Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification

The direct measurement of external loads acting on structures remains a challenge in many engineering applications. In this context, mechanical load identification has received considerable attention to inverse them using some response signals. Obviously, sensor placement is fundamental to the succe...

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Main Authors: Liu, Yaru, Wang, Lei
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/170877
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1708772023-10-04T04:27:23Z Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification Liu, Yaru Wang, Lei School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Optimal Sensor Placement Mechanical Load Identification The direct measurement of external loads acting on structures remains a challenge in many engineering applications. In this context, mechanical load identification has received considerable attention to inverse them using some response signals. Obviously, sensor placement is fundamental to the success of load identification. Considering temperature effects in the environment, this study investigates an optimal heterogeneous sensor placement framework for multi-case mechanical load identification. Firstly, the temperature field approximation method is developed using the measuring points with the minimum error in RBF interpolation. Based on the modal superposition theory, the formulas of mechanical load identification under static and dynamic cases are then deduced utilizing the responses eliminating thermal-oriented components. With the specific loading position, an index of the modal contribution rate is defined to provide a reasonable modal selection. Further, an optimal placement framework of multi-type response sensors (strain gauges and accelerometers) considering distance constraints is constructed for mechanical load identification under static/dynamic multiple cases, in which the optimization objective integrates the global performance and local evaluation of the interested modal loads. More specifically, an algorithm of collaborative clustering for heterogeneous modal matrices is involved to avoid redundant information and alleviate the computation burden. Eventually, two numerical examples are discussed to demonstrate the validity and feasibility of the developed approach. The authors would like to thank the National Nature Science Foundation of China (12072007, 12132001, 52192632), the China Scholarship Council (No. 202206020119), the Ningbo Nature Science Foundation (202003N4018), and the Defense Industrial Technology Development Program (JCKY2019205A006, JCKY2019203A003) for the financial supports. 2023-10-04T04:27:23Z 2023-10-04T04:27:23Z 2023 Journal Article Liu, Y. & Wang, L. (2023). Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification. International Journal of Mechanical Sciences, 253, 108369-. https://dx.doi.org/10.1016/j.ijmecsci.2023.108369 0020-7403 https://hdl.handle.net/10356/170877 10.1016/j.ijmecsci.2023.108369 2-s2.0-85152927717 253 108369 en International Journal of Mechanical Sciences © 2023 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Optimal Sensor Placement
Mechanical Load Identification
spellingShingle Engineering::Mechanical engineering
Optimal Sensor Placement
Mechanical Load Identification
Liu, Yaru
Wang, Lei
Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
description The direct measurement of external loads acting on structures remains a challenge in many engineering applications. In this context, mechanical load identification has received considerable attention to inverse them using some response signals. Obviously, sensor placement is fundamental to the success of load identification. Considering temperature effects in the environment, this study investigates an optimal heterogeneous sensor placement framework for multi-case mechanical load identification. Firstly, the temperature field approximation method is developed using the measuring points with the minimum error in RBF interpolation. Based on the modal superposition theory, the formulas of mechanical load identification under static and dynamic cases are then deduced utilizing the responses eliminating thermal-oriented components. With the specific loading position, an index of the modal contribution rate is defined to provide a reasonable modal selection. Further, an optimal placement framework of multi-type response sensors (strain gauges and accelerometers) considering distance constraints is constructed for mechanical load identification under static/dynamic multiple cases, in which the optimization objective integrates the global performance and local evaluation of the interested modal loads. More specifically, an algorithm of collaborative clustering for heterogeneous modal matrices is involved to avoid redundant information and alleviate the computation burden. Eventually, two numerical examples are discussed to demonstrate the validity and feasibility of the developed approach.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Liu, Yaru
Wang, Lei
format Article
author Liu, Yaru
Wang, Lei
author_sort Liu, Yaru
title Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
title_short Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
title_full Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
title_fullStr Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
title_full_unstemmed Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
title_sort multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
publishDate 2023
url https://hdl.handle.net/10356/170877
_version_ 1779171095602003968