering, Shandong University, Jinan, Shandong, China
Sui, Qingmei
School of Control Science and Engineering, Shandong University, Jinan, Shandong, China
Jia, Lei
School of Control Science and Engineering, Shandong University, Jinan, Shandong, China
Pages: 15
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Stock #: JTE20230149
ISSN: 0090-3973
DOI: 10.1520/JTE20230149