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Fast γ Photon Imaging for Inner Surface Defects Detecting
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DOI：10.3390/s21238134.png)
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Abstract
En 中文
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 gamma 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.
Keywords:
positron emission computed tomography
field-programmable gate array
iteration algorithm
internal defect detection
image reconstruction
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