Novel Approaches for Structural Health Monitoring

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 49116

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Guest Editor
Head of the Laboratory of Bio-Inspired Nanomechanics “G.M. Pugno”, Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: structural dynamics, structural health monitoring; machine learning; nonlinear dynamics; signal processing; structural engineering; vibration analysis; biomechanics
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Special Issue Information

Dear Colleagues,

The thirty-plus years of progress in the field of structural health monitoring (SHM) have left a paramount impact on our everyday lives. Be it for the monitoring of fixed- and rotary-wing aircrafts, for the preservation of the cultural and architectural heritage, or for the predictive maintenance of long-span bridges or wind farms, SHM has shaped the framework of many engineering fields. Given the current state of quantitative and principled methodologies, it is nowadays possible to rapidly and consistently evaluate the structural safety of industrial machines, modern concrete buildings, historical masonry complexes, etc., to test their capability to serve their intended purpose. However, old unsolved problematics as well as new challenges exist. Unmodeled nonlinearities, ineffective sensor placement, and the effects of confounding influences due to operational and environmental variability still harm the effectiveness of state-of-art SHM apparatuses. Unprecedented conditions such as hypersonic flight, stricter safety requirements, and ageing civil infrastructure pose new challenges for confrontation. Therefore, the aim of this Special Issue is to gather the main contributions of academics and practitioners in civil, aerospace, and mechanical engineering to provide a common ground for structural health monitoring. Studies concerning nondestructive testing, machine learning, signal processing, sensor fusion, vibration-based techniques, and related fields are all welcome, both numerical and experimental.

Prof. Cecilia Surace
Guest Editor

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Keywords

  • structural health monitoring
  • nondestructive testing
  • machine learning
  • vibration-based
  • signal processing

Published Papers (16 papers)

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Editorial

Jump to: Research, Review

8 pages, 193 KiB  
Editorial
Special Issue on Novel Approaches for Structural Health Monitoring
by Cecilia Surace
Appl. Sci. 2021, 11(16), 7210; https://doi.org/10.3390/app11167210 - 05 Aug 2021
Cited by 2 | Viewed by 1256
Abstract
Crucial mechanical systems and civil structures or infrastructures, such as bridges, railways, buildings, wind turbines, aeroplanes and more are subjected during their lifetime to natural deterioration of their structural integrity [...] Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)

Research

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23 pages, 6321 KiB  
Article
The Extreme Function Theory for Damage Detection: An Application to Civil and Aerospace Structures
by Davide Martucci, Marco Civera and Cecilia Surace
Appl. Sci. 2021, 11(4), 1716; https://doi.org/10.3390/app11041716 - 15 Feb 2021
Cited by 18 | Viewed by 2021
Abstract
Any damaged condition is a rare occurrence for mechanical systems, as it is very unlikely to be observed. Thus, it represents an extreme deviation from the median of its probability distribution. It is, therefore, necessary to apply proper statistical solutions, i.e., Rare Event [...] Read more.
Any damaged condition is a rare occurrence for mechanical systems, as it is very unlikely to be observed. Thus, it represents an extreme deviation from the median of its probability distribution. It is, therefore, necessary to apply proper statistical solutions, i.e., Rare Event Modelling (REM). The classic tool for this aim is the Extreme Value Theory (EVT), which deals with uni- or multivariate scalar values. The Extreme Function Theory (EFT), on the other hand, is defined by enlarging the fundamental EVT concepts to whole functions. When combined with Gaussian Process Regression (GPR), the EFT is perfectly suited for mode shape-based outlier detection. In fact, it is possible to investigate the structure’s normal modes as a whole rather than focusing on their constituent data points, with quantifiable advantages. This provides a useful tool for Structural Health Monitoring, especially to reduce false alarms. This recently proposed methodology is here tested and validated both numerically and experimentally for different examples coming from Civil and Aerospace Engineering applications. One-dimensional beamlike elements with several boundary conditions are considered, as well as a two-dimensional plate-like spar and a frame structure. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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22 pages, 10603 KiB  
Article
Full-Field Strain Reconstruction Using Uniaxial Strain Measurements: Application to Damage Detection
by Rinto Roy, Marco Gherlone, Cecilia Surace and Alexander Tessler
Appl. Sci. 2021, 11(4), 1681; https://doi.org/10.3390/app11041681 - 13 Feb 2021
Cited by 13 | Viewed by 1919
Abstract
This work investigates the inverse problem of reconstructing the continuous displacement field of a structure using a spatially distributed set of discrete uniaxial strain data. The proposed technique is based on the inverse Finite Element Method (iFEM), which has been demonstrated to be [...] Read more.
This work investigates the inverse problem of reconstructing the continuous displacement field of a structure using a spatially distributed set of discrete uniaxial strain data. The proposed technique is based on the inverse Finite Element Method (iFEM), which has been demonstrated to be suitable for full-field displacement, and subsequently strain, reconstruction in beam and plate structures using discrete or continuous surface strain measurements. The iFEM uses a variationally based approach to displacement reconstruction, where an error functional is discretized using a set of finite elements. The effects of position and orientation of uniaxial strain measurements on the iFEM results are investigated, and the use of certain strain smoothing strategies for improving reconstruction accuracy is discussed. Reconstruction performance using uniaxial strain data is examined numerically using the problem of a thin plate with an internal crack. The results obtained highlight that strain field reconstruction using the proposed strategy can provide useful information regarding the presence, position, and orientation of damage on the plate. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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42 pages, 15316 KiB  
Article
Rail Diagnostics Based on Ultrasonic Guided Waves: An Overview
by Davide Bombarda, Giorgio Matteo Vitetta and Giovanni Ferrante
Appl. Sci. 2021, 11(3), 1071; https://doi.org/10.3390/app11031071 - 25 Jan 2021
Cited by 38 | Viewed by 8688
Abstract
Rail tracks undergo massive stresses that can affect their structural integrity and produce rail breakage. The last phenomenon represents a serious concern for railway management authorities, since it may cause derailments and, consequently, losses of rolling stock material and lives. Therefore, the activities [...] Read more.
Rail tracks undergo massive stresses that can affect their structural integrity and produce rail breakage. The last phenomenon represents a serious concern for railway management authorities, since it may cause derailments and, consequently, losses of rolling stock material and lives. Therefore, the activities of track maintenance and inspection are of paramount importance. In recent years, the use of various technologies for monitoring rails and the detection of their defects has been investigated; however, despite the important progresses in this field, substantial research efforts are still required to achieve higher scanning speeds and improve the reliability of diagnostic procedures. It is expected that, in the near future, an important role in track maintenance and inspection will be played by the ultrasonic guided wave technology. In this manuscript, its use in rail track monitoring is investigated in detail; moreover, both of the main strategies investigated in the technical literature are taken into consideration. The first strategy consists of the installation of the monitoring instrumentation on board a moving test vehicle that scans the track below while running. The second strategy, instead, is based on distributing the instrumentation throughout the entire rail network, so that continuous monitoring in quasi-real-time can be obtained. In our analysis of the proposed solutions, the prototypes and the employed methods are described. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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19 pages, 9427 KiB  
Article
Mooring-Failure Monitoring of Submerged Floating Tunnel Using Deep Neural Network
by Do-Soo Kwon, Chungkuk Jin, MooHyun Kim and Weoncheol Koo
Appl. Sci. 2020, 10(18), 6591; https://doi.org/10.3390/app10186591 - 21 Sep 2020
Cited by 18 | Viewed by 2468
Abstract
This paper presents a machine learning method for detecting the mooring failures of SFT (submerged floating tunnel) based on DNN (deep neural network). The floater-mooring-coupled hydro-elastic time-domain numerical simulations are conducted under various random wave excitations and failure/intact scenarios. Then, the big-data is [...] Read more.
This paper presents a machine learning method for detecting the mooring failures of SFT (submerged floating tunnel) based on DNN (deep neural network). The floater-mooring-coupled hydro-elastic time-domain numerical simulations are conducted under various random wave excitations and failure/intact scenarios. Then, the big-data is collected at various locations of numerical motion sensors along the SFT to be used for the present DNN algorithm. In the input layer, tunnel motion-sensor signals and wave conditions are inputted while the output layer provides the probabilities of 21 failure scenarios. In the optimization stage, the numbers of hidden layers, neurons of each layer, and epochs for reliable performance are selected. Several activation functions and optimizers are also tested for the present DNN model, and Sigmoid function and Adamax are respectively adopted to enhance the classification accuracy. Moreover, a systematic sensitivity test with respect to the numbers and arrangements of sensors is performed to find the appropriate sensor combination to achieve target prediction accuracy. The technique of confusion matrix is used to represent the accuracy of the DNN algorithms for various cases, and the classification accuracy as high as 98.1% is obtained with seven sensors. The results of this study demonstrate that the DNN model can effectively monitor the mooring failures of SFTs utilizing real-time sensor signals. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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19 pages, 6744 KiB  
Article
Damping of Beam Vibrations Using Tuned Particles Impact Damper
by Mateusz Żurawski and Robert Zalewski
Appl. Sci. 2020, 10(18), 6334; https://doi.org/10.3390/app10186334 - 11 Sep 2020
Cited by 13 | Viewed by 3246
Abstract
The presented paper reveals an innovative device which is the Tuned Particle Impact Damper (TPID). The damper enables the user change the dynamical features of the vibrating system thanks to rapidly tuning the volume of the container where the grains are locked. The [...] Read more.
The presented paper reveals an innovative device which is the Tuned Particle Impact Damper (TPID). The damper enables the user change the dynamical features of the vibrating system thanks to rapidly tuning the volume of the container where the grains are locked. The effectiveness of proposed semi-active damping methodology was confirmed in experiments on vibrations of a cantilever beam excited by kinematic rule. Various damping characteristics captured for different volumes of the grains container and mass of granular material are presented. It is confirmed that the proposed TPID device allowed for efficient attenuation of the beam’s vibration amplitude in the range of its resonant frequency vibrations. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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12 pages, 4466 KiB  
Article
Health and Structural Integrity of Monitoring Systems: The Case Study of Pressurized Pipelines
by Vladimír Chmelko, Martin Garan, Miroslav Šulko and Marek Gašparík
Appl. Sci. 2020, 10(17), 6023; https://doi.org/10.3390/app10176023 - 31 Aug 2020
Cited by 5 | Viewed by 1772
Abstract
In the operation of some structures, particularly in energy or chemical industry where pressurized pipeline systems are employed, certain unexpected critical situations may occur, which must be definitely avoided. Otherwise, such situations would result in undesirable damage to the environment or even the [...] Read more.
In the operation of some structures, particularly in energy or chemical industry where pressurized pipeline systems are employed, certain unexpected critical situations may occur, which must be definitely avoided. Otherwise, such situations would result in undesirable damage to the environment or even the endangerment of human life. For example, the occurrence of such nonstandard states can significantly affect the safety of high-pressure pipeline systems. The following paper discusses basic physical prerequisites for assembling the systems that can sense loading states and monitor the operational safety conditions of pressure piping systems in the long-run. The appropriate monitoring system hardware with cost-effective data management was designed in order to enable the real-time monitoring of operational safety parameters. Furthermore, the paper presents the results obtained from the measurements of existing real-time safety monitoring systems for selected pipeline systems. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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14 pages, 18400 KiB  
Article
Strain Response Characteristics of RC Beams Strengthened with CFRP Sheet Using BOTDR
by Ki-Nam Hong, Won-Bo Shim, Yeong-Mo Yeon and Kyu-San Jeong
Appl. Sci. 2020, 10(17), 6005; https://doi.org/10.3390/app10176005 - 29 Aug 2020
Cited by 1 | Viewed by 1775
Abstract
This paper presents the structural behaviors of reinforced concrete (RC) beams that have been strengthened with carbon-fiber-reinforced polymer (CFRP) sheets experimentally and numerically. Test specimens were subjected to four-point bending, and structural behavior was observed using a strain gauge and a Brillouin optical [...] Read more.
This paper presents the structural behaviors of reinforced concrete (RC) beams that have been strengthened with carbon-fiber-reinforced polymer (CFRP) sheets experimentally and numerically. Test specimens were subjected to four-point bending, and structural behavior was observed using a strain gauge and a Brillouin optical time domain reflectometer (BOTDR) sensor. Non-linear finite element analysis was conducted to examine the applicability and reliability of numerical models using the commercial finite element code, LS-DYNA. In the results, the de-bonded section between the beam substrate and CFRP sheet affected the initial crack in the structure, while the ultimate load, which is related to structural failure, was unaffected. The predicted results correlated well with the experimental observations in terms of the trend of the load-displacement curve, initial crack load, ultimate load and failure mode. Additionally, it is shown that the de-bonding behaviors in the interface were examined using the strain distributions for the CFRP sheets through the experiment and numerical simulations. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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23 pages, 5849 KiB  
Article
Bayesian Calibration of Hysteretic Parameters with Consideration of the Model Discrepancy for Use in Seismic Structural Health Monitoring
by Rosario Ceravolo, Alessio Faraci and Gaetano Miraglia
Appl. Sci. 2020, 10(17), 5813; https://doi.org/10.3390/app10175813 - 22 Aug 2020
Cited by 5 | Viewed by 2618
Abstract
Bayesian model calibration techniques are commonly employed in the characterization of nonlinear dynamic systems, as they provide a conceptual and effective framework to deal with model uncertainties, experimental errors and procedure assumptions. This understanding has resulted in the need to introduce a model [...] Read more.
Bayesian model calibration techniques are commonly employed in the characterization of nonlinear dynamic systems, as they provide a conceptual and effective framework to deal with model uncertainties, experimental errors and procedure assumptions. This understanding has resulted in the need to introduce a model discrepancy term to account for the differences between model-based predictions and real observations. Indeed, the goal of this work is to investigate model-driven seismic structural health monitoring procedures based on a Bayesian uncertainty quantification framework, and thus make relevant considerations for its use in the seismic structural health monitoring, focusing on masonry structures. Specifically, the Bayesian inference has been applied to the calibration of nonlinear hysteretic systems to both provide: (i) most probable values (MPV) of the parameters following the calibration; and (ii) estimates of the model discrepancy posterior distribution. The effect of the model discrepancy in the calibration is first illustrated recurring to a single degree of freedom using a Bouc–Wen type oscillator as a numerical benchmark. The model discrepancy is then introduced for calibrating a reference nonlinear Bouc–Wen model derived from real data acquired on a monitored masonry building. The main novelty of this study is the application of the framework of uncertainty quantification on models representing data measured directly on masonry structures during seismic events. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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14 pages, 2761 KiB  
Article
Piezoelectric Electro-Mechanical Impedance (EMI) Based Structural Crack Monitoring
by Tao Wang, Bohai Tan, Mingge Lu, Zheng Zhang and Guangtao Lu
Appl. Sci. 2020, 10(13), 4648; https://doi.org/10.3390/app10134648 - 05 Jul 2020
Cited by 25 | Viewed by 3166
Abstract
To detect small cracks in plate like structures, the high frequency characteristics of local dynamics were studied with the piezoelectric electro-mechanical impedance (EMI) method, and damages were monitored by the changes of the EMI. The finite element simulation model of EMI was established, [...] Read more.
To detect small cracks in plate like structures, the high frequency characteristics of local dynamics were studied with the piezoelectric electro-mechanical impedance (EMI) method, and damages were monitored by the changes of the EMI. The finite element simulation model of EMI was established, and numerical analysis was conducted. The simulation results indicated that the peak frequency of the piezoelectric admittance signal is a certain order resonance frequency of the structure, and the piezoelectric impedance method could effectively detect the dynamic characteristics of the structure. The piezoelectric admittance simulation and experimental study of aluminum beams with different crack sizes were performed. Simulation and experimental results revealed that the peak admittance frequency decreases with the increase of crack size, and the higher resonance frequency is more sensitive to the small-scale damage. The proposed method has good repeatability and strong signal-to-noise ratio to monitor the occurrence and development of small-scale crack damage, and it has an important application prospect. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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24 pages, 10191 KiB  
Article
Robust Structural Damage Detection Using Analysis of the CMSE Residual’s Sensitivity to Damage
by Mingqiang Xu, Shuqing Wang, Jian Guo and Yingchao Li
Appl. Sci. 2020, 10(8), 2826; https://doi.org/10.3390/app10082826 - 19 Apr 2020
Cited by 5 | Viewed by 2013
Abstract
This paper presents a robust damage identification scheme in which damage is predicted by solving the cross-modal strain energy (CMSE) linear system of equations. This study aims to address the excessive equations issue faced in the assemblage of the CMSE system. A sensitivity [...] Read more.
This paper presents a robust damage identification scheme in which damage is predicted by solving the cross-modal strain energy (CMSE) linear system of equations. This study aims to address the excessive equations issue faced in the assemblage of the CMSE system. A sensitivity index that, to some extent, measures how the actual damage level vector satisfies each CMSE equation, is derived by performing an analysis of the defined residual’s sensitivity to damage. The index can be used to eliminate redundant equations and enhance the robustness of the CMSE system. Moreover, to circumvent a potentially ill-conditioned problem, a previously published iterative Tikhonov regularization method is adopted to solve the CMSE system. Some improvements to this method for determining the iterative regularization parameter and regularization operator are given. The numerical robustness of the proposed damage identification scheme against measurement noise is proved by analyzing a 2-D truss structure. The effects of location and extent of damage on the damage identification results are investigated. Furthermore, the feasibility of the proposed scheme for damage identification is experimentally validated on a beam structure. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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20 pages, 9333 KiB  
Article
A Novel Dense Full-Field Displacement Monitoring Method Based on Image Sequences and Optical Flow Algorithm
by Guojun Deng, Zhixiang Zhou, Shuai Shao, Xi Chu and Chuanyi Jian
Appl. Sci. 2020, 10(6), 2118; https://doi.org/10.3390/app10062118 - 20 Mar 2020
Cited by 16 | Viewed by 2550
Abstract
This paper aims to achieve a large bridge structural health monitoring (SHM) efficiently, economically, credibly, and holographically through noncontact remote sensing (NRS). For these purposes, the author proposes a NRS method for collecting the holographic geometric deformation of test bridge, using static image [...] Read more.
This paper aims to achieve a large bridge structural health monitoring (SHM) efficiently, economically, credibly, and holographically through noncontact remote sensing (NRS). For these purposes, the author proposes a NRS method for collecting the holographic geometric deformation of test bridge, using static image sequences. Specifically, a uniaxial automatic cruise acquisition device was designed to collect static images on bridge elevation under different damage conditions. Considering the strong spatiotemporal correlations of the sequence data, the relationships between six fixed fields of view were identified through the SIFT algorithm. On this basis, the deformation of the bridge structure was obtained by tracking a virtual target using the optical flow algorithm. Finally, the global holographic deformation of the test bridge was derived. The research results show that: The output data of our NRS method are basically consistent with the finite-element prediction (maximum error: 11.11%) and dial gauge measurement (maximum error: 12.12%); the NRS method is highly sensitive to the actual deformation of the bridge structure under different damage conditions, and can capture the deformation in a continuous and accurate manner. The research findings lay a solid basis for structure state interpretation and intelligent damage identification. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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23 pages, 11620 KiB  
Article
Railway Wheel Flat Recognition and Precise Positioning Method Based on Multisensor Arrays
by Chenyi Zhou, Liang Gao, Hong Xiao and Bowen Hou
Appl. Sci. 2020, 10(4), 1297; https://doi.org/10.3390/app10041297 - 14 Feb 2020
Cited by 17 | Viewed by 3675
Abstract
Wheel flats have become a major problem affecting the long-term service of railway systems. Wheels with flats create intermittent impact loads to trains and rails. This not only accelerates the deterioration of vehicle and track components but also leads to abnormal wheel-rail contact [...] Read more.
Wheel flats have become a major problem affecting the long-term service of railway systems. Wheels with flats create intermittent impact loads to trains and rails. This not only accelerates the deterioration of vehicle and track components but also leads to abnormal wheel-rail contact conditions. An effective method for detecting wheel conditions is urgently needed to ensure the operation of the railway and provide guidance for the repair of wheels. However, most previous researches have used qualitative detection methods, and hence have been unable to achieve accurate positioning of the wheel flats. In addition, the theoretical basis for the layout scheme for wheel flat detection sensors is lacking, making it impossible to meet the needs of field applications. In this study, we simulated the spatial distribution characteristics of rail strain, under different wheel flat conditions, and based on this, a layout scheme of multisensor arrays was proposed which more effectively captured the responses of the wheel flats. A wheel flat recognition and precise positioning method based on multisensor fusion was designed. The algorithm was validated through the combination of experimental and simulation methods. The result shows that the algorithm can ideally detect and locate the wheel flats under complex conditions. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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16 pages, 6404 KiB  
Article
Monitoring and Analysis of Dynamic Characteristics of Super High-rise Buildings using GB-RAR: A Case Study of the WGC under Construction, China
by Lv Zhou, Jiming Guo, Xuelin Wen, Jun Ma, Fei Yang, Cheng Wang and Di Zhang
Appl. Sci. 2020, 10(3), 808; https://doi.org/10.3390/app10030808 - 23 Jan 2020
Cited by 10 | Viewed by 3053
Abstract
Accurate dynamic characteristics of super high-rise buildings serve as a guide in their construction and operation. Ground-based real aperture radar (GB-RAR) techniques have been applied in monitoring and analyzing the dynamic characteristics of different buildings, but only few studies have utilized them to [...] Read more.
Accurate dynamic characteristics of super high-rise buildings serve as a guide in their construction and operation. Ground-based real aperture radar (GB-RAR) techniques have been applied in monitoring and analyzing the dynamic characteristics of different buildings, but only few studies have utilized them to derive the dynamic characteristics of super high-rise buildings, especially those higher than 400 m and under construction. In this study, we proposed a set of technical methods for monitoring and analyzing the dynamic characteristics of super high-rise buildings based on GB-RAR and wavelet analysis. A case study was conducted on the monitoring and analysis of the dynamic characteristics of the Wuhan Greenland Center (WGC) under construction (5–7 July 2017) with a 636 m design height. Displacement time series was accurately derived through GB-RAR and wavelet analysis, and the accuracy reached the submillimeter level. The maximum horizontal displacement amplitudes at the top of the building in the north–south and east–west directions were 18.84 and 15.94 mm, respectively. The roof displacement trajectory of the WGC was clearly identified. A certain negative correlation between the temperature and displacement changes at the roof of the building was identified. Study results demonstrate that the proposed method is effective for the dynamic monitoring and analysis of super high-rise buildings with noninvasive and nondestructive characteristics. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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Review

Jump to: Editorial, Research

14 pages, 1026 KiB  
Review
State-of-the-Art Review on Determining Prestress Losses in Prestressed Concrete Girders
by Marco Bonopera, Kuo-Chun Chang and Zheng-Kuan Lee
Appl. Sci. 2020, 10(20), 7257; https://doi.org/10.3390/app10207257 - 16 Oct 2020
Cited by 35 | Viewed by 4023
Abstract
Prestressing methods were used to realize long-span bridges in the last few decades. For their predictive maintenance, devices and dynamic nondestructive procedures for identifying prestress losses were mainly developed since serviceability and safety of Prestressed Concrete (PC) girders depend on the effective state [...] Read more.
Prestressing methods were used to realize long-span bridges in the last few decades. For their predictive maintenance, devices and dynamic nondestructive procedures for identifying prestress losses were mainly developed since serviceability and safety of Prestressed Concrete (PC) girders depend on the effective state of prestressing. In fact, substantial long term prestress losses can induce excessive deflections and cracking in large span PC bridge girders. However, old unsolved problematics as well as new challenges exist since a variation in prestress force does not significantly affect the vibration responses of such PC girders. As a result, this makes uncertain the use of natural frequencies as appropriate parameters for prestress loss determinations. Thus, amongst emerging techniques, static identification based on vertical deflections has preliminary proved to be a reliable method with the goal to become a dominant approach in the near future. In fact, measured vertical deflections take accurately and instantaneously into account the changes of structural geometry of PC girders due to prestressing losses on the equilibrium conditions, in turn caused by the combined effects of tendon relaxation, concrete creep and shrinkage, and parameters of real environment as, e.g., temperature and relative humidity. Given the current state of quantitative and principled methodologies, this paper represents a state-of-the-art review of some important research works on determining prestress losses conducted worldwide. The attention is principally focused on a static nondestructive method, and a comparison with dynamic ones is elaborated. Comments and recommendations are made at proper places, while concluding remarks including future studies and field developments are mentioned at the end of the paper. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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34 pages, 1791 KiB  
Review
Application of the Subspace-Based Methods in Health Monitoring of Civil Structures: A Systematic Review and Meta-Analysis
by Hoofar Shokravi, Hooman Shokravi, Norhisham Bakhary, Mahshid Heidarrezaei, Seyed Saeid Rahimian Koloor and Michal Petrů
Appl. Sci. 2020, 10(10), 3607; https://doi.org/10.3390/app10103607 - 22 May 2020
Cited by 29 | Viewed by 3709
Abstract
A large number of research studies in structural health monitoring (SHM) have presented, extended, and used subspace system identification. However, there is a lack of research on systematic literature reviews and surveys of studies in this field. Therefore, the current study is undertaken [...] Read more.
A large number of research studies in structural health monitoring (SHM) have presented, extended, and used subspace system identification. However, there is a lack of research on systematic literature reviews and surveys of studies in this field. Therefore, the current study is undertaken to systematically review the literature published on the development and application of subspace system identification methods. In this regard, major databases in SHM, including Scopus, Google Scholar, and Web of Science, have been selected and preferred reporting items for systematic reviews and meta-analyses (PRISMA) has been applied to ensure complete and transparent reporting of systematic reviews. Along this line, the presented review addresses the available studies that employed subspace-based techniques in the vibration-based damage detection (VDD) of civil structures. The selected papers in this review were categorized into authors, publication year, name of journal, applied techniques, research objectives, research gap, proposed solutions and models, and findings. This study can assist practitioners and academicians for better condition assessment of structures and to gain insight into the literature. Full article
(This article belongs to the Special Issue Novel Approaches for Structural Health Monitoring)
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