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12 December 2024 Defect detection of CNG cylinders based on ultrasonic pulse echo method and improved HRNet
Yuhu Fang, Fei Wang, Qingkun He, Yu Ding, Yu Zhou
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Proceedings Volume 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024); 134392A (2024) https://doi.org/10.1117/12.3055483
Event: Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 2024, Xiamen, China
Abstract
Ultrasonic testing is a commonly used non-destructive testing technology that utilizes the propagation characteristics of high-frequency sound waves in materials to detect and evaluate their internal structure, defects, and integrity. Due to its high sensitivity and non-destructive nature, ultrasonic testing is suitable for detecting defects in cylinders. This paper designs a defect detection method for CNG cylinders based on the ultrasonic pulse echo method and HRNet. First, a comprehensive scan of the CNG cylinder is conducted using the ultrasonic pulse echo method. After obtaining the scan results, the Kalman filtering method is used to remove noise interference, resulting in a more accurate waveform. An improved HRNet is then utilized for defect target detection. The main improvement of HRNet lies in using global and local feature fusion to achieve higher precision defect identification and introducing the ASPP module to enhance the network's feature extraction and anti-interference capabilities. In experiments, the method can effectively identify groove-type defects and corrosion defects in CNG cylinders.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yuhu Fang, Fei Wang, Qingkun He, Yu Ding, and Yu Zhou "Defect detection of CNG cylinders based on ultrasonic pulse echo method and improved HRNet", Proc. SPIE 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 134392A (12 December 2024); https://doi.org/10.1117/12.3055483
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KEYWORDS
Ultrasonics
Defect detection
Feature extraction
Signal processing
Signal filtering
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