Improved Adaptive Multi-Objective Particle Swarm Optimization of Sensor Layout for Shape Sensing with Inverse Finite Element Method

The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 22; H. 14; S. 5203
Hauptverfasser:	Li, Xiaohan, Niu, Shengtao, Bao, Hong, Hu, Naigang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 12.07.2022 MDPI
Schlagworte:	Accuracy Archives & records Deformation deformation reconstruction Efficiency Engineering exploitation exploration external candidate solution set Finite element analysis Genetic algorithms inverse finite element method multi-objective particle swarm optimization Optimization algorithms Sensors Working conditions
ISSN:	1424-8220, 1424-8220
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Abstract	The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.
AbstractList	The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM. The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.
Author	Bao, Hong Niu, Shengtao Li, Xiaohan Hu, Naigang
AuthorAffiliation	Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi’an 710071, China; xhanli@stu.xidian.edu.cn (X.L.); stniu@stu.xidian.edu.cn (S.N.); nghu@xidian.edu.cn (N.H.)
AuthorAffiliation_xml	– name: Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi’an 710071, China; xhanli@stu.xidian.edu.cn (X.L.); stniu@stu.xidian.edu.cn (S.N.); nghu@xidian.edu.cn (N.H.)
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Cites_doi	10.1111/mice.12517 10.1016/j.enconman.2016.05.073 10.1016/j.swevo.2021.100847 10.3390/s19051192 10.1088/0964-1726/23/4/045027 10.1016/j.measurement.2020.108347 10.1002/eqe.2486 10.1155/2018/6121293 10.1109/ACCESS.2021.3086559 10.3390/s19061306 10.1088/1742-6596/1881/4/042018 10.3390/s21124221 10.3390/s22041692 10.1061/(ASCE)CP.1943-5487.0000905 10.1177/1350650117724639 10.3390/e21060602 10.1016/j.measurement.2017.09.022 10.3390/en11102716 10.1016/j.paerosci.2018.04.001 10.1016/j.procs.2016.07.135 10.1016/j.cageo.2018.01.016 10.1016/j.asoc.2018.10.012 10.3390/app8091454 10.1016/j.ijsolstr.2012.06.009 10.1109/TCYB.2017.2710133 10.1016/j.cma.2004.03.015 10.1016/j.measurement.2021.110676 10.1007/s10462-012-9378-3 10.1007/s10462-015-9445-7 10.1016/j.measurement.2020.108533 10.1016/j.jsv.2018.07.006
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References	Cheshmehgaz (ref_19) 2015; 43 Chen (ref_15) 2022; 71 Guo (ref_4) 2022; 4 ref_36 ref_30 Azimi (ref_6) 2020; 35 Zhou (ref_25) 2016; 123 ref_18 Ratnam (ref_22) 2018; 114 Zhao (ref_13) 2017; 2017 Mandal (ref_27) 2021; 169 Roshan (ref_1) 2021; 21 Zhao (ref_17) 2018; 2018 Han (ref_26) 2021; 62 Gerardo (ref_3) 2022; 22 Gherlone (ref_12) 2014; 23 Niu (ref_14) 2022; 190 Guo (ref_7) 2021; 1881 Yuen (ref_16) 2015; 44 Luu (ref_29) 2018; 113 Deng (ref_31) 2021; 9 Gherlone (ref_11) 2012; 49 Zhu (ref_33) 2017; 47 ref_24 Engelbrecht (ref_37) 2016; 45 ref_20 Li (ref_34) 2016; 91 Das (ref_2) 2021; 169 Tessler (ref_10) 2005; 194 Akbarzadeh (ref_21) 2018; 232 Liu (ref_23) 2018; 74 Huang (ref_5) 2020; 34 ref_28 Yu (ref_32) 2019; 18 Gordis (ref_35) 2018; 433 ref_9 Gherlone (ref_8) 2018; 99
References_xml	– volume: 4 start-page: 256 year: 2022 ident: ref_4 article-title: Research on Real-time Signal Stability of Computer Monitoring Bridge Structure Health Sensor publication-title: Sci. J. Intell. Syst. Res. – ident: ref_9 – volume: 35 start-page: 597 year: 2020 ident: ref_6 article-title: Structural health monitoring using extremely compressed data through deep learning publication-title: Comput. Aided Civ. Infrastruct. Eng. doi: 10.1111/mice.12517 – volume: 123 start-page: 116 year: 2016 ident: ref_25 article-title: Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2016.05.073 – volume: 62 start-page: 100847 year: 2021 ident: ref_26 article-title: Multi-objective particle swarm optimization with adaptive strategies for feature selection publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2021.100847 – ident: ref_28 doi: 10.3390/s19051192 – volume: 23 start-page: 045027 year: 2014 ident: ref_12 article-title: An inverse finite element method for beam shape sensing: Theoretical framework and experimental validation publication-title: Smart Mater. Struct. doi: 10.1088/0964-1726/23/4/045027 – volume: 169 start-page: 108347 year: 2021 ident: ref_27 article-title: Multi-objective optimization of Cu-MWCNT composite electrode in electro discharge machining using MOPSO-TOPSIS publication-title: Measurement doi: 10.1016/j.measurement.2020.108347 – volume: 44 start-page: 757 year: 2015 ident: ref_16 article-title: Efficient Bayesian sensor placement algorithm for structural identification: A general approach for multi-type sensory systems publication-title: Earthq. Eng. Struct. Dyn. doi: 10.1002/eqe.2486 – volume: 2018 start-page: 6121293 year: 2018 ident: ref_17 article-title: Optimal Sensor Placement for Inverse Finite Element Reconstruction of Three-Dimensional Frame Deformation publication-title: Int. J. Aerosp. Eng. doi: 10.1155/2018/6121293 – volume: 9 start-page: 89741 year: 2021 ident: ref_31 article-title: A Competitive Particle Swarm Algorithm Based on Vector Angles for Multi-Objective Optimization publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3086559 – ident: ref_18 doi: 10.3390/s19061306 – volume: 1881 start-page: 042018 year: 2021 ident: ref_7 article-title: Analysis on Structural Health Monitoring System of High-Pile Wharf Based on Optical Fiber Sensor publication-title: J. Phys. Conf. Ser. doi: 10.1088/1742-6596/1881/4/042018 – volume: 21 start-page: 4221 year: 2021 ident: ref_1 article-title: Crack-Length Estimation for Structural Health Monitoring Using the High-Frequency Resonances Excited by the Energy Release during Fatigue-Crack Growth publication-title: Sensors doi: 10.3390/s21124221 – volume: 22 start-page: 1692 year: 2022 ident: ref_3 article-title: Methodology for Detecting Progressive Damage in Structures Using Ultrasound-Guided Waves publication-title: Sensors doi: 10.3390/s22041692 – volume: 34 start-page: 04020025 year: 2020 ident: ref_5 article-title: Anomaly Identification of Structural Health Monitoring Data Using Dynamic Independent Component Analysis publication-title: J. Comput. Civ. Eng. doi: 10.1061/(ASCE)CP.1943-5487.0000905 – volume: 232 start-page: 657 year: 2018 ident: ref_21 article-title: Multiobjective optimization of thermohydrodynamic journal bearing using MOPSO algorithm publication-title: Proc. Inst. Mech. Eng. Part J J. Eng. Tribol. doi: 10.1177/1350650117724639 – volume: 2017 start-page: 1 year: 2017 ident: ref_13 article-title: The Application Research of Inverse Finite Element Method for Frame Deformation Estimation publication-title: Int. J. Aerosp. Eng. – ident: ref_30 doi: 10.3390/e21060602 – volume: 114 start-page: 78 year: 2018 ident: ref_22 article-title: An effective hybrid multi objective evolutionary algorithm for solving real time event in flexible job shop scheduling problem publication-title: Measurement doi: 10.1016/j.measurement.2017.09.022 – ident: ref_24 doi: 10.3390/en11102716 – volume: 99 start-page: 14 year: 2018 ident: ref_8 article-title: Shape sensing methods: Review and experimental comparison on a wing-shaped plate publication-title: Prog. Aerosp. Sci. doi: 10.1016/j.paerosci.2018.04.001 – volume: 91 start-page: 1001 year: 2016 ident: ref_34 article-title: A Novel Ranking-based Optimal Guides Selection Strategy in MOPSO publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2016.07.135 – volume: 113 start-page: 81 year: 2018 ident: ref_29 article-title: A parallel competitive Particle Swarm Optimization for non-linear first arrival traveltime tomography and uncertainty quantification publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2018.01.016 – volume: 74 start-page: 167 year: 2018 ident: ref_23 article-title: Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems publication-title: Appl. Soft Comput. J. doi: 10.1016/j.asoc.2018.10.012 – ident: ref_20 doi: 10.3390/app8091454 – volume: 49 start-page: 3100 year: 2012 ident: ref_11 article-title: Shape sensing of 3D frame structures using an inverse Finite Element Method publication-title: Int. J. Solids Struct. doi: 10.1016/j.ijsolstr.2012.06.009 – volume: 47 start-page: 2794 year: 2017 ident: ref_33 article-title: An External Archive-Guided Multiobjective Particle Swarm Optimization Algorithm publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2017.2710133 – ident: ref_36 – volume: 18 start-page: 349 year: 2019 ident: ref_32 article-title: Decomposition-based multi-objective comprehensive learning particle swarm optimisation publication-title: Int. J. Comput. Sci. Eng. – volume: 194 start-page: 327 year: 2005 ident: ref_10 article-title: A least-squares variational method for full-field reconstruction of elastic deformations in shear-deformable plates and shells publication-title: Comput. Methods Appl. Mech. Eng. doi: 10.1016/j.cma.2004.03.015 – volume: 190 start-page: 110676 year: 2022 ident: ref_14 article-title: Shape sensing of plate structures through coupling inverse finite element method and scaled boundary element analysis publication-title: Measurement doi: 10.1016/j.measurement.2021.110676 – volume: 43 start-page: 311 year: 2015 ident: ref_19 article-title: The review of multiple evolutionary searches and multi-objective evolutionary algorithms publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-012-9378-3 – volume: 45 start-page: 131 year: 2016 ident: ref_37 article-title: Particle swarm optimization with crossover: A review and empirical analysis publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-015-9445-7 – volume: 169 start-page: 108533 year: 2021 ident: ref_2 article-title: Performance of swarm intelligence based chaotic meta-heuristic algorithms in civil structural health monitoring publication-title: Measurement doi: 10.1016/j.measurement.2020.108533 – volume: 71 start-page: 1 year: 2022 ident: ref_15 article-title: A Unified Full-Field Deformation Measurement Method for Beam-Like Structure publication-title: IEEE Trans. Instrum. Meas. – volume: 433 start-page: 179 year: 2018 ident: ref_35 article-title: Minimum condition number by orthogonal projection row selection of artificial boundary conditions for finite element model update and damage detection publication-title: J. Sound Vib. doi: 10.1016/j.jsv.2018.07.006
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SubjectTerms	Accuracy Archives & records Deformation deformation reconstruction Efficiency Engineering exploitation exploration external candidate solution set Finite element analysis Genetic algorithms inverse finite element method multi-objective particle swarm optimization Optimization algorithms Sensors Working conditions
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Title	Improved Adaptive Multi-Objective Particle Swarm Optimization of Sensor Layout for Shape Sensing with Inverse Finite Element Method
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