Fast γ Photon Imaging for Inner Surface Defects Detecting
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...
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          | Published in | Sensors (Basel, Switzerland) Vol. 21; no. 23; p. 8134 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
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        05.12.2021
     MDPI  | 
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| Online Access | Get full text | 
| ISSN | 1424-8220 1424-8220  | 
| DOI | 10.3390/s21238134 | 
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| Abstract | 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. | 
    
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| AbstractList | 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. 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.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.  | 
    
| Author | Liu, Jian Zhao, Min Guo, Ruipeng Luo, Guangdong Yao, Min  | 
    
| AuthorAffiliation | 1 College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; guangdong@nuaa.edu.cn (G.L.); zhaomin2@nuaa.edu.cn (M.Z.); rpguo@nuaa.edu.cn (R.G.); jliu@nuaa.edu.cn (J.L.) 2 Nondestructive Detection and Monitoring Technology for High Speed Transportation Facilities, Key Laboratory of Ministry of Industry and Information Technolog, Nanjing 210016, China  | 
    
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| Cites_doi | 10.1109/ACCESS.2020.3016674 10.1016/j.phpro.2012.05.122 10.1063/5.0006104 10.1784/insi.2016.58.11.617 10.1049/cje.2021.08.001 10.1088/1674-1056/24/1/018702 10.1109/ACCESS.2020.3038661 10.1109/ICCSCE.2016.7893538 10.1063/1.5042043 10.1016/j.compositesb.2021.109167 10.1109/TBCAS.2015.2471813 10.3390/jimaging5010016 10.1016/j.ces.2019.05.020 10.1371/journal.pone.0138498 10.1002/app.51296 10.1007/s11554-016-0563-5 10.1088/1361-6560/abc09d 10.1088/0031-9155/55/11/012 10.1142/S2010194518601138 10.1016/j.radphyschem.2021.109690 10.1016/j.nucengdes.2016.01.017  | 
    
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| SubjectTerms | Acoustic emission testing Algorithms field-programmable gate array Flow velocity Fourier transforms image reconstruction internal defect detection iteration algorithm positron emission computed tomography  | 
    
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| Title | Fast γ Photon Imaging for Inner Surface Defects Detecting | 
    
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