{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/106325"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/106325","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Sudden-event monitoring of civil infrastructure using wireless smart sensors","abstract":"Many of the civil infrastructure damage scenarios involve sudden events, including natural disasters and anthropogenic hazards. Due to their unpredictable nature, many of these events go unnoticed or unreported; but their consequence can be catastrophic, resulting in damage/failure in a matter of seconds or hidden damage that accelerates structural degradation. An efficient structural health monitoring (SHM) system is thus critical to not only send early warning of these events to facilitate appropriate emergency response, but also enable rapid damage assessment to make informed decisions. Traditional monitoring systems using wired sensors can be prohibitive, mainly due to high installation costs resulting from onerous and expensive cabling networks. Wireless smart sensors (WSS) are an attractive alternative, as they have the potential to significantly reduce the cost. However, this solution remains elusive because of three inherent challenges: (1) most wireless sensors are duty-cycled to preserve a limited battery power; as a result, they will miss the onset of events when they are in power-saving sleep mode; (2) the wireless communication throughput is strictly limited, so time-consuming data transmission can result in large delay for subsequent damage assessment; (3) sensor malfunction often occurs in wireless monitoring systems, so the existing faulty data may result in false condition assessment, negatively affecting informed decisions. To address these challenges, this research aims to develop an intelligent wireless monitoring system consisting of five main components: ultralow-power on-demand sensing prototypes, high-precision time synchronization strategies, high-throughput live-streaming framework, effective sensor fault management, and a graphic user interface for rapid condition assessment and real-time data visualization. The capabilities of the developed monitoring system are validated through lab and field tests, demonstrating that the proposed solution is able to detect sudden events, provide high-fidelity synchronized data, and present structural damage assessment in an efficient manner.","abstract_html":"Many of the civil infrastructure damage scenarios involve sudden events, including natural disasters and anthropogenic hazards. Due to their unpredictable nature, many of these events go unnoticed or unreported; but their consequence can be catastrophic, resulting in damage/failure in a matter of seconds or hidden damage that accelerates structural degradation. An efficient structural health monitoring (SHM) system is thus critical to not only send early warning of these events to facilitate appropriate emergency response, but also enable rapid damage assessment to make informed decisions. Traditional monitoring systems using wired sensors can be prohibitive, mainly due to high installation costs resulting from onerous and expensive cabling networks. Wireless smart sensors (WSS) are an attractive alternative, as they have the potential to significantly reduce the cost. However, this solution remains elusive because of three inherent challenges: (1) most wireless sensors are duty-cycled to preserve a limited battery power; as a result, they will miss the onset of events when they are in power-saving sleep mode; (2) the wireless communication throughput is strictly limited, so time-consuming data transmission can result in large delay for subsequent damage assessment; (3) sensor malfunction often occurs in wireless monitoring systems, so the existing faulty data may result in false condition assessment, negatively affecting informed decisions. To address these challenges, this research aims to develop an intelligent wireless monitoring system consisting of five main components: ultralow-power on-demand sensing prototypes, high-precision time synchronization strategies, high-throughput live-streaming framework, effective sensor fault management, and a graphic user interface for rapid condition assessment and real-time data visualization. The capabilities of the developed monitoring system are validated through lab and field tests, demonstrating that the proposed solution is able to detect sudden events, provide high-fidelity synchronized data, and present structural damage assessment in an efficient manner.","abstract_has_math":false,"creators":["Fu, Yuguang"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Spencer Jr., Billie F.","Agha, Gul A.","Fahnestock, Larry A.","Work, Daniel B.","Mechitov, Kirill A."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-03-02T22:12:11Z","date_published":"2020-03-02T22:12:11Z","updated_at":"2026-07-22T22:24:45Z","subjects":["sudden-event monitoring","wireless smart sensors","even-triggered sensing","time synchronization","live streaming","rapid damage assessment","sensor fault management","seismic building monitoring","bridge impact detection"],"languages":["en"],"rights":["Copyright 2019 Yuguang Fu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/106325","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Spencer Jr., Billie F.","Agha, Gul A.","Fahnestock, Larry A.","Work, Daniel B.","Mechitov, Kirill A."]},{"key":"dc:creator","label":"Author","values":["Fu, Yuguang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-03-02T22:12:11Z","2022-03-03T10:15:19Z","2019-10-18","2019-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["sudden-event monitoring","wireless smart sensors","even-triggered sensing","time synchronization","live streaming","rapid damage assessment","sensor fault management","seismic building monitoring","bridge impact detection"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Yuguang Fu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/106325"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Many of the civil infrastructure damage scenarios involve sudden events, including natural disasters and anthropogenic hazards. Due to their unpredictable nature, many of these events go unnoticed or unreported; but their consequence can be catastrophic, resulting in damage/failure in a matter of seconds or hidden damage that accelerates structural degradation. An efficient structural health monitoring (SHM) system is thus critical to not only send early warning of these events to facilitate appropriate emergency response, but also enable rapid damage assessment to make informed decisions. Traditional monitoring systems using wired sensors can be prohibitive, mainly due to high installation costs resulting from onerous and expensive cabling networks. Wireless smart sensors (WSS) are an attractive alternative, as they have the potential to significantly reduce the cost. However, this solution remains elusive because of three inherent challenges: (1) most wireless sensors are duty-cycled to preserve a limited battery power; as a result, they will miss the onset of events when they are in power-saving sleep mode; (2) the wireless communication throughput is strictly limited, so time-consuming data transmission can result in large delay for subsequent damage assessment; (3) sensor malfunction often occurs in wireless monitoring systems, so the existing faulty data may result in false condition assessment, negatively affecting informed decisions. To address these challenges, this research aims to develop an intelligent wireless monitoring system consisting of five main components: ultralow-power on-demand sensing prototypes, high-precision time synchronization strategies, high-throughput live-streaming framework, effective sensor fault management, and a graphic user interface for rapid condition assessment and real-time data visualization. The capabilities of the developed monitoring system are validated through lab and field tests, demonstrating that the proposed solution is able to detect sudden events, provide high-fidelity synchronized data, and present structural damage assessment in an efficient manner.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-12-01","The student, Yuguang Fu, accepted the attached license on 2019-10-15 at 21:39.","The student, Yuguang Fu, submitted this Dissertation for approval on 2019-10-15 at 22:48.","This Dissertation was approved for publication on 2019-10-18 at 17:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14497 on 2020-02-28 at 17:21:05","Made available in DSpace on 2020-03-02T22:12:11Z (GMT). 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Due to their unpredictable nature, many of these events go unnoticed or unreported; but their consequence can be catastrophic, resulting in damage/failure in a matter of seconds or hidden damage that accelerates structural degradation. An efficient structural health monitoring (SHM) system is thus critical to not only send early warning of these events to facilitate appropriate emergency response, but also enable rapid damage assessment to make informed decisions. Traditional monitoring systems using wired sensors can be prohibitive, mainly due to high installation costs resulting from onerous and expensive cabling networks. Wireless smart sensors (WSS) are an attractive alternative, as they have the potential to significantly reduce the cost. However, this solution remains elusive because of three inherent challenges: (1) most wireless sensors are duty-cycled to preserve a limited battery power; as a result, they will miss the onset of events when they are in power-saving sleep mode; (2) the wireless communication throughput is strictly limited, so time-consuming data transmission can result in large delay for subsequent damage assessment; (3) sensor malfunction often occurs in wireless monitoring systems, so the existing faulty data may result in false condition assessment, negatively affecting informed decisions. To address these challenges, this research aims to develop an intelligent wireless monitoring system consisting of five main components: ultralow-power on-demand sensing prototypes, high-precision time synchronization strategies, high-throughput live-streaming framework, effective sensor fault management, and a graphic user interface for rapid condition assessment and real-time data visualization. The capabilities of the developed monitoring system are validated through lab and field tests, demonstrating that the proposed solution is able to detect sudden events, provide high-fidelity synchronized data, and present structural damage assessment in an efficient manner.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-12-01","The student, Yuguang Fu, accepted the attached license on 2019-10-15 at 21:39.","The student, Yuguang Fu, submitted this Dissertation for approval on 2019-10-15 at 22:48.","This Dissertation was approved for publication on 2019-10-18 at 17:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14497 on 2020-02-28 at 17:21:05","Made available in DSpace on 2020-03-02T22:12:11Z (GMT). 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