Real-time implementation with FPGA-based DAQ system of a probabilistic disruption predictor from scratch

被引：2

作者：

Vega, J. ^{[1
,62
]}

Ruiz, M. ^{[2
,99
]}

Barrera, E. ^{[2
]}

Castro, R. ^{[1
]}

Ratta, G. A. ^{[1
]}

Dormido-Canto, S. ^{[3
,98
]}

Murari, A. ^{[4
,17
,40
]}

Bernal, E. ^{[2
]}

Abduallev, S. ^{[44
]}

Abhangi, M. ^{[51
]}

Abreu, P. ^{[58
]}

Afzal, M. ^{[12
]}

Aggarwal, K. M. ^{[34
]}

Ahlgren, T. ^{[106
]}

Ahn, J. H. ^{[13
]}

Aho-Mantila, L. ^{[116
]}

Aiba, N. ^{[74
]}

Airila, M. ^{[116
]}

Albanese, R. ^{[109
]}

Aldred, V. ^{[12
]}

Alegre, D. ^{[98
]}

Alessi, E. ^{[50
]}

Aleynikov, P. ^{[60
]}

Alfier, A. ^{[17
]}

Alkseev, A. ^{[77
]}

Allinson, M. ^{[12
]}

Alper, B. ^{[12
]}

Alves, E. ^{[58
]}

Ambrosino, G. ^{[109
]}

Ambrosino, R. ^{[110
]}

Amicucci, L. ^{[95
]}

Amosov, V. ^{[93
]}

Sunden, E. Andersson ^{[27
]}

Angelone, M. ^{[95
]}

Anghel, M. ^{[90
]}

Angioni, C. ^{[67
]}

Appel, L. ^{[12
]}

Appelbee, C. ^{[12
]}

Arena, P. ^{[35
]}

Ariola, M. ^{[110
]}

Arnichand, H. ^{[13
]}

Arshad, S. ^{[46
]}

Ash, A. ^{[12
]}

Ashikawa, N. ^{[73
]}

Aslanyan, V. ^{[69
]}

Asunta, O. ^{[6
]}

Auriemma, F. ^{[17
]}

Austin, Y. ^{[12
]}

Avotina, L. ^{[108
]}

Axton, M. D. ^{[12
]}

机构：

[1] CIEMAT, Lab Nacl Fus, Avda Complutense 40, E-28040 Madrid, Spain

[2] Univ Politecn Madrid, Grp Invest Instrumentat & Acust Aplicada, Madrid, Spain

[3] UNED, Dept Informat & Automat, Madrid, Spain

[4] Consorzio RFX, Corso Stati Uniti 4, I-35127 Padua, Italy

[5] Culham Sci Ctr, JET, EUROfus Consortium, Abingdon OX14 3DB, Oxon, England

[6] Aalto Univ, POB 14100, FIN-00076 Aalto, Finland

[7] Aix Marseille Univ, CNRS, Ctr Marseille, M2P2 UMR 7340, F-13451 Marseille, France

[8] Aix Marseille Univ, CNRS, IUSTI UMR 7343, F-13013 Marseille, France

[9] Aix Marseille Univ, CNRS, PIIM, UMR 7345, F-13013 Marseille, France

[10] Arizona State Univ, Tempe, AZ USA

[11] Barcelona Supercomp Ctr, Barcelona, Spain

[12] CCFE Culham Sci Ctr, Abingdon OX14 3DB, Oxon, England

[13] CEA, IRFM, F-13108 St Paul Les Durance, France

[14] Univ Calif San Diego, Ctr Energy Res, La Jolla, CA 92093 USA

[15] Ctr Brasileiro Pesquisas Fis, Rua Xavier Sigaud 160, BR-22290180 Rio De Janeiro, Brazil

[16] Consorzio CREATE, Via Claudio 21, I-80125 Naples, Italy

[17] Consorzio RFX, Corso Stati Uniti 4, I-35127 Padua, Italy

[18] Daegu Univ, Gyongsan 712174, Gyeongbuk, South Korea

[19] Univ Carlos III Madrid, Dept Fis, Madrid 28911, Spain

[20] Univ Ghent, Dept Appl Phys UG, St Pietersnieuwstr 41, B-9000 Ghent, Belgium

[21] Chalmers Univ Technol, Dept Earth & Space Sci, SE-41296 Gothenburg, Sweden

[22] Univ Cagliari, Dept Elect & Elect Engn, Piazza Armi 09123, Cagliari, Italy

[23] Comenius Univ, Dept Expt Phys, Fac Math Phys & Informat, Mlynska Dolina F2, Bratislava 84248, Slovakia

[24] Warsaw Univ Technol, Dept Mat Sci, PL-01152 Warsaw, Poland

[25] Korea Adv Inst Sci & Technol, Dept Nucl & Quantum Engn, Daejeon 34141, South Korea

[26] Univ Strathclyde, Dept Phys & Appl Phys, Glasgow G4 ONG, Lanark, Scotland

[27] Uppsala Univ, Dept Phys & Astron, SE-75120 Uppsala, Sweden

[28] Chalmers Univ Technol, Dept Phys, S-41296 Gothenburg, Sweden

[29] Imperial Coll London, Dept Phys, London SW7 2AZ, England

[30] KTH, SCI, Dept Phys, SE-10691 Stockholm, Sweden

[31] Univ Basel, Dept Phys, Basel, Switzerland

[32] Univ Oxford, Dept Phys, Oxford OX1 2JD, England

[33] Univ Warwick, Dept Phys, Coventry CV4 7AL, W Midlands, England

[34] Queens Univ, Dept Pure & Appl Phys, Belfast BT7 1NN, Antrim, North Ireland

[35] Univ Catania, Dipartimento Ingn Elettr Elettron & Informat, I-95125 Catania, Italy

[36] Univ Trento, Dipartimento Ingn Ind, Trento, Italy

[37] Dublin City Univ, Dublin, Ireland

[38] Swiss Plasma Ctr, EPFL, CH-1015 Lausanne, Switzerland

[39] EUROfus Programme Management Unit, Boltzmannstr 2, D-85748 Garching, Germany

[40] Culham Sci Ctr, EUROfus Programme Management Unit, Culham OX14 3DB, England

[41] European Commiss, B-1049 Brussels, Belgium

[42] ULB, Fluid & Plasma Dynam, Campus Plaine CP 231 Blvd Triomphe, B-1050 Brussels, Belgium

[43] FOM Inst DIFFER, Eindhoven, Netherlands

[44] Forschungszentrum Julich GmbH, Inst Energie & Klimaforsch Plasmaphys, D-52425 Julich, Germany

[45] Fourth State Res, 503 Lockhart Dr, Austin, TX USA

[46] Fus Energy Joint Undertaking, Josep Pl 2,Torres Diagonal Litoral B3, Barcelona 08019, Spain

[47] KTH, Fusion Plasma Phys, EES, SE-10044 Stockholm, Sweden

[48] Gen Atom, POB 85608, San Diego, CA 92186 USA

[49] HRS Fusion, W Orange, NJ USA

[50] IFP CNR, Via R Cozzi 53, I-20125 Milan, Italy

来源：

FUSION ENGINEERING AND DESIGN | 2018年 / 129卷

关键词：

Disruption prediction; Real-time; Machine learning; Venn predictors; Data acquisition; Fpga; CLASSIFICATION;

D O I：

10.1016/j.fusengdes.2018.02.071

中图分类号：

TL [原子能技术]; O571 [原子核物理学];

学科分类号：

0827 ; 082701 ;

摘要：

Real-time (RT) disruption prediction (DP) is essential to trigger mitigation actions that avoid irreversible damage to the devices. This paper deals with disruption mitigation alarms and performs the RT implementation of a probabilistic predictor. The RT implementation has been carried out with a fast controller with DAQ FPGA-based data acquisition devices corresponding to ITER catalogue (in particular, a reconfigurable Input/Output platform has been used). Up to three input signals have been used and relevant information for the prediction is extracted from the temporal and the frequency domains. The signals are read from the JET database. Then D/A conversions are carried out and used as inputs to the real time system. In this way, the whole process of digitization, data analysis and prediction is performed. The computation time for each prediction takes less than 200 mu s.

引用

页码：179 / 182

页数：4

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