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Automatic geometry calibration based on metric optimization in stationary computed tomography baggage scanner with 2-angle sparsity

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 C03032-C03032页

作者： Shim, Jiyong Kim, Woosung Jeon, Duhee Cho, Hyosung Yonsei Univ Dept Radiat Convergence Engn Wonju South Korea

Recently, SSTLabs Co. in Korea has designed and developed a stationary computed tomography (SCT) baggage scanner with 2t-angle sparsity, comprising 20 pairs of monoblock-type X-ray sources and linear array-type dual-layer detectors arranged within a scan angle of 360 degrees at an equiangular distance. We implemented an SCT reconstruction method for a specific (i.e., very sparse-view) system configuration by adopting an iterative algorithm based on the popular compressed- sensing (CS) mathematical theory. However, the method exhibited poor reconstruction quality owing to the mismatch in scan parameters between the nominal (designed) and actual values used during reconstruction. To overcome this limitation, we propose a pragmatic geometric calibration method based on a metric optimization technique for the mean structural similarity index measure to ensure high-quality CS-reconstructed images from the developed SCT baggage scanner. To verify the efficacy of the proposed method, we conducted a numerical simulation and experiments before its practical implementation and found no significant image distortion and edge blur in the SCT images reconstructed with the proposed geometric calibration, except for artifacts stemming from sparse-view angular sampling. The measured signal-to-noise ratio, contrast-to-noise ratio, and mean square error values between the calibrated and corresponding phantom slice images were improved by approximately 5.2-, 7.4-, and 3.5-fold, respectively, compared to those for the uncalibrated images, demonstrating the efficacy of the proposed geometric calibration method. Furthermore, the proposed method is self-operating and thus does not require a geometric calibration phantom.

关键词： Computerized Tomography (CT) and Computed Radiography (CR) Detection of explosives Inspection with x-rays pattern recognition, cluster finding, calibration and fitting methods

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A temperature-adaptive neutron-gamma discrimination algorithm for NaIL detector using a one-dimensional Convolutional Neural Network

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 P03032-P03032页

作者： Zhou, Yulong Zheng, Zekun Duan, Han Zhao, Chaoyang Wang, Zhonghai Sichuan Univ Coll Phys 29 Wangjiang Rd Chengdu 610065 Peoples R China Sichuan Univ Key Lab Radiat Phys & Technol Minist Educ 29 Wangjiang Rd Chengdu 610065 Peoples R China

Both the NaIL scintillator and silicon photomultiplier (SiPM) are susceptible to temperature fluctuations, which could change the characteristics of detected neutron and gamma waveforms result in significant drift in the pulse shape discrimination (PSD) values with fixed PSD algorithm parameters, causing false alarms or missed alarms. This paper investigates a temperature-adaptive neutron-gamma discrimination algorithm using a one-dimensional convolutional neural network (1D-CNN). This algorithm can discriminate mixed neutron-gamma data automatically at various temperatures, rather than adjusting algorithm parameters manually as in the conventional methods. The performance of this algorithm is evaluated using a laboratory-developed NaIL+SiPM detector and compared with the Charge Integration Method (CIM) and the Fully Connected Neural Network (Fc-NN). The discrimination accuracy of the algorithm exceeds 99.96% for data across all temperatures, encompassing both temperatures included in the training set and those outside of it. The area the curve (AUC) metric of the receiver operating characteristic (ROC) curve consistently exceeds 0.999 across different temperatures, with FAR consistently below 0.1%, indicating that the algorithm is not significantly affected by temperature variations. The algorithm exhibits robust neutron-gamma discrimination capabilities and excellent generalizability at different temperatures, making it suitable real-time neutron-gamma discrimination scenarios where temperature conditions are subject to change.

关键词： pattern recognition, cluster finding, calibration and fitting methods Gamma (scintillators, CZT, HPGe, HgI etc) Neutron detectors (cold, thermal, fast neutrons)

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A regression algorithm for the retrieval of wet troposphere path delay from dual-channel water vapor radiometer measurements

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 P03020-P03020页

作者： Sun, Shijie Xiong, Zhengdong Lu, Yihuai Chenga, Tingqing Jiang, Haihe Chinese Acad Sci Hefei Inst Phys Sci Anhui Prov Key Lab Med Phys & Technol Inst Hlth & Med Technol Hefei 230031 Peoples R China Univ Sci & Technol China Hefei 230026 Anhui Peoples R China Anhui Univ Chinese Med Sch Med Informat Engn Hefei 230012 Peoples R China Hefei Comprehens Natl Sci Ctr Inst Environm Hefei 230601 Peoples R China

The dual-channel water vapor radiometer provides a real-time tropospheric wet delay for electromagnetic signal delay calibration by measuring atmospheric radiation signals. This paper introduces the linear regression algorithm (LRA) inversion method for improving the accuracy of the zenith wet delay (ZWD) values from water vapor radiometers. Compared to the traditional fixed coefficient algorithm (FCA), which has previously been applied for ZWD retrieval, LRA can improve the accuracy of ZWD retrieval performance from water vapor radiometer measurements in different seasons. LRA has a greater capacity to describe the relationship between water vapor radiometer measurement and atmospheric refractive structure information. Compared with the ZWD obtained from radiosonde data, the root mean square error of the ZWD using LRA was 1.77 mm for the tested year. This research contains a detailed comparison of LRA and the traditional FCA using the same test datasets. The comparison demonstrates that the LRA significantly improves the ZWD accuracy, particularly in seasons with high water vapor content.

关键词： Microwave radiometers pattern recognition, cluster finding, calibration and fitting methods Microwave Calibrators Radiation calculations

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Feature extraction on the TRD readout FPGA with HLS in the mCBM experiment

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 C03047-C03047页

作者： Schledt, D. Blume, C. Kebschull, U. Goethe Univ Frankfurt Max Von Laue Str 1 D-60438 Frankfurt Germany

The CBM experiment uses a free streaming DAQ with interaction rates up to 10MHz resulting in data rates, which exceed storage capabilities, necessitating online processing. The SPADIC ASIC of the CBM-TRD provides hit messages with oscilloscope-like sampling of the detector data, encoding valuable information. To speed up data unpacking and computing time, feature extraction is moved to the readout FPGA. In the mCBM experiment this approach is tested, demonstrating the benefits of HLS and C++ template programming for algorithm development. Results show resolution improvements and significant reductions in data volume and unpacking speed at the computing cluster.

关键词： Data processing methods Data acquisition concepts Digital signal processing (DSP) pattern recognition, cluster finding, calibration and fitting methods

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A space-time tracking algorithm for high occupancy events at future colliders

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JOURNAL OF INSTRUMENTATION 2025年第4期20卷

作者： Casarsa, Massimo Jindariani, Sergo Ristori, Luciano INFN Sez Trieste via A Valerio 2 I-34127 Trieste Italy Fermilab Natl Accelerator Lab POB 500 Batavia IL 60510 USA

We propose to explore the potential advantages of a new class of tracking algorithms loosely inspired by the Hough transform concept and where we include the time of arrival of each hit as an additional coordinate to be treated in the same way as a spatial coordinate. A remarkable property of this algorithm is that the execution time is proportional to the total number of hits to be processed, making it particularly attractive for high occupancy situations expected at future colliders. The particular structure of the algorithm also lends itself naturally to parallel hardware implementations which, combined to its intrinsic flexibility, should provide a powerful tool for triggering at future colliders. To probe the effectiveness of the algorithm, we apply it to a quasi-realistic simulated environment of a possible future muon collider experiment and report the performance.

关键词： Data processing methods pattern recognition, cluster finding, calibration and fitting methods Trigger algorithms

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Lightweight rotating machinery fault diagnosis based on quadratic convolutional neural network and evidence fusion of multi-source sensor information

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JOURNAL OF INSTRUMENTATION 2025年第2期20卷 P02019-P02019页

作者： Wang, Shanshan Han, Wenkang Zhang, Hao Zeng, Liang Hubei Univ Technol Sch Elect & Elect Engn Wuhan 430068 Hubei Peoples R China Hubei Univ Technol Hubei Key Lab High Efficiency Utilizat Solar Energ Wuhan 430068 Peoples R China

Rotating machinery is the core component of various modern equipment. Timely and accurate fault detection is of great significance to ensure the safe operation of mechanical equipment and the stability of production efficiency. Deep learning-based methods have triggered a boom in the field of machinery fault diagnosis. However, due to factors such as noise interference in industrial applications, an increase in accuracy is often accompanied by an increase in computational cost, leading to difficulties in deploying the model in engineering applications. In order to find a balance between robustness and complexity, this paper proposes a lightweight intelligent fault diagnosis framework called (QSMC-EFN). Firstly, a new nonlinear quadratic neural network is used to extract features initially and then combined with a multiscale separable convolutional block to extract multiscale features of the vibration signal. Different features from multiple scales are subsequently fused using a statistical Dempster-Shafer (DS) theory of evidence, fed into a lightweight feature extraction layer consisting of multi-scale separated convolution and broadcast attention mechanisms to gain further the ability to extract more critical features. Through experiments on the planetary gearbox and variable speed bearing datasets, it is verified that the proposed fault diagnosis system ensures effectiveness while also achieving a lightweight model.

关键词： Detection of defects Manufacturing Overall mechanics design (support structures and materials, vibration analysis etc) pattern recognition, cluster finding, calibration and fitting methods

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A geometrical calibration method for the PIXSCAN micro-CT scanner

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JOURNAL OF INSTRUMENTATION 2009年第7期4卷 P07016-P07016页

作者： Khoury, R. Bonissent, A. Clements, J. C. Meessen, C. Vigeolas, E. Billault, M. Morel, C. CNRS CPPM IN2P3 F-13288 Marseille 9 France Univ Aix Marseille 2 F-13288 Marseille 9 France

Reconstruction in Cone-Beam Tomography can suffer from artifacts due to geometrical misalignments of the source-detector system. They can be avoided by a complete and precise description of the system. We present a high precision method for the geometric calibration for the PIXSCAN, a small animal X-ray CT scanner demonstrator based on hybrid pixel detectors (XPAD2). The specificities of the XPAD2 detectors (dead pixels, tilts and gaps between modules...) made the calibration of the PIXSCAN quite difficult. The method uses a calibration object consisting of a hollow cylinder of polycarbonate on which we positioned four metallic balls. It requires 360 X-ray images (1 degrees increments). An analytic expression of the 3 image ellipses has been derived. It is used for a least square regression of the 13 alignment parameters after a correction of the internal XPAD2 geometry. Our method is fast and completely automated, achieving a precision of about 30 mu m.

关键词： X-ray detectors Computerized Tomography (CT) and Computed Radiography (CR) Detector alignment and calibration methods (lasers, sources, particle-beams) pattern recognition, cluster finding, calibration and fitting methods

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Transport of covariance matrices in the inhomogeneous magnetic field of the ATLAS experiment by the application of a semi-analytical method

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JOURNAL OF INSTRUMENTATION 2009年第4期4卷 P04016-P04016页

作者： Lund, E. Bugge, L. Gavrilenko, I. Strandlie, A. Univ Oslo N-0316 Oslo Norway CERN European Org Nucl Res CH-1211 Geneva 23 Switzerland PN Lebedev Phys Inst Moscow 117924 Russia Gjovik Univ Coll N-2802 Gjovik Norway

In this paper we study the transport of track parameter covariance matrices - the so-called error propagation - in the inhomogeneous magnetic field of the ATLAS experiment. The Jacobian elements are transported in parallel with the track parameters, avoiding the inherent need of any purely numerical scheme of propagating a set of auxiliary tracks. We evaluate the quality of the transported Jacobians by a very thorough, purely numerical approach of obtaining the same derivatives, providing a quantitative understanding of the effects of including gradients of energy loss and the magnetic field on the accuracy of the error propagation. Irrespective of the accuracy of the underlying track parameter propagation, the method of parallel integration of the derivatives is demonstrated to be significantly faster than even the simplest numerical scheme. The error propagation presented in this paper is part of the simultaneous track and error propagation ( STEP) algorithm of the common ATLAS tracking software.

关键词： pattern recognition, cluster finding, calibration and fitting methods Simulation methods and programs Data processing methods

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Precision luminosity measurements at LHCb

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JOURNAL OF INSTRUMENTATION 2014年第12期9卷 P12005-P12005页

作者： Aaij, R. Adeva, B. Adinolfi, M. Affolder, A. Ajaltouni, Z. Akar, S. Albrecht, J. Alessio, F. Alexander, M. Ali, S. Alkhazov, G. Alvarez Cartelle, P. Alves, A. A., Jr. Amato, S. Amerio, S. Amhis, Y. An, L. Anderlini, L. Anderson, J. Andreassen, R. Andreotti, M. Andrews, J. E. Appleby, R. B. Gutierrez, O. Aquines Archilli, F. Artamonov, A. Artuso, M. Aslanides, E. Auriemma, G. Baalouch, M. Bachmann, S. Back, J. J. Badalov, A. Baesso, C. Baldini, W. Barlow, R. J. Barschel, C. Barsuk, S. Barter, W. Batozskaya, V. Battista, V. Bay, A. Beaucourt, L. Beddow, J. Bedeschi, F. Bediaga, I. Belogurov, S. Belous, K. Belyaev, I. Ben-Haim, E. Bencivenni, G. Benson, S. Benton, J. Berezhnoy, A. Bernet, R. Bettler, M. -O. van Beuzekom, M. Bien, A. Bifani, S. Bird, T. Bizzeti, A. Bjornstad, P. M. Blake, T. Blanc, F. Blouw, J. Blusk, S. Bocci, V. Bondar, A. Bondar, N. Bonivento, W. Borghi, S. Borgia, A. Borsato, M. Bowcock, T. J. V. Bowen, E. Bozzi, C. Brambach, T. Bressieux, J. Brett, D. Britsch, M. Britton, T. Brodzicka, J. Brook, N. H. Brown, H. Bursche, A. Buytaert, J. Cadeddu, S. Calabrese, R. Calvi, M. Calvo Gomez, M. Campana, P. Perez, D. Campora Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carson, L. Carvalho Akiba, K. Casse, G. Cassina, L. Garcia, L. Castillo Cattaneo, M. Cauet, Ch. Cenci, R. Charles, M. Charpentier, Ph. Chefdeville, M. Chen, S. Cheung, S. -F. Chiapolini, N. Chrzaszcz, M. Ciba, K. Vidal, X. Cid Ciezarek, G. Clarke, P. E. L. Clemencic, M. Cliff, H. V. Closier, J. Coco, V. Cogan, J. Cogneras, E. Cojocariu, L. Collazuol, G. Collins, P. Comerma-Montells, A. Contu, A. Cook, A. Coombes, M. Coquereau, S. Corti, G. Corvo, M. Counts, I. Couturier, B. Cowan, G. A. Craik, D. C. Cruz Torres, M. Cunliffe, S. Currie, R. D'Ambrosio, C. Dalseno, J. David, P. David, P. N. Y. Davis, A. De Bruyn, K. De Capua, S. De Cian, M. De Miranda, J. M. De Paula, L. De Silva, W. De Simone, P. Dean, C. -T. Decamp, D. Deckenhoff, M. Del Buono, L. Deleage, N. Derkach, D. Deschamps, O. Dettori, F. Di Canto, A. Dijkstra, H. Donleavy, S. CBPF Rio De Janeiro Brazil Univ Fed Rio de Janeiro Rio De Janeiro Brazil Tsinghua Univ Ctr High Energy Phys Beijing 100084 Peoples R China Univ Savoie CNRS IN2P3 LAPP Annecy Le Vieux France Univ Blaise Pascal Clermont Univ CNRS IN2P3LPC Clermont Ferrand France Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Univ Paris 11 CNRS IN2P3 LAL F-91405 Orsay France Univ Paris Diderot Univ Paris 06 CNRS IN2P3LPNHE Paris France Tech Univ Dortmund Fak Phys Dortmund Germany Max Planck Inst Kernphys D-69117 Heidelberg Germany Heidelberg Univ Inst Phys Heidelberg Germany Univ Coll Dublin Sch Phys Dublin 2 Ireland Sez INFN Bari Bari Italy Sez INFN Bologna Bologna Italy Sez INFN Cagliari Cagliari Italy Sez INFN Ferrara Ferrara Italy Sez INFN Firenze I-50125 Florence Italy Ist Nazl Fis Nucl Lab Nazl Frascati I-00044 Frascati Italy Sez INFN Genova Genoa Italy Sez INFN Milano Bicocca I-20133 Milan Italy Sez INFN Milano I-20133 Milan Italy Sez INFN Padova Padua Italy Sez INFN Pisa Pisa Italy Sez INFN Roma Tor Vergata Rome Italy Sez INFN Roma La Sapienza Rome Italy Polish Acad Sci Henryk Niewodniczanski Inst Nucl Phys Krakow Poland AGH Univ Sci & Technol Fac Phys & Appl Comp Sci Krakow Poland Natl Ctr Nucl Res NCBJ Warsaw Poland Horia Hulubei Natl Inst Phys & Nucl Engn Bucharest Romania PNPI Gatchina Russia Inst Theoret & Expt Phys Moscow 117259 Russia Moscow MV Lomonosov State Univ SINP Inst Nucl Phys Moscow Russia Russian Acad Sci Inst Nucl Res RAN Moscow 117312 Russia Budker Inst Nucl Phys SB RAS Novosibirsk 630090 Russia Novosibirsk State Univ Novosibirsk 630090 Russia Inst High Energy Phys Protvino Russia Univ Barcelona Barcelona Spain Univ Santiago Compostela Santiago De Compostela Spain CERN European Org Nucl Res CH-1211 Geneva Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland Univ Zurich Inst Phys Zurich Switzerland Nikhef Natl Inst Subatom Phys Amsterdam Netherlands Vrije Univ Amsterdam Amsterdam

Measuring cross-sections at the LHC requires the luminosity to be determined accurately at each centre-of-mass energy root s. In this paper results are reported from the luminosity calibrations carried out at the LHC interaction point 8 with the LHCb detector for root s = 2.76, 7 and 8TeV (proton-proton collisions) and for root s(NN) = 5TeV (proton-lead collisions). Both the "van der Meer scan" and "beam-gas imaging" luminosity calibration methods were employed. It is observed that the beam density profile cannot always be described by a function that is factorizable in the two transverse coordinates. The introduction of a two-dimensional description of the beams improves significantly the consistency of the results. For proton-proton interactions at root s = 8TeV a relative precision of the luminosity calibration of 1.47% is obtained using van der Meer scans and 1.43% using beam-gas imaging, resulting in a combined precision of 1.12%. Applying the calibration to the full data set determines the luminosity with a precision of 1.16%. This represents the most precise luminosity measurement achieved so far at a bunched-beam hadron collider.

关键词： pattern recognition, cluster finding, calibration and fitting methods Instrumentation for particle accelerators and storage rings - high energy (linear accelerators, synchrotrons)

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Artificial neural networks-based track fitting of cosmic muons through stacked resistive plate chambers

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JOURNAL OF INSTRUMENTATION 2018年第10期13卷 P10035-P10035页

作者： Samuel, D. Suresh, K. Cent Univ Karnataka Kalaburagi 585367 Karnataka India

The India-based Neutrino Observatory (INO) collaboration, as part of its detector R&D program, has developed prototype stacks of resistive plate chambers (RPCs) to study their performance. These stacks have also been used as testbenches for the development of related hardware and software. A crucial parameter in the characterisation of these detectors and other physics studies is the detection efficiency, which is estimated from track fitting of cosmic muons passing through the stack. So far, a simple straight line fit was used for track fitting, which was sensitive to noise hits and led to rejection of events. In this paper, we present our first results of using artificial neural networks (ANN) for track fitting of cosmic muons traversing a stack of RPCs. We present in detail, the simulation framework designed for this purpose and show that an ANN offers better track reconstruction efficiency than straight line fitting. We also discuss the influence of noise and detection efficiency of cosmic muons on the track reconstruction efficiency.

关键词： Neutrino detectors pattern recognition, cluster finding, calibration and fitting methods Resistive-plate chambers Simulation methods and programs

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