Digital twin based condition monitoring of a knuckle boom crane: An experimental study
Tài liệu tham khảo
Haag, 2018, Digital twin–proof of concept, Manuf. Lett., 15, 64, 10.1016/j.mfglet.2018.02.006
Boschert, 2016, Digital twin—the simulation aspect, 59
Negri, 2017, A review of the roles of digital twin in cps-based production systems, Procedia Manuf., 11, 939, 10.1016/j.promfg.2017.07.198
D. Guivarch, E. Mermoz, Y. Marino, M. Sartor, Creation of helicopter dynamic systems digital twin using multibody simulations, CIRP Annals. (2019).
Tuegel, 2011, Reengineering aircraft structural life prediction using a digital twin, Int. J. Aerospace Eng., 10.1155/2011/154798
Li, 2017, Dynamic bayesian network for aircraft wing health monitoring digital twin, Aiaa J., 55, 930, 10.2514/1.J055201
B.R. Seshadri, T. Krishnamurthy, Structural health management of damaged aircraft structures using digital twin concept, in: 25th AIAA/AHS Adaptive Structures Conference, 2017, p. 1675.
Cai, 2017, Sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing, Procedia Manuf., 10, 1031, 10.1016/j.promfg.2017.07.094
Botkina, 2018, Digital twin of a cutting tool, Procedia CIRP, 72, 215, 10.1016/j.procir.2018.03.178
Luo, 2019, Digital twin for cnc machine tool: modeling and using strategy, J. Ambient Intell. Humanized Comput., 10, 1129, 10.1007/s12652-018-0946-5
Deng, 2018, From open cnc systems to cyber-physical machine tools: a case study, Procedia CIRP, 72, 1270, 10.1016/j.procir.2018.03.110
Rosen, 2015, About the importance of autonomy and digital twins for the future of manufacturing, IFAC-PapersOnLine, 48, 567, 10.1016/j.ifacol.2015.06.141
Schluse, 2018, Experimentable digital twins—streamlining simulation-based systems engineering for industry 4.0, IEEE Trans. Industr. Inf., 14, 1722, 10.1109/TII.2018.2804917
Biesinger, 2019, A digital twin for production planning based on cyber-physical systems: A case study for a cyber-physical system-based creation of a digital twin, Procedia CIRP, 79, 355, 10.1016/j.procir.2019.02.087
Vrabic, 2018, Digital twins: Understanding the added value of integrated models for through-life engineering services, Procedia Manuf., 16, 139, 10.1016/j.promfg.2018.10.167
Zheng, 2019, An application framework of digital twin and its case study, J. Ambient Intell. Humanized Comput., 10, 1141, 10.1007/s12652-018-0911-3
T. Moi, A. Cibicik, T. Rølvåg, Digital twin based fatigue monitoring of a knuckle boom crane, published at 3rd International Conference on Structural Integrity and Durability (6 2019).
Uhl, 2007, The inverse identification problem and its technical application, Arch. Appl. Mech., 77, 325, 10.1007/s00419-006-0086-9
Liu, 2014, Explicit form of an implicit method for inverse force identification, J. Sound Vib., 333, 730, 10.1016/j.jsv.2013.09.040
Jayalakshmi, 2018, Dynamic force reconstruction techniques from incomplete measurements, J. Vib. Control, 24, 5321, 10.1177/1077546317752709
Li, 2018, Time domain force identification based on adaptive lq regularization, J. Vib. Control, 24, 5610, 10.1177/1077546318761968
Li, 2019, A revised time domain force identification method based on bayesian formulation, Int. J. Numer. Meth. Eng., 118, 411, 10.1002/nme.6019
Sanchez, 2015
Li, 2018, Force identification based on a comprehensive approach combining taylor formula and acceleration transmissibility, Inverse Probl. Sci. Eng., 26, 1612, 10.1080/17415977.2017.1417407
Yuen, 2018, Real-time substructural identification by boundary force modeling, Struc. Control Health Monit., 25, e2151, 10.1002/stc.2151
T. Lai, T.-H. Yi, H.-N. Li, Parametric study on sequential deconvolution for force identification, J. Sound Vib. 377 (2016). https://doi.org/10.1016/j.jsv.2016.05.013.
Zhu, 2014, Force identification in time domain based on dynamic programming, Appl. Math. Comput., 235, 226
Li, 2014, A load identification method based on wavelet multi-resolution analysis, J. Sound Vib., 333, 381, 10.1016/j.jsv.2013.09.026
J. Liu, X. Han, C. Jiang, H.M. Ning, Y.C. Bai, Dynamic load identification for uncertain structures baed on interval analysis and regularization method, Int. J. Comput. Methods 08 (2011). https://doi.org/10.1142/S0219876211002757.
Li, 2018, Force localization and reconstruction using a two-step iterative approach, J. Vib. Control, 24, 3830, 10.1177/1077546317713366
Liu, 2014, A novel computational inverse technique for load identification using the shape function method of moving least square fitting, Comput. Struct., 144, 127, 10.1016/j.compstruc.2014.08.002
T. Rølvåg, B. Haugen, M. Bella, F. Berto, Fatigue analysis of high performance race engines, published at 3rd International Conference on Structural Integrity and Durability (6 2019).
Rølvåg, 2017, Dynamic test bench for motocross engines, Adv. Mech. Eng., 9, 10.1177/1687814017726921
Siemens Industry Software, Element Library Reference (2014). URL https://docs.plm.automation.siemens.com/data_services/resources/nxnastran/10/help/en_US/tdocExt/pdf/element.pdf.