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Damage Detection of Truss Employing Swarm-Based Optimization Techniques: A Comparison

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Advanced Engineering Optimization Through Intelligent Techniques

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 949))

Abstract

Swarm-based optimization techniques are very popular and well known in the field of damage detection of structures. Present paper evaluates the performance of three different variants of particle swarm optimization (PSO) and continuous ant colony optimization (ACOr) to detect damages in plane and space truss structure based on frequency and mode shapes-based objective function. The algorithms considered for the comparison are: unified particle swarm optimization (UPSO), ageing leader challenger particle swarm optimization (ALC-PSO), enhanced PSO with intelligent particle number (IPN-PSO) and continuous ant colony optimization (ACOr). A 25 member plane truss and a 25 member space truss are considered for the comparison among the algorithms. The numerical study reveals the superiority of UPSO over other algorithms in terms of minimum computational effort and success rate.

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Acknowledgements

This research work is financially supported by ISRO (Indian Space Research Organisation) IIT Kharagpur cell. The authors are grateful to ISRO cell for their financial support to carry out the research work at Department of Aerospace Engineering, IIT, Kharagpur.

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Authors and Affiliations

  1. Department of Aerospace Engineering, IIT Kharagpur, Kharagpur, India

    Swarup K. Barman & Dipak K. Maiti

  2. Department of Civil Engineering, IIT Kharagpur, Kharagpur, India

    Damodar Maity

Authors
  1. Swarup K. Barman
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  2. Dipak K. Maiti
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  3. Damodar Maity
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Correspondence to Swarup K. Barman .

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Editors and Affiliations

  1. Sardar Vallabhbhai National Institute of Technology, Surat, Surat, Gujarat, India

    R. Venkata Rao

  2. Cracow University of Technology, Kraków, Poland

    Jan Taler

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Barman, S.K., Maiti, D.K., Maity, D. (2020). Damage Detection of Truss Employing Swarm-Based Optimization Techniques: A Comparison. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_3

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