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An Improved Blind Source Separation for Structural Mode Identification Using Fewer Measurements

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Structural Health Monitoring and Damage Detection, Volume 7

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Abstract

In this paper, we present a novel underdetermined structural mode identification algorithm within the framework of Blind Source Separation (BSS) employing PARAllel FACtor (PARAFAC) decomposition. In the proposed method, BSS is employed on vibration measurements to generate an over-complete dictionary of multi-component bases, which are then used to estimate the modal parameters by utilizing the strong uniqueness property of PARAFAC decomposition. Results show significant computational efficiency of the proposed method over existing BSS algorithms, while substantially improving the upper bound of source separation capability of existing PARAFAC decompositions.

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Author information

Authors and Affiliations

  1. Department of Civil Engineering, Lakehead University, Thunder Bay, ON, Canada, P7B 5E1

    Ayan Sadhu

  2. Director of Research, SpectraQuest Inc., 8227– Hermitage road, Richmond, VA, 23228, USA

    Budhaditya Hazra

Authors
  1. Ayan Sadhu
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  2. Budhaditya Hazra
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Corresponding author

Correspondence to Ayan Sadhu .

Editor information

Editors and Affiliations

  1. Dept. of Mechanical Engineering, University of Massachusetts Lowell, Lowell, Massachusetts, USA

    Christopher Niezrecki

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© 2015 The Society for Experimental Mechanics, Inc.

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Sadhu, A., Hazra, B. (2015). An Improved Blind Source Separation for Structural Mode Identification Using Fewer Measurements. In: Niezrecki, C. (eds) Structural Health Monitoring and Damage Detection, Volume 7. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-15230-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-15230-1_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15229-5

  • Online ISBN: 978-3-319-15230-1

  • eBook Packages: EngineeringEngineering (R0)

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