{"id":{"repo_id":"must-thes","oai_identifier":"oai:scholarsmine.mst.edu:doctoral_dissertations-3766"},"canonical_url":"https://search.dev.ndltd.org/etd/must-thes/oai:scholarsmine.mst.edu:doctoral_dissertations-3766","repository":{"repo_id":"must-thes","name":"Missouri University of Science and Technology","base_url":"https://scholarsmine.mst.edu/do/oai/"},"display":{"title":"Adaptive data analysis for damage detection and system identification in civil infrastructure","abstract":"\"Time-varying structural systems are often encountered in civil engineering. As extreme events occur more frequently and severely in recent years, more structures are loaded beyond their elastic conditions and may thus experience damage in the years to come. Even if structures remain elastic, energy dissipation devices installed on structures often reveal hysteretic behaviors under earthquake loads. Therefore, it is imperative to develop and implement novel technologies that enable the identification and damage detection of time-varying systems. In this dissertation, adaptive wavelet transform (AWT) and multiple analytical mode decomposition (M-AMD) are proposed and applied to identify system properties and detect damage in structures. AWT is an optimized time-frequency representation of dynamic responses for the extraction of features. It is defined as an average of overlapped short-time wavelet transforms with time-varying wavelet parameters in order to extract time-dependent frequencies. The effectiveness of AWT is demonstrated by various analytical signals, acoustic emission and impact echo responses. M-AMD is a response decomposition method for the identification of weakly to moderately nonlinear oscillators based on vibration responses. It can be used to accurately separate the low and high frequency components of time-varying stiffness and damping coefficients in dynamic systems. The efficiency and accuracy of the proposed M-AMD are evaluated with three characteristic nonlinear oscillators and a 1/4-scale 3-story building model with frictional damping under seismic excitations. Finally, AWT-based M-AMD is applied to decompose the measured dynamic responses of a 1/20-scale cable-stayed bridge model tested on four shake tables and evaluate the progression of damage under increasing earthquake loads\"--Abstract, page iii.","abstract_html":""Time-varying structural systems are often encountered in civil engineering. As extreme events occur more frequently and severely in recent years, more structures are loaded beyond their elastic conditions and may thus experience damage in the years to come. Even if structures remain elastic, energy dissipation devices installed on structures often reveal hysteretic behaviors under earthquake loads. Therefore, it is imperative to develop and implement novel technologies that enable the identification and damage detection of time-varying systems. In this dissertation, adaptive wavelet transform (AWT) and multiple analytical mode decomposition (M-AMD) are proposed and applied to identify system properties and detect damage in structures. AWT is an optimized time-frequency representation of dynamic responses for the extraction of features. It is defined as an average of overlapped short-time wavelet transforms with time-varying wavelet parameters in order to extract time-dependent frequencies. The effectiveness of AWT is demonstrated by various analytical signals, acoustic emission and impact echo responses. M-AMD is a response decomposition method for the identification of weakly to moderately nonlinear oscillators based on vibration responses. It can be used to accurately separate the low and high frequency components of time-varying stiffness and damping coefficients in dynamic systems. The efficiency and accuracy of the proposed M-AMD are evaluated with three characteristic nonlinear oscillators and a 1/4-scale 3-story building model with frictional damping under seismic excitations. Finally, AWT-based M-AMD is applied to decompose the measured dynamic responses of a 1/20-scale cable-stayed bridge model tested on four shake tables and evaluate the progression of damage under increasing earthquake loads"--Abstract, page iii.","abstract_has_math":false,"creators":["Qu, Hongya"],"institution":"Missouri University of Science and Technology","degree_name":"Ph. D. in Civil Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T03:18:26Z","subjects":["Civil and Environmental Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/2761","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Qu, Hongya"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Civil Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Missouri University of Science and Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Civil and Environmental Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/2761"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"Time-varying structural systems are often encountered in civil engineering. As extreme events occur more frequently and severely in recent years, more structures are loaded beyond their elastic conditions and may thus experience damage in the years to come. Even if structures remain elastic, energy dissipation devices installed on structures often reveal hysteretic behaviors under earthquake loads. Therefore, it is imperative to develop and implement novel technologies that enable the identification and damage detection of time-varying systems. In this dissertation, adaptive wavelet transform (AWT) and multiple analytical mode decomposition (M-AMD) are proposed and applied to identify system properties and detect damage in structures. AWT is an optimized time-frequency representation of dynamic responses for the extraction of features. It is defined as an average of overlapped short-time wavelet transforms with time-varying wavelet parameters in order to extract time-dependent frequencies. The effectiveness of AWT is demonstrated by various analytical signals, acoustic emission and impact echo responses. M-AMD is a response decomposition method for the identification of weakly to moderately nonlinear oscillators based on vibration responses. It can be used to accurately separate the low and high frequency components of time-varying stiffness and damping coefficients in dynamic systems. The efficiency and accuracy of the proposed M-AMD are evaluated with three characteristic nonlinear oscillators and a 1/4-scale 3-story building model with frictional damping under seismic excitations. Finally, AWT-based M-AMD is applied to decompose the measured dynamic responses of a 1/20-scale cable-stayed bridge model tested on four shake tables and evaluate the progression of damage under increasing earthquake loads\"--Abstract, page iii."]},{"key":"dc:title","label":"Title","values":["Adaptive data analysis for damage detection and system identification in civil infrastructure"]}]}],"canonical_facts":{"dc:creator":["Qu, Hongya"],"dc:description.abstract":["\"Time-varying structural systems are often encountered in civil engineering. As extreme events occur more frequently and severely in recent years, more structures are loaded beyond their elastic conditions and may thus experience damage in the years to come. Even if structures remain elastic, energy dissipation devices installed on structures often reveal hysteretic behaviors under earthquake loads. Therefore, it is imperative to develop and implement novel technologies that enable the identification and damage detection of time-varying systems. In this dissertation, adaptive wavelet transform (AWT) and multiple analytical mode decomposition (M-AMD) are proposed and applied to identify system properties and detect damage in structures. AWT is an optimized time-frequency representation of dynamic responses for the extraction of features. It is defined as an average of overlapped short-time wavelet transforms with time-varying wavelet parameters in order to extract time-dependent frequencies. The effectiveness of AWT is demonstrated by various analytical signals, acoustic emission and impact echo responses. M-AMD is a response decomposition method for the identification of weakly to moderately nonlinear oscillators based on vibration responses. It can be used to accurately separate the low and high frequency components of time-varying stiffness and damping coefficients in dynamic systems. The efficiency and accuracy of the proposed M-AMD are evaluated with three characteristic nonlinear oscillators and a 1/4-scale 3-story building model with frictional damping under seismic excitations. Finally, AWT-based M-AMD is applied to decompose the measured dynamic responses of a 1/20-scale cable-stayed bridge model tested on four shake tables and evaluate the progression of damage under increasing earthquake loads\"--Abstract, page iii."],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/2761"],"dc:subject":["Civil and Environmental Engineering"],"dc:title":["Adaptive data analysis for damage detection and system identification in civil infrastructure"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Civil Engineering"],"thesis:institution_name":["Missouri University of Science and Technology"]},"updated_at":"2026-07-24T03:18:26Z"}