Sensor Networks in Structural Health Monitoring: From Theory to Practice
The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle an...
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| Định dạng: | Online |
|---|---|
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Những chủ đề: | |
| Truy cập trực tuyến: | ONIX_20220111_9783036506326_13 |
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| _version_ | 1869518592801767424 |
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| collection | Directory of Open Access Books |
| description | The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle and resilience management is heavily dependent on the advent of low-cost and easily deployable sensors Nonetheless, in optimizing these deployments, a number of open issues remain with respect to the sensing side. These are associated with the type, configuration, and eventual processing of the information acquired from these sensors to deliver continuous behavioral signatures of the monitored structures. This book discusses the latest advances in the field of sensor networks for SHM. The focus lies both in active research on the theoretical foundations of optimally deploying and operating sensor networks and in those technological developments that might designate the next generation of sensing solutions targeted for SHM. The included contributions span the complete SHM information chain, from sensor design to configuration, data interpretation, and triggering of reactive action. The featured papers published in this Special Issue offer an overview of the state of the art and further proceed to introduce novel methods and tools. Particular attention is given to the treatment of uncertainty, which inherently describes the sensed information and the behavior of monitored systems. |
| format | Online |
| id | doab-20.500.12854ir-76277 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-762772024-04-09T23:16:32Z Sensor Networks in Structural Health Monitoring: From Theory to Practice Chatzi, Eleni Dertimanis, Vasilis K. probabilistic data-interpretation Bayesian model updating error-domain model falsification iterative asset-management practical applicability computation time swarm-based parallel control (SPC) Internet of Things (IoT) soil–structure interaction (SSI) semi-active control adjacent buildings Bayesian inference model updating modal identification structural dynamics bridges sensor placement optimisation structural health monitoring damage identification mutual information evolutionary optimisation inertial sensor fusion instrumented particle MEMS sediment entrainment sensor calibration frequency of entrainment varying environmental and operational conditions damage detection and localization Gaussian process regression autoregressive with exogenous inputs distributed sensor network mode shape curvatures n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle and resilience management is heavily dependent on the advent of low-cost and easily deployable sensors Nonetheless, in optimizing these deployments, a number of open issues remain with respect to the sensing side. These are associated with the type, configuration, and eventual processing of the information acquired from these sensors to deliver continuous behavioral signatures of the monitored structures. This book discusses the latest advances in the field of sensor networks for SHM. The focus lies both in active research on the theoretical foundations of optimally deploying and operating sensor networks and in those technological developments that might designate the next generation of sensing solutions targeted for SHM. The included contributions span the complete SHM information chain, from sensor design to configuration, data interpretation, and triggering of reactive action. The featured papers published in this Special Issue offer an overview of the state of the art and further proceed to introduce novel methods and tools. Particular attention is given to the treatment of uncertainty, which inherently describes the sensed information and the behavior of monitored systems. 2022-01-11T13:27:19Z 2022-01-11T13:27:19Z 2021 book ONIX_20220111_9783036506326_13 9783036506326 9783036506333 https://directory.doabooks.org/handle/20.500.12854/76277 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/3655 https://mdpi.com/books/pdfview/book/3655 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-0633-3 10.3390/books978-3-0365-0633-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036506326 9783036506333 164 Basel, Switzerland open access |
| spellingShingle | probabilistic data-interpretation Bayesian model updating error-domain model falsification iterative asset-management practical applicability computation time swarm-based parallel control (SPC) Internet of Things (IoT) soil–structure interaction (SSI) semi-active control adjacent buildings Bayesian inference model updating modal identification structural dynamics bridges sensor placement optimisation structural health monitoring damage identification mutual information evolutionary optimisation inertial sensor fusion instrumented particle MEMS sediment entrainment sensor calibration frequency of entrainment varying environmental and operational conditions damage detection and localization Gaussian process regression autoregressive with exogenous inputs distributed sensor network mode shape curvatures n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues Sensor Networks in Structural Health Monitoring: From Theory to Practice |
| title | Sensor Networks in Structural Health Monitoring: From Theory to Practice |
| title_full | Sensor Networks in Structural Health Monitoring: From Theory to Practice |
| title_fullStr | Sensor Networks in Structural Health Monitoring: From Theory to Practice |
| title_full_unstemmed | Sensor Networks in Structural Health Monitoring: From Theory to Practice |
| title_short | Sensor Networks in Structural Health Monitoring: From Theory to Practice |
| title_sort | sensor networks in structural health monitoring from theory to practice |
| topic | probabilistic data-interpretation Bayesian model updating error-domain model falsification iterative asset-management practical applicability computation time swarm-based parallel control (SPC) Internet of Things (IoT) soil–structure interaction (SSI) semi-active control adjacent buildings Bayesian inference model updating modal identification structural dynamics bridges sensor placement optimisation structural health monitoring damage identification mutual information evolutionary optimisation inertial sensor fusion instrumented particle MEMS sediment entrainment sensor calibration frequency of entrainment varying environmental and operational conditions damage detection and localization Gaussian process regression autoregressive with exogenous inputs distributed sensor network mode shape curvatures n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues |
| topic_facet | probabilistic data-interpretation Bayesian model updating error-domain model falsification iterative asset-management practical applicability computation time swarm-based parallel control (SPC) Internet of Things (IoT) soil–structure interaction (SSI) semi-active control adjacent buildings Bayesian inference model updating modal identification structural dynamics bridges sensor placement optimisation structural health monitoring damage identification mutual information evolutionary optimisation inertial sensor fusion instrumented particle MEMS sediment entrainment sensor calibration frequency of entrainment varying environmental and operational conditions damage detection and localization Gaussian process regression autoregressive with exogenous inputs distributed sensor network mode shape curvatures n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues |
| url | ONIX_20220111_9783036506326_13 |