Article Details

Abstract

To address the lack of standardized quantitative evaluation methods for the imaging quality of ultrasonic C-scan equipment and the assessment deviations easily caused by the irregular shapes of natural defects, this study takes the adhesive layer of rail transit vehicle window glass as the research object and investigates an imaging quality evaluation method. A dedicated ultrasonic C-scan detection system is built, and test blocks containing circular artificial defects with diameters of 7–10 mm are prepared; two types of quantitative evaluation parameters, namely the image distortion coefficient and the scanning axis mechanical error coefficient, are constructed. Median filtering and histogram equalization are adopted for preprocessing, the Otsu algorithm and the Canny operator are used to extract defect edges, and Andrew's monotone chain algorithm combined with the convex hull deviation method is used to detect convex and concave feature points on the edges, thereby completing the calculation and analysis of the feature parameters. Experimental results show that the coefficient of variation of the image distortion coefficient is 1.29% and that of the scanning axis mechanical error coefficient is 15.90%. The proposed method can quantify imaging distortion and mechanical scanning errors, achieve objective quantitative evaluation of imaging quality, provide a standardized solution for the performance verification and parameter optimization of ultrasonic C-scan equipment, and support the application of ultrasonic non-destructive testing in precision components of rail transit.

Keywords

ultrasonic C-scan; imaging quality assessment; edge detection; convex and concave point detection; feature parameter

References

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About the authors

Zhang Zhenyang (2000-), male, Han ethnicity, from Xuzhou, Jiangsu, master's student, research interests include ultrasonic non-destructive testing.