Damage diagnosis in bridge structures using rotation influence line: Validation on a cable-stayed bridge
Tài liệu tham khảo
Ren, 2005, Baseline finite element modeling of a large span cable-stayed bridge through field ambient vibration tests, Comp Struct, 83, 536, 10.1016/j.compstruc.2004.11.013
Li, 2016, The state of the art in structural health monitoring of cable-stayed bridges, J Civil Struct Health Monitor, 6, 43, 10.1007/s13349-015-0115-x
Diord, 2017, High spatial resolution modal identification of a stadium suspension roof: assessment of the estimates uncertainty and of modal contributions, Eng Struct, 135, 117, 10.1016/j.engstruct.2016.12.060
Cunha, 2001, Dynamic tests on large cable-stayed bridge, J Bridge Eng, 6, 54, 10.1061/(ASCE)1084-0702(2001)6:1(54)
Asadollahi, 2017, Statistical analysis of modal properties of a cable-stayed bridge through long-term wireless structural health monitoring, J Bridge Eng, 22, 04017051, 10.1061/(ASCE)BE.1943-5592.0001093
De Roeck, 2000, Benchmark study on system identification through ambient vibration measurements, 1106
Reynders, 2011
Mustapha, 2015, Pattern recognition based on time series analysis using vibration data for structural health monitoring in civil structures, Electron J Struct Eng
Anaissi, 2017, Adaptive one-class support vector machine for damage detection in structural health monitoring, 42
Ko, 2002, Multi-stage identification scheme for detecting damage in cable-stayed Kap Shui Mun Bridge, Eng Struct, 24, 857, 10.1016/S0141-0296(02)00024-X
Casciati, 2017, Damage localization in a cable-stayed bridge via bio-inspired metaheuristic tools, Struct Control Health Monitor, 24, e1922, 10.1002/stc.1922
Mao, 2018, Investigation of dynamic properties of long-span cable-stayed bridges based on one-year monitoring data under normal operating condition, Struct Control Health Monitor, 10.1002/stc.2146
Rainieri, 2017, Challenging aspects in removing the influence of environmental factors on modal parameter estimates, Proc Eng, 199, 2244, 10.1016/j.proeng.2017.09.210
Huang, 2018, Damage identification of a large cable-stayed bridge with novel cointegrated Kalman filter method under changing environments, Struct Control Health Monitor, 10.1002/stc.2152
Nazarian, 2016, Detection of tension loss in cables of cable-stayed bridges by distributed monitoring of bridge deck strains, J Struct Eng, 142, 04016018, 10.1061/(ASCE)ST.1943-541X.0001463
Lin, 2017, Damage detection in the cable structures of a bridge using the virtual distortion method, J Bridge Eng, 22, 04017039, 10.1061/(ASCE)BE.1943-5592.0001072
Zarbaf Haji Agha Mohammad, 2017, Stay force estimation in cable-stayed bridges using stochastic subspace identification methods, J Bridge Eng, 22, 04017055, 10.1061/(ASCE)BE.1943-5592.0001091
Alamdari, 2018, A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge, Struct Health Monitor
Mehrabi, 2006, In-service evaluation of cable-stayed bridges, overview of available methods and findings, J Bridge Eng, 11, 716, 10.1061/(ASCE)1084-0702(2006)11:6(716)
Zhang, 2014, Smart elasto-magneto-electric (EME) sensors for stress monitoring of steel cables: design theory and experimental validation, Sensors, 14, 13644, 10.3390/s140813644
Li, 2009, Applications of optical fibre Bragg gratings sensing technology-based smart stay cables, Opt Lasers Eng, 47, 1077, 10.1016/j.optlaseng.2009.04.016
Christen, 2003, Three-dimensional localization of defects in stay cables using magnetic flux leakage methods, J Nondestruct Eval, 22, 93, 10.1023/B:JONE.0000010736.74285.b6
Xu, 2018, A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge, Struct Control Health Monitor, 10.1002/stc.2155
Feng, 2017, Cable tension force estimate using novel noncontact vision-based sensor, Measurement, 99, 44, 10.1016/j.measurement.2016.12.020
Zejli, 2012, Detection of the presence of broken wires in cables by acoustic emission inspection, J Bridge Eng, 17, 921, 10.1061/(ASCE)BE.1943-5592.0000404
Mehrabi, 2006, Assessment of in-service cable stayed bridges—approach and findings, Struct Congress 2006: Struct Eng Public Safety, 1
Sukhorukov, 2012, Nondestructive testing of bridge stay cables, Struct Mater Technol, 2012, 347
Zhang, 2018, A two-step FEM-SEM approach for wave propagation analysis in cable structures, J Sound Vibration, 415, 41, 10.1016/j.jsv.2017.11.002
Schaal, 2015, Energy-based models for guided ultrasonic wave propagation in multi-wire cables, Int J Solids Struct, 64, 22, 10.1016/j.ijsolstr.2015.03.010
Weng, 2008, Output-only modal identification of a cable-stayed bridge using wireless monitoring systems, Eng Struct, 30, 1820, 10.1016/j.engstruct.2007.12.002
Liao, 2001, Wireless monitoring of cable tension of cable-stayed bridges using PVDF piezoelectric films, J Intell Mater Syst Struct, 12, 331, 10.1106/AVHK-TLR4-6PTQ-QGXY
Anaissi, 2018, A tensor-based structural damage identification and severity assessment, Sensors, 18, 111, 10.3390/s18010111
Wang, 2017, Extraction of influence line through a fitting method from bridge dynamic response induced by a passing vehicle, Eng Struct, 151, 648, 10.1016/j.engstruct.2017.06.067
Lansdell, 2017, Development and testing of a bridge weigh-in-motion method considering nonconstant vehicle speed, Eng Struct, 152, 709, 10.1016/j.engstruct.2017.09.044
Strauss, 2012, Influence line-model correction approach for the assessment of engineering structures using novel monitoring techniques, Smart Struct Syst, 9, 1, 10.12989/sss.2012.9.1.001
Xiao, 2014, Multiscale modeling and model updating of a cable-stayed bridge. II: model updating using modal frequencies and influence lines, J Bridge Eng, 20, 04014113, 10.1061/(ASCE)BE.1943-5592.0000723
Wu, 2017, Stiffness monitoring and damage assessment of bridges under moving vehicular loads using spatially-distributed optical fiber sensors, Smart Mater Struct, 26, 035058, 10.1088/1361-665X/aa5c6f
Cavadas, 2013, Damage detection using data-driven methods applied to moving-load responses, Mech Syst Signal Process, 39, 409, 10.1016/j.ymssp.2013.02.019
Chen, 2014, Damage detection in long suspension bridges using stress influence lines, J Bridge Eng, 20, 05014013, 10.1061/(ASCE)BE.1943-5592.0000681
Zaurin, 2009, Integration of computer imaging and sensor data for structural health monitoring of bridges, Smart Mater Struct, 19, 015019, 10.1088/0964-1726/19/1/015019
González, 2012, Testing of a bridge weigh-in-motion algorithm utilising multiple longitudinal sensor locations, J Testing Evaluation, 40, 961, 10.1520/JTE104576
Sun, 2017, Automated operational modal analysis of a cable-stayed bridge, J Bridge Eng, 22, 05017012, 10.1061/(ASCE)BE.1943-5592.0001141
Kalhori, 2017, Traffic data collection using a bridge-weigh-in-motion system in a cable-stayed bridge
Brincker, 2001, Modal identification of output-only systems using frequency domain decomposition, Smart Mater Struct, 10, 441, 10.1088/0964-1726/10/3/303
OBrien, 2012, Increasing truck weight limits: implications for bridges, Proc-Social Behavioral Sci, 48, 2071, 10.1016/j.sbspro.2012.06.1180
O'Brien, 2006, Calculating an influence line from direct measurements, Proc Inst Civil Eng
Ieng, 2014, Bridge influence line estimation for bridge weigh-in-motion system, J Comp Civil Eng, 29, 06014006, 10.1061/(ASCE)CP.1943-5487.0000384
Frøseth, 2017, Influence line extraction by deconvolution in the frequency domain, Comp Struct, 189, 21, 10.1016/j.compstruc.2017.04.014
Paige, 1982, LSQR: an algorithm for sparse linear equations and sparse least squares, ACM Trans Math Software, 8, 43, 10.1145/355984.355989
Blake, 2013