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Big Model Strategy for Bridge Structural Health Monitoring Based on Data-Driven, Adaptive Method and Convolutional Neural Network (CNN) Group
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作者 Yadong Xu Weixing Hong +3 位作者 Mohammad Noori Wael A.Altabey Ahmed Silik Nabeel S.D.Farhan 《Structural Durability & Health Monitoring》 EI 2024年第6期763-783,共21页
This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemb... This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemble methods,collaborative learning,and distributed computing,the approach effectively manages the complexity and scale of large-scale bridge data.The CNN employs transfer learning,fine-tuning,and continuous monitoring to optimize models for adaptive and accurate structural health assessments,focusing on extracting meaningful features through time-frequency analysis.By integrating Finite Element Analysis,time-frequency analysis,and CNNs,the strategy provides a comprehensive understanding of bridge health.Utilizing diverse sensor data,sophisticated feature extraction,and advanced CNN architecture,the model is optimized through rigorous preprocessing and hyperparameter tuning.This approach significantly enhances the ability to make accurate predictions,monitor structural health,and support proactive maintenance practices,thereby ensuring the safety and longevity of critical infrastructure. 展开更多
关键词 structural health monitoring(shm) BRIDGES big model Convolutional Neural Network(CNN) Finite Element Method(FEM)
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Energy evolution and structural health monitoring of coal under different failure modes:An experimental study
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作者 Yarong Xue Xueqiu He +4 位作者 Dazhao Song Zhenlei Li Majid Khan Taoping Zhong Fei Yang 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2024年第5期917-928,共12页
Structural instability in underground engineering,especially in coal-rock structures,poses significant safety risks.Thus,the development of an accurate monitoring method for the health of coal-rock bodies is crucial.T... Structural instability in underground engineering,especially in coal-rock structures,poses significant safety risks.Thus,the development of an accurate monitoring method for the health of coal-rock bodies is crucial.The focus of this work is on understanding energy evolution patterns in coal-rock bodies under complex conditions by using shear,splitting,and uniaxial compression tests.We examine the changes in energy parameters during various loading stages and the effects of various failure modes,resulting in an innovative energy dissipation-based health evaluation technique for coal.Key results show that coal bodies go through transitions between strain hardening and softening mechanisms during loading,indicated by fluctuations in elastic energy and dissipation energy density.For tensile failure,the energy profile of coal shows a pattern of “high dissipation and low accumulation” before peak stress.On the other hand,shear failure is described by “high accumulation and low dissipation” in energy trends.Different failure modes correlate with an accelerated increase in the dissipation energy before destabilization,and a significant positive correlation is present between the energy dissipation rate and the stress state of the coal samples.A novel mathematical and statistical approach is developed,establishing a dissipation energy anomaly index,W,which categorizes the structural health of coal into different danger levels.This method provides a quantitative standard for early warning systems and is adaptable for monitoring structural health in complex underground engineering environments,contributing to the development of structural health monitoring technology. 展开更多
关键词 energy dissipation structural health monitoring early warning coal-rock mechanics failure mode
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Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel
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作者 Qing Ai Hao Tian +4 位作者 Hui Wang Qing Lang Xingchun Huang Xinghong Jiang Qiang Jing 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期1797-1827,共31页
Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficient... Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance. 展开更多
关键词 Anomaly detection dynamic predictive model structural health monitoring immersed tunnel LSTM ARIMA
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Improving autoencoder-based unsupervised damage detection in uncontrolled structural health monitoring under noisy conditions
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作者 Yang Kang Wang Linyuan +4 位作者 Gao Chao Chen Mozhi Tian Zhihui Zhou Dunzhi Liu Yang 《仪器仪表学报》 EI CAS CSCD 北大核心 2024年第6期91-100,共10页
Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enh... Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions. 展开更多
关键词 structural health monitoring guided waves principal component analysis deep learning DENOISING dynamic environmental condition
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Structural Health Monitoring by Accelerometric Data of a Continuously Monitored Structure with Induced Damages
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作者 Giada Faraco Andrea Vincenzo De Nunzio +1 位作者 Nicola Ivan Giannoccaro Arcangelo Messina 《Structural Durability & Health Monitoring》 EI 2024年第6期739-762,共24页
The possibility of determining the integrity of a real structure subjected to non-invasive and non-destructive monitoring,such as that carried out by a series of accelerometers placed on the structure,is certainly a g... The possibility of determining the integrity of a real structure subjected to non-invasive and non-destructive monitoring,such as that carried out by a series of accelerometers placed on the structure,is certainly a goal of extreme and current interest.In the present work,the results obtained from the processing of experimental data of a real structure are shown.The analyzed structure is a lattice structure approximately 9 m high,monitored with 18 uniaxial accelerometers positioned in pairs on 9 different levels.The data used refer to continuous monitoring that lasted for a total of 1 year,during which minor damage was caused to the structure by alternatively removing some bracings and repositioning them in the structure.Two methodologies detecting damage based on decomposition techniques of the acquired data were used and tested,as well as a methodology combining the two techniques.The results obtained are extremely interesting,as all the minor damage caused to the structure was identified by the processing methods used,based solely on the monitored data and without any knowledge of the real structure being analyzed.The results use 15 acquisitions in environmental conditions lasting 10 min each,a reasonable amount of time to get immediate feedback on possible damage to the structure. 展开更多
关键词 structural health monitoring damage detection vibration measurements stochastic subspace identification
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Review and Prospect of Research on Structural Health Monitoring Technology for Bridges
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作者 Guoyi Liu 《Journal of Architectural Research and Development》 2024年第3期156-161,共6页
As a crucial infrastructure in the transport system,the safe operation of bridges is directly related to all aspects of people’s daily lives.The development of bridge structural health monitoring technology and its a... As a crucial infrastructure in the transport system,the safe operation of bridges is directly related to all aspects of people’s daily lives.The development of bridge structural health monitoring technology and its application play an important role in ensuring the safety and extending the service life of bridges.This paper carries out in-depth research and analysis on the related technology of bridge structural health monitoring.Firstly,the existing monitoring technologies at home and abroad are sorted out,and the advantages and problems of various methods are compared and analyzed,including nondestructive testing,stress measurement,vibration characteristic identification,and other commonly used monitoring technologies.Secondly,the key technologies and equipment in the bridge health monitoring system,such as sensor technology,data acquisition,and processing technology,are introduced in detail.Finally,the development trend in the field of bridge health monitoring is prospected from both theoretical research and technical application.In the future,with the development of emerging technologies such as big data,cloud computing,and the Internet of Things,it is expected that bridge health monitoring with intelligent and systematic features will be more widely applied to provide a stronger guarantee for the safe and efficient operation of bridges. 展开更多
关键词 Bridge structural health monitoring Safe operation monitoring technology
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Discussion on Structural Health Monitoring of Urban Underground Road Tunnel
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作者 Yike Wei 《Journal of World Architecture》 2024年第5期18-23,共6页
The number of urban underground road tunnels in China is increasing year by year,and health monitoring of tunnels is an effective management method to ensure their structural integrity.However,for shorter underground ... The number of urban underground road tunnels in China is increasing year by year,and health monitoring of tunnels is an effective management method to ensure their structural integrity.However,for shorter underground road tunnel projects,insufficient investment often leads to less frequent application of health monitoring systems.The application of intelligent structural health monitoring means can not only reduce the project cost but also help workers fully understand the actual situation of the tunnel structure.Therefore,this paper analyzes the characteristics,problems,and design of the urban underground road tunnel structural health monitoring system,and discusses the implementation of the urban underground road tunnel structural health monitoring system. 展开更多
关键词 Urban underground road Tunnel structure health monitoring
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Deformation warning index for reinforced concrete dam based on structural health monitoring data and numerical simulation 被引量:2
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作者 Ming-qiang Zhan Bo Chen Zhong-ru Wu 《Water Science and Engineering》 EI CAS CSCD 2023年第4期408-418,共11页
The material mechanical parameters of the dam body and foundation will change when a dam is reinforced during the aging process.This causes significant changes in the structural state of the project and makes it diffi... The material mechanical parameters of the dam body and foundation will change when a dam is reinforced during the aging process.This causes significant changes in the structural state of the project and makes it difficult to ensure its structural safety.In this study,a new deformation warning index for reinforced concrete dams was developed according to the prototype monitoring data,statistical models,three-dimensional finite element model(FEM)numerical simulation,and the critical conditions of the dam structure.A statistical model was established to separate the water pressure component.Then,a three-dimensional FEM of the reinforced concrete dam was constructed to simulate the water pressure component.Furthermore,the deformation components that affected the mechanical parameters of the dam under the same amount of reservoir water level change were separated and quantified accurately.In addition,the method for inversion of comprehensive mechanical parameters after dam reinforcement was used.The influence mechanisms of the deformation behavior of concrete dams under the reservoir water level and temperature changes were investigated.A new deformation warning index was developed by combining the forward-simulated critical water pressure component and temperature component in the period of extreme temperature decrease with the aging component separated by the statistical model.The new deformation warning index considers the structural state of the dam before and after reinforcement and links the structural strength criterion and the deformation evolution mechanisms.It provides a theoretical foundation and decision support for long-term service and operation management of reinforced dams. 展开更多
关键词 Deformation warning index structural health monitoring Finite element simulation REINFORCEMENT Multiple-arch dam Parameter inverse analysis
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Development of piezoelectric-based technology for application in civil structural health monitoring
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作者 Qian Feng Yabin Liang 《Earthquake Research Advances》 CSCD 2023年第2期54-61,共8页
Piezoelectric material,as one of the great potential materials,had attracted lots of attention all over the world due to its distinguish advantages.In this paper,the development of piezoelectric-based technology for a... Piezoelectric material,as one of the great potential materials,had attracted lots of attention all over the world due to its distinguish advantages.In this paper,the development of piezoelectric-based technology for application in the field of civil structural health monitoring(CSHM),was summarized and discussed.Based on the different identification mechanisms,the piezoelectric transducer-based technology can be divided into two main approaches as the active or passive sensing and detection methods.This paper summarized the development of these two approaches and discussed their applications in the area of civil structural health monitoring,such as structural and concrete engineering,bridge engineering,pipeline engineering,protection engineering for geological hazards and earthquake disasters,and so on.In addition,the electrical mechanical impedance(EMI)technique,as one of the active identification methods,was also detailly presented.Finally,its great potential for the piezoelectric-based technique was presented based on the detail discussion,especially in the areas of civil structural health monitoring. 展开更多
关键词 Piezoelectric-based technology Civil structural health monitoring Active or passive sensing Detection methods
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Operational modal identification of suspension bridge based on structural health monitoring system 被引量:7
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作者 李枝军 李爱群 韩晓林 《Journal of Southeast University(English Edition)》 EI CAS 2009年第1期104-107,共4页
An output-only modal identification method by a combination use of the peak-picking method and the cross spectrum methods are presented. Meanwhile, a novel mode shape optimum method of the deck is proposed. The method... An output-only modal identification method by a combination use of the peak-picking method and the cross spectrum methods are presented. Meanwhile, a novel mode shape optimum method of the deck is proposed. The methods are applied to the operational modal identification system of the Runyang Suspension Bridge, which can be used to obtain the modal parameters of the bridge from out-only data sets collected by its structural health monitoring system (SHMS). As an example, the vibration response data of the deck, cable and tower recorded during typhoon Matsa excitation are used to illustrate the program application. Some of the modal frequencies observed from deck vibration responses are also found in the vibration responses of the cable and the tower. The results show that some modal shapes of the deck are strongly coupled with the cable and the tower. By comparing the identification results from the operational modal system with those from field measurements, a good agreement between them is achieved, but some modal frequencies identified from the operational modal identification system (OMIS), such as L1 and L2, obviously decrease compared with those from the field measurements. 展开更多
关键词 suspension bridge operational modal identification structural health monitoring system ambient vibration test
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The State of the Art of Data Science and Engineering in Structural Health Monitoring 被引量:66
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作者 Yuequan Bao Zhicheng Chen +3 位作者 Shiyin Wei Yang Xu Zhiyi Tang Hui Li 《Engineering》 SCIE EI 2019年第2期234-242,共9页
Structural health monitoring (SHM) is a multi-discipline field that involves the automatic sensing of structural loads and response by means of a large number of sensors and instruments, followed by a diagnosis of the... Structural health monitoring (SHM) is a multi-discipline field that involves the automatic sensing of structural loads and response by means of a large number of sensors and instruments, followed by a diagnosis of the structural health based on the collected data. Because an SHM system implemented into a structure automatically senses, evaluates, and warns about structural conditions in real time, massive data are a significant feature of SHM. The techniques related to massive data are referred to as data science and engineering, and include acquisition techniques, transition techniques, management techniques, and processing and mining algorithms for massive data. This paper provides a brief review of the state of the art of data science and engineering in SHM as investigated by these authors, and covers the compressive sampling-based data-acquisition algorithm, the anomaly data diagnosis approach using a deep learning algorithm, crack identification approaches using computer vision techniques, and condition assessment approaches for bridges using machine learning algorithms. Future trends are discussed in the conclusion. 展开更多
关键词 structural health monitoring monitoring DATA COMPRESSIVE sampling MACHINE LEARNING Deep LEARNING
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Design and application of structural health monitoring system in long-span cable-membrane structure 被引量:8
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作者 Tang Teng Yang Dong-Hui +2 位作者 Wang Lei Zhang Jian-Ren Yi Ting-Hua 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2019年第2期461-474,共14页
Cable-membrane structures have small rigidity and are highly sensitive to wind. Structural health monitoring is necessary to ensure the serviceability and safety of the structure. In this research, the design method o... Cable-membrane structures have small rigidity and are highly sensitive to wind. Structural health monitoring is necessary to ensure the serviceability and safety of the structure. In this research, the design method of a structural health monitoring system is using the characteristics of a cable-membrane structure. Taking the Yueyang Sanhe Airport Terminal as an example, a finite element model is established to determine the critical structural components. Next, the engineering requirements and the framework of the monitoring system are studied based on the results of numerical analysis. The specific implementation of the structural health monitoring is then carried out, which includes sensor selection, installation and wiring. The proposed framework is successfully applied to the monitoring system for the Yueyang Airport terminal building, and the synchronous acquisition of fiber Bragg grating and acceleration sensor signals is implemented in an innovative way. The successful implementation and operation of structural health monitoring will help to guarantee the safety of the cablemembrane structure during its service life. 展开更多
关键词 cable-membrane structural health monitoring FI nite element model SYNCHRONOUS ACQUISITION structural safety
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New Developments in Structural Health Monitoring Based on Diagnostic Lamb Wave 被引量:9
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作者 Shenfang YUAN, Yingdi XU and Ge PENGThe Smart Materials & Structures Aeronautic Key Laboratory, Nanjing University of Aeronautic and Astronautic, Nanjing 210016, China 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2004年第5期490-496,共7页
Structure health monitoring based on diagnostic Lamb waves has been found to be one of the most promising techniques recently. This paper has a brief review of the new developments on this method including the basic n... Structure health monitoring based on diagnostic Lamb waves has been found to be one of the most promising techniques recently. This paper has a brief review of the new developments on this method including the basic novel of the method, fundamentals and mathematics of Lamb wave propagation, narrowband and wideband Lamb wave excitation methods, optimization of excitation factors and diagnostic Lamb wave interpretation methods. 展开更多
关键词 structural health monitoring Lamb wave methods Factor optimization Damage localization
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Structural health monitoring of long-span suspension bridges using wavelet packet analysis 被引量:8
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作者 丁幼亮 李爱群 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2007年第3期289-294,共6页
During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vib... During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage, This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform (WPT). The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum (WPES) has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations. 展开更多
关键词 structural health monitoring wavelet packet analysis wavelet packet energy spectrum ambient vibration test long-span suspension bridge
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Application of wavelet transform in structural health monitoring 被引量:9
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作者 Yashodhya Kankanamge Yufeng Hu Xiaoyun Shao 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2020年第2期515-532,共18页
Structural health monitoring(SHM)is a process of implementing a damage detection strategy in existing structures to evaluate their condition to ensure safety.The changes in the material,geometric and/or structural pro... Structural health monitoring(SHM)is a process of implementing a damage detection strategy in existing structures to evaluate their condition to ensure safety.The changes in the material,geometric and/or structural properties affect structural responses,which can be captured and analyzed for condition assessment.Various vibration-based damage detection algorithms have been developed in the past few decades.Among them,wavelet transform(WT)gained popularity as an efficient method of signal processing to build a framework to identify modal properties and detect damage in structures.This article presents the state-of-the-art implementation of various WT tools in SHM with a focus on civil structures.The unique features and limitations of WT,and a comparison of WT and other signal processing methods,are further discussed.The comprehensive literature review in this study will help interested researchers to investigate the use of WT in SHM to meet their specific needs. 展开更多
关键词 WAVELET TRANSFORM DAMAGE detection MODAL properties structural health monitoring NUMERICAL simulations
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Structural health monitoring of bridges in the State of Connecticut 被引量:3
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作者 Chengyin Liu Joshua Olund +3 位作者 Alan Cardini Paul D'Attilio Eric Feldblum John DeWolf 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2008年第4期427-437,共11页
A joint effort between the Connecticut Department of Transportation and the University of Connecticut has been underway for more than 20 years to utilize various structural monitoring approaches to assess different br... A joint effort between the Connecticut Department of Transportation and the University of Connecticut has been underway for more than 20 years to utilize various structural monitoring approaches to assess different bridges in Connecticut. This has been done to determine the performance of existing bridges, refine techniques needed to evaluate different bridge components, and develop approaches that can be used to provide a continuous status of a bridge's structural integrity. This paper briefly introduces the background of these studies, with emphasis on recent research and the development of structural health monitoring concepts. This paper presents the results from three different bridge types: a post-tensioned curved concrete box girder bridge, a curved steel box-girder bridge, and a steel multi-girder bridge. The structural health monitoring approaches to be discussed have been successfully tested using field data collected during multi-year monitoring periods, and are based on vibrations, rotations and strains. The goal has been to develop cost-effective strategies to provide critical information needed to manage the State of Connecticut's bridge infrastructure. 展开更多
关键词 structural integrity structural health monitoring field data vibrations
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Finite element model updating of existing steel bridge based on structural health monitoring 被引量:4
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作者 何旭辉 余志武 陈政清 《Journal of Central South University of Technology》 EI 2008年第3期399-403,共5页
Based on the physical meaning of sensitivity,a new finite element(FE) model updating method was proposed. In this method,a three-dimensional FE model of the Nanjing Yangtze River Bridge(NYRB) with ANSYS program was es... Based on the physical meaning of sensitivity,a new finite element(FE) model updating method was proposed. In this method,a three-dimensional FE model of the Nanjing Yangtze River Bridge(NYRB) with ANSYS program was established and updated by modifying some design parameters. To further validate the updated FE model,the analytical stress-time histories responses of main members induced by a moving train were compared with the measured ones. The results show that the relative error of maximum stress is 2.49% and the minimum relative coefficient of analytical stress-time histories responses is 0.793. The updated model has a good agreement between the calculated data and the tested data,and provides a current baseline FE model for long-term health monitoring and condition assessment of the NYRB. At the same time,the model is validated by stress-time histories responses to be feasible and practical for railway steel bridge model updating. 展开更多
关键词 steel bridge model updating structural health monitoring condition assessment sensitivity
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Remote structural health monitoring with serially multiplexed fiber optic acoustic emission sensors 被引量:2
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作者 陈仲裕 梁玉进 Farhad Ansari 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2003年第1期141-146,共6页
Development and testing of a serially multiplexed fiber optic sensor system is described.The sensor differs from conventional fiber optic acoustic systems,as it is capable of sensing AE emissions at several points alo... Development and testing of a serially multiplexed fiber optic sensor system is described.The sensor differs from conventional fiber optic acoustic systems,as it is capable of sensing AE emissions at several points along the length of a single fiber.Multiplexing provides for single channel detection of cracks and their locations in large structural systems. An algorithm was developed for signal recognition and tagging of the AE waveforms for detection of' crack locations,Labora- tory experiments on plain concrete beams and post-tensioned FRP tendons were pcrlormed to evaluate the crack detection capability of the sensor system.The acoustic emission sensor was able to detect initiation,growth and location of the cracks in concrete as well as in the FRP tendons.The AE system is potentially suitable lot applications involving health monitoring of structures following an earthquake. 展开更多
关键词 acoustic emission crack detection concrete EARTHQUAKE fiber optic sensors FRP tendon MULTIPLEXING post seismic structural health monitoring
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Strain Transfer Mechanism of Grating Ends Fiber Bragg Grating for Structural Health Monitoring 被引量:4
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作者 Guang Chen Keqin Ding +2 位作者 Qibo Feng Xinran Yin Fangxiong Tang 《Structural Durability & Health Monitoring》 EI 2019年第3期289-301,共13页
The grating ends bonding fiber Bragg grating(FBG)sensor has been widely used in sensor packages such as substrate type and clamp type for health monitoring of large structures.However,owing to the shear deformation of... The grating ends bonding fiber Bragg grating(FBG)sensor has been widely used in sensor packages such as substrate type and clamp type for health monitoring of large structures.However,owing to the shear deformation of the adhesive layer of FBG,the strain measured by FBG is often different from the strain of actual matrix,which causes strain measurement errors.This investigation aims at improving the measurement accuracy of strain for the grating ends surface-bonded FBG.To fulfill this objective,a strain transfer equation of the grating ends bonding FBG is derived,and a theoretical model of the average strain transfer from the matrix to the optical fiber is developed.Moreover,parameters that influence the average strain transfer rate from the matrix to the optical fiber are analyzed.A selection scheme of bonding parameters by numerical simulation is provided,which is significantly advantageous over that of the grating bonding FBG.The theoretical equation is verified by finite element method(FEM).Compared with the existing model,the proposed model has higher measurement accuracy.Experimental tests are performed to validate the effectiveness of the proposed model on the equalintensity cantilever beam,whose surface is attached to the bare FBG with grating ends bonding and strain gauge by using epoxy glue.The results show that there is a great agreement between the outcome of the bare FBG and that of the strain gauge,and the corrected strain is closer to the true strain.The proposed model provides a theoretical basis for the design of the grating ends surface-bonded FBG strain sensor for health monitoring of large structures. 展开更多
关键词 structural health monitoring grating ends bonding fiber Bragg grating the average strain transfer shear-lag theory
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A framework for computer vision-based health monitoring of a truss structure subjected to unknown excitations
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作者 Mariusz Ostrowski Bartlomiej Blachowski +3 位作者 Bartosz Wójcik Mateusz Żarski Piotr Tauzowski Łukasz Jankowski 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2023年第1期1-17,共17页
Computer vision(CV)methods for measurement of structural vibration are less expensive,and their application is more straightforward than methods based on sensors that measure physical quantities at particular points o... Computer vision(CV)methods for measurement of structural vibration are less expensive,and their application is more straightforward than methods based on sensors that measure physical quantities at particular points of a structure.However,CV methods produce significantly more measurement errors.Thus,computer vision-based structural health monitoring(CVSHM)requires appropriate methods of damage assessment that are robust with respect to highly contaminated measurement data.In this paper a complete CVSHM framework is proposed,and three damage assessment methods are tested.The first is the augmented inverse estimate(AIE),proposed by Peng et al.in 2021.This method is designed to work with highly contaminated measurement data,but it fails with a large noise provided by CV measurement.The second method,as proposed in this paper,is based on the AIE,but it introduces a weighting matrix that enhances the conditioning of the problem.The third method,also proposed in this paper,introduces additional constraints in the optimization process;these constraints ensure that the stiffness of structural elements can only decrease.Both proposed methods perform better than the original AIE.The latter of the two proposed methods gives the best results,and it is robust with respect to the selected coefficients,as required by the algorithm. 展开更多
关键词 computer vision structural health monitoring physics-based graphical models augmented inverse estimate model updating non-negative least square method
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