Fast γ Photon Imaging for Inner Surface Defects Detecting

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 23; p. 8134
• Main Authors: Yao, Min, Luo, Guangdong, Zhao, Min, Guo, Ruipeng, Liu, Jian
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 05.12.2021; MDPI
• Subjects: Acoustic emission testing; Algorithms; Computed tomography; Corrosion prevention; Edge detection; Field programmable gate arrays; field-programmable gate array; Flow velocity; Fourier transforms; Image quality; image reconstruction; internal defect detection; iteration algorithm; Measurement methods; Photons; Positron emission; positron emission computed tomography; Surface defects; Tomography
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s21238134

Only a few effective methods can detect internal defects and monitor the internal state of complex structural parts. On the basis of the principle of PET (positron emission computed tomography), a new measurement method, using γ photon to detect defects of an inner surface, is proposed. This method has the characteristics of strong penetration, anti-corrosion and anti-interference. With the aim of improving detection accuracy and imaging speed, this study also proposes image reconstruction algorithms, combining the classic FBP (filtered back projection) with MLEM (maximum likelihood expectation Maximization) algorithm. The proposed scheme can reduce the number of iterations required, when imaging, to achieve the same image quality. According to the operational demands of FPGAs (field-programmable gate array), a BPML (back projection maximum likelihood) algorithm is adapted to the structural characteristics of an FPGA, which makes it feasible to test the proposed algorithms therein. Furthermore, edge detection and defect recognition are conducted after reconstructing the inner image. The effectiveness and superiority of the algorithm are verified, and the performance of the FPGA is evaluated by the experiments.