Linear Array Industrial Computerized Tomography Quantitative Detection Method for Small Defects Based on Coefficients of Variation

Abstract

A method for accurate and quantitative nondestructive testing of small defects inside metal components has been developed by experimentally investigating the grayscale distribution in computerized tomography (CT) images for a typical 304 stainless-steel material that is extensively used in industrial products. CT scans were performed as a function of the defect pore size. The grayscale level and the noise deviation distribution were measured in each CT image. The localized grayscale features where the defects are located in the CT image were studied using wavelet decomposition. A quantitative correlation between the defect size and the grayscale distribution in the CT images was established based on the coefficient of variation. The experimental findings, when combined with the advantages of an industrial CT detection method, allow for small defects to be characterized, imaged, and presented. The results show that the quantitative accuracy of this method is higher when compared with the traditional full-width at half-maximum method. The measurement process developed herein is simple and highly practicable and, furthermore, represents an effective way to characterize the size of small defects.

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Acknowledgments

This study was funded by the National Natural Science Foundation of China (61701446), Fund Project (JSZL2017208C001), Zhejiang Province Public Welfare Project (LGG20F010003), and Ningbo Science and Technology Service Demonstration Project (2019F1036).

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Correspondence to Zicheng Qi.

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Qi, Z., Ni, P., Jiang, W. et al. Linear Array Industrial Computerized Tomography Quantitative Detection Method for Small Defects Based on Coefficients of Variation. Journal of Elec Materi (2021). https://doi.org/10.1007/s11664-020-08704-8

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Keywords

  • Industrial computerized tomography
  • wavelet decomposition
  • coefficient of variation
  • small defect quantification