by Garavelli, B., Pozzi, P., Macera, D., Zanotti, L. and Mencarelli, A., Bubba, G., Bertoni, P., Sammartini, M. and Bettelli, M., Bertuccio, G., Ghiringhelli, G. and Zappettini, A.
Abstract:
An innovative X-ray inspection technology, named XSpectra (R), has been developed with the aim to improve the current state of art in the field of real-time detection of contaminants in food products on production lines. The technology architecture is based on modules equipped with a 128 pixels CdTe array detector each read-out by full-custom Front-End ASICs. A full-custom Multi-Channel-Analyzer reconstructs the radiation spectrum, which is then processed by advanced Neural Network algorithms performing both image reconstruction and foreign bodies detection. The experimental characterization of XSpectra (R) has demonstrated the sensitivity of the fully operating system to photon energies down to about 10 keV at events rates up to several millions of photons per second. A line-width of 8.5 keV FWHM has been measured, at room temperature, on the 60 keV photo-peak of a synchrotron radiation in low-rate conditions. A spectral non-linearity error within +/- 0.5% has been obtained within the energy range 25 keV -100 keV. The effective capability of XSpectra (R) to detect currently undetectable low-density contaminants inside real food products has also been proved.
Reference:
XSpectra (R): an Advanced Real-Time Food Contaminants Detector (Garavelli, B., Pozzi, P., Macera, D., Zanotti, L. and Mencarelli, A., Bubba, G., Bertoni, P., Sammartini, M. and Bettelli, M., Bertuccio, G., Ghiringhelli, G. and Zappettini, A.), In 2019 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE (NSS/MIC), IEEE, 2019.
Bibtex Entry:
@inproceedings{ ISI:000569982800221, Author = {Garavelli, B. and Pozzi, P. and Macera, D. and Zanotti, L. and Mencarelli, A. and Bubba, G. and Bertoni, P. and Sammartini, M. and Bettelli, M. and Bertuccio, G. and Ghiringhelli, G. and Zappettini, A.}, Book-Group-Author = {{IEEE}}, Title = {{XSpectra (R): an Advanced Real-Time Food Contaminants Detector}}, Booktitle = {{2019 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE (NSS/MIC)}}, Series = {{IEEE Nuclear Science Symposium and Medical Imaging Conference}}, Year = {{2019}}, Note = {{IEEE Nuclear Science Symposium / Medical Imaging Conference (NSS/MIC), Manchester, ENGLAND, OCT 26-NOV 02, 2019}}, Organization = {{IEEE}}, Abstract = {{An innovative X-ray inspection technology, named XSpectra (R), has been developed with the aim to improve the current state of art in the field of real-time detection of contaminants in food products on production lines. The technology architecture is based on modules equipped with a 128 pixels CdTe array detector each read-out by full-custom Front-End ASICs. A full-custom Multi-Channel-Analyzer reconstructs the radiation spectrum, which is then processed by advanced Neural Network algorithms performing both image reconstruction and foreign bodies detection. The experimental characterization of XSpectra (R) has demonstrated the sensitivity of the fully operating system to photon energies down to about 10 keV at events rates up to several millions of photons per second. A line-width of 8.5 keV FWHM has been measured, at room temperature, on the 60 keV photo-peak of a synchrotron radiation in low-rate conditions. A spectral non-linearity error within +/- 0.5% has been obtained within the energy range 25 keV -100 keV. The effective capability of XSpectra (R) to detect currently undetectable low-density contaminants inside real food products has also been proved.}}, Publisher = {{IEEE}}, Address = {{345 E 47TH ST, NEW YORK, NY 10017 USA}}, Type = {{Proceedings Paper}}, Language = {{English}}, Affiliation = {{Garavelli, B (Corresponding Author), Xnext Srl, Via Adelaide Bono Cairoli 30, I-20127 Milan, Italy. Garavelli, B.; Pozzi, P.; Macera, D.; Zanotti, L.; Mencarelli, A.; Bubba, G.; Bertoni, P., Xnext Srl, Via Adelaide Bono Cairoli 30, I-20127 Milan, Italy. Zanotti, L., ASML, Eindhoven, North Brabant P, Netherlands. Sammartini, M.; Bertuccio, G.; Ghiringhelli, G., Politecn Milan, Piazza Leonardo da Vinci 32, I-20133 Milan, Italy. Bettelli, M.; Zappettini, A., IMEM CNR, Parco Area Sci 37-A, I-43124 Parma, Italy.}}, ISSN = {{1095-7863}}, ISBN = {{978-1-7281-4164-0}}, Keywords = {{Non-destructive-test X-ray equipment; CdTe detectors; Multi-spectral analysis}}, Research-Areas = {{Nuclear Science & Technology; Radiology, Nuclear Medicine & Medical Imaging}}, Web-of-Science-Categories = {{Nuclear Science & Technology; Radiology, Nuclear Medicine & Medical Imaging}}, Number-of-Cited-References = {{0}}, Times-Cited = {{0}}, Usage-Count-Last-180-days = {{0}}, Usage-Count-Since-2013 = {{0}}, Doc-Delivery-Number = {{BP9NR}}, Unique-ID = {{ISI:000569982800221}}, DA = {{2020-12-22}}, }
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