Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures

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

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 50219

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Guest Editor
Department of Environmental Engineering, University of Calabria, Via P. Bucci Cubo 44A, 87036 Rende, Italy
Interests: structural health monitoring (SHM); self-monitoring materials and structures; computational mechanics; civil infrastructures
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Guest Editor
Department of Civil Engineering, University of Calabria, 87036 Rende, Italy
Interests: terrestrial laser scanner; virtual reality-augmented reality (VR/AR); frequency-based analysis; structures monitoring; landslides monitoring; GIS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There can be many reasons a civil infrastructure can deteriorate. First of all, the age of the structure—the passage of time can cause the phenomena of decay of mechanical and/or geometric characteristics as a result of fatigue, corrosion, relaxation, and so on, but also, seismic events or fire can damage it.

Until the last century, the concept of infrastructure maintenance was linked to episodic control, through static methods and the destructive or non-destructive investigation of materials and of parts of the structure. Today, the availability of new sensors or new materials, new methods of computerized analysis, and new data transmission systems, allows for the constant monitoring of civil infrastructures.

This gives rise to the concept of structural health, and, in particular, its monitoring. To achieve this purpose, sensors capable of instantaneously communicating their measurements to data processing systems, computational techniques for the definition of the structural behavior, and data communication, even at a distance, in a fast and safe way, were developed. These sensors are often dynamic, optical, wired, or wireless, and they are also accompanied by new materials with self-monitoring characteristics.

An important role is then played by the computational mechanics for the analysis of the behavior of the structure and the correct interpretation of the signals coming from the sensors, the geomatic methods for the definition of the geometry, and of its variation (both static and dynamic) as well as during the phases of use of the infrastructure, the Internet of things (i.o.t.)  for the management of data storage and transmission (especially in areas where there is no electricity), and, finally, the  new materials (in particular self-monitoring materials).

Therefore, in this Special Issue, in order to establish the state-of-the-art on the subject and to identify new challenges for the near future, we invite the publication of research results in each of these fields, namely: computational mechanics; geomatics; new materials, with particular regard to self-monitoring ones; and the use of I.o.T technologies, for the common purpose of constantly evaluating the structural health of civil infrastructures.

Prof. Raffaele Zinno
Dr. Serena Artese
Guest editors

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Keywords

  • Structural Health Monitoring (SHM)
  • Self-monitoring materials and structures
  • Computational Mechanics
  • I.O.T. for S.H.M.
  • Geomatics
  • Civil Infrastructures

Published Papers (15 papers)

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Editorial

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4 pages, 198 KiB  
Editorial
Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures
by Raffaele Zinno and Serena Artese
Appl. Sci. 2021, 11(3), 1140; https://0-doi-org.brum.beds.ac.uk/10.3390/app11031140 - 26 Jan 2021
Cited by 4 | Viewed by 1433
Abstract
Starting from the early years of the 21st century, the problem of monitoring the physical–chemical–mechanical conditions of structures and infrastructures for civil use began to be thought in a significantly different way than in the last century [...] Full article

Research

Jump to: Editorial, Review

16 pages, 5751 KiB  
Article
Study on the Method of Moving Load Identification Based on Strain Influence Line
by Jing Yang, Peng Hou, Caiqian Yang and Yang Zhang
Appl. Sci. 2021, 11(2), 853; https://0-doi-org.brum.beds.ac.uk/10.3390/app11020853 - 18 Jan 2021
Cited by 7 | Viewed by 2026
Abstract
In order to improve the accuracy of load identification and study the influence of transverse distribution, a novel method was proposed for the moving load identification based on strain influence line and the load transverse distribution under consideration. The load identification theory based [...] Read more.
In order to improve the accuracy of load identification and study the influence of transverse distribution, a novel method was proposed for the moving load identification based on strain influence line and the load transverse distribution under consideration. The load identification theory based on strain influence line was derived, and the strain integral coefficient was proposed for the identification. A series of numerical simulations and experiments were carried out to verify the method. The numerical results showed that the method without considering the load transverse distribution was not suitable for solving the space problem, and the method with the load transverse distribution under consideration has a high identification accuracy and excellent anti-noise performance. The experimental results showed that the speed identification error was smaller than ±5%, and the vehicle speed had no obvious influence on the identification results of the vehicle weight. Moreover, the average identification error of the vehicle weight was smaller than ±10%, and the error of more than 90% of samples was smaller than ±5%. Full article
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21 pages, 6750 KiB  
Article
Health Monitoring of Stress-Laminated Timber Bridges Assisted by a Hygro-Thermal Model for Wood Material
by Stefania Fortino, Petr Hradil, Keijo Koski, Antti Korkealaakso, Ludovic Fülöp, Hauke Burkart and Timo Tirkkonen
Appl. Sci. 2021, 11(1), 98; https://0-doi-org.brum.beds.ac.uk/10.3390/app11010098 - 24 Dec 2020
Cited by 6 | Viewed by 2533
Abstract
Timber bridges are economical, easy to construct, use renewable material and can have a long service life, especially in Nordic climates. Nevertheless, durability of timber bridges has been a concern of designers and structural engineers because most of their load-carrying members are exposed [...] Read more.
Timber bridges are economical, easy to construct, use renewable material and can have a long service life, especially in Nordic climates. Nevertheless, durability of timber bridges has been a concern of designers and structural engineers because most of their load-carrying members are exposed to the external climate. In combination with certain temperatures, the moisture content (MC) accumulated in wood for long periods may cause conditions suitable for timber biodegradation. In addition, moisture induced cracks and deformations are often found in timber decks. This study shows how the long term monitoring of stress-laminated timber decks can be assisted by a recent multi-phase finite element model predicting the distribution of MC, relative humidity (RH) and temperature (T) in wood. The hygro-thermal monitoring data are collected from an earlier study of the Sørliveien Bridge in Norway and from a research on the new Tapiola Bridge in Finland. In both cases, the monitoring uses integrated humidity-temperature sensors which provide the RH and T in given locations of the deck. The numerical results show a good agreement with the measurements and allow analysing the MCs at the bottom of the decks that could be responsible of cracks and cupping deformations. Full article
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11 pages, 1624 KiB  
Article
Archetypal Use of Artificial Intelligence for Bridge Structural Monitoring
by Bernardino Chiaia and Valerio De Biagi
Appl. Sci. 2020, 10(20), 7157; https://0-doi-org.brum.beds.ac.uk/10.3390/app10207157 - 14 Oct 2020
Cited by 2 | Viewed by 1781
Abstract
Structural monitoring is a research topic that is receiving more and more attention, especially in light of the fact that a large part our infrastructural heritage was built in the Sixties and is aging and approaching the end of its design working life. [...] Read more.
Structural monitoring is a research topic that is receiving more and more attention, especially in light of the fact that a large part our infrastructural heritage was built in the Sixties and is aging and approaching the end of its design working life. The detection of damage is usually performed through artificial intelligence techniques. In contrast, tools for the localization and the estimation of the extent of the damage are limited, mainly due to the complete datasets of damages needed for training the system. The proposed approach consists in numerically generating datasets of damaged structures on the basis of random variables representing the actions and the possible damages. Neural networks were trained to perform the main structural monitoring tasks: damage detection, localization, and estimation. The artificial intelligence tool interpreted the measurements on a real structure. To simulate real measurements more accurately, noise was added to the synthetic dataset. The results indicate that the accuracy of the measurement devices plays a relevant role in the quality of the monitoring. Full article
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21 pages, 8874 KiB  
Article
Evaluation of Long-Range Mobile Mapping System (MMS) and Close-Range Photogrammetry for Deformation Monitoring. A Case Study of Cortes de Pallás in Valencia (Spain)
by Francesco Di Stefano, Miriam Cabrelles, Luis García-Asenjo, José Luis Lerma, Eva Savina Malinverni, Sergio Baselga, Pascual Garrigues and Roberto Pierdicca
Appl. Sci. 2020, 10(19), 6831; https://0-doi-org.brum.beds.ac.uk/10.3390/app10196831 - 29 Sep 2020
Cited by 12 | Viewed by 3000
Abstract
This contribution describes the methodology applied to evaluate the suitability of a Long-Range Mobile Mapping System to be integrated with other techniques that are currently used in a large and complex landslide deformation monitoring project carried out in Cortes de Pallás, in Valencia [...] Read more.
This contribution describes the methodology applied to evaluate the suitability of a Long-Range Mobile Mapping System to be integrated with other techniques that are currently used in a large and complex landslide deformation monitoring project carried out in Cortes de Pallás, in Valencia (Spain). Periodical geodetic surveys provide a reference frame realized by 10 pillars and 15 additional check points placed in specific points of interest, all with millimetric accuracy. The combined use of Close-Range Photogrammetry provides a well-controlled 3D model with 1–3 cm accuracy, making the area ideal for testing new technologies. Since some zones of interest are usually obstructed by construction, trees, or lamp posts, a possible solution might be the supplementary use of dynamic scanning instruments with the mobile mapping solution Kaarta Stencil 2 to collect the missing data. However, the reliability of this technology has to be assessed and validated before being integrated into the existing 3D models in the well-controlled area of Cortes de Pallás. The results of the experiment show that the accuracy achieved are compatible with those obtained from Close-Range Photogrammetry and can also be safely used to supplement image-based information for monitoring with 3–8 cm overall accuracy. Full article
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15 pages, 10311 KiB  
Article
Determination of Axial Force in Tie Rods of Historical Buildings Using the Model-Updating Technique
by Ivan Duvnjak, Suzana Ereiz, Domagoj Damjanović and Marko Bartolac
Appl. Sci. 2020, 10(17), 6036; https://0-doi-org.brum.beds.ac.uk/10.3390/app10176036 - 31 Aug 2020
Cited by 8 | Viewed by 3568
Abstract
Tie rods are structural elements that transfer axial tensile loads and are typically used on walls, vaults, arches, and buttresses in historical buildings. To verify their load-bearing capacity and identify possible structural damage risks, the forces transferred by tie rods and the corresponding [...] Read more.
Tie rods are structural elements that transfer axial tensile loads and are typically used on walls, vaults, arches, and buttresses in historical buildings. To verify their load-bearing capacity and identify possible structural damage risks, the forces transferred by tie rods and the corresponding stresses must be determined. However, this is often a challenging task due to the lack of project documentation for historical buildings. Uncertainties like complex boundary conditions or unknown material and geometrical properties make it hard to assess the tie rods’ load level. This paper presents a methodology for the determination of axial forces in tie rods that combines on-site experimental research and a numerical model-updating technique. Along with the common approach based on a determination of the natural frequency of tie rods, this paper presents an approach based on tie rods’ mode shapes. Special emphasis is placed on the boundary conditions coefficient, which is a crucial parameter in the analytical solution for axial forces determination based on the conducted on-site experiments. The method is applied in a historical building case study. Full article
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20 pages, 6678 KiB  
Article
TLS and GB-RAR Measurements of Vibration Frequencies and Oscillation Amplitudes of Tall Structures: An Application to Wind Towers
by Serena Artese and Giovanni Nico
Appl. Sci. 2020, 10(7), 2237; https://0-doi-org.brum.beds.ac.uk/10.3390/app10072237 - 25 Mar 2020
Cited by 24 | Viewed by 3050
Abstract
This article presents a methodology for the monitoring of tall structures based on the joint use of a terrestrial laser scanner (TLS), configured in line scanner mode, and a ground-based real aperture radar (GB-RAR) interferometer. The methodology provides both natural frequencies and oscillation [...] Read more.
This article presents a methodology for the monitoring of tall structures based on the joint use of a terrestrial laser scanner (TLS), configured in line scanner mode, and a ground-based real aperture radar (GB-RAR) interferometer. The methodology provides both natural frequencies and oscillation amplitudes of tall structures. Acquisitions of the surface of the tall structure are performed by the TLS with a high sampling rate: each line scan provides an instantaneous longitudinal section. By interpolating the points of each line, oscillation profiles are estimated with a much better precision than each single point. The amplitude and frequency of the main oscillation mode of the whole structure are derived from the TLS profiles. GB-RAR measurements are used to measure the vibration frequencies of higher oscillation modes which are not caught by the TLS due its lower precision in the measurement of displacements. In contrast, the high spatial resolution of TLS measurements provides an accurate description of oscillation amplitude along the tower, which cannot be caught by the GB-RAR, due to its poorer spatial resolution. TLS and GB-RAR acquisitions are simultaneous. The comparison with the analytical solution for oscillation modes demonstrates that the proposed methodology can provide useful information for structural health monitoring (SHM). The methodology does not require the use of targets on the structure and it can be applied during its normal use, even in presence of dynamic loads (wind, traffic vibrations, etc.). A test was carried out on a wind tower where the synergistic use of TLS and GB-RAR made it possible to fully describe the spectral properties of the tower and at the same time measure the amplitude of the first oscillation mode along the tower with a high spatial resolution. Full article
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19 pages, 11392 KiB  
Article
An Efficient Pipeline to Obtain 3D Model for HBIM and Structural Analysis Purposes from 3D Point Clouds
by Massimiliano Pepe, Domenica Costantino and Alfredo Restuccia Garofalo
Appl. Sci. 2020, 10(4), 1235; https://0-doi-org.brum.beds.ac.uk/10.3390/app10041235 - 12 Feb 2020
Cited by 83 | Viewed by 6214
Abstract
The aim of this work is to identify an efficient pipeline in order to build HBIM (heritage building information modelling) and create digital models to be used in structural analysis. To build accurate 3D models it is first necessary to perform a geomatics [...] Read more.
The aim of this work is to identify an efficient pipeline in order to build HBIM (heritage building information modelling) and create digital models to be used in structural analysis. To build accurate 3D models it is first necessary to perform a geomatics survey. This means performing a survey with active or passive sensors and, subsequently, accomplishing adequate post-processing of the data. In this way, it is possible to obtain a 3D point cloud of the structure under investigation. The next step, known as “scan-to-BIM (building information modelling)”, has led to the creation of an appropriate methodology that involved the use of Rhinoceros software and a few tools developed within this environment. Once the 3D model is obtained, the last step is the implementation of the structure in FEM (finite element method) and/or in HBIM software. In this paper, two case studies involving structures belonging to the cultural heritage (CH) environment are analysed: a historical church and a masonry bridge. In particular, for both case studies, the different phases were described involving the construction of the point cloud and, subsequently, the construction of a 3D model. This model is suitable both for structural analysis and for the parameterization of rheological and geometric information of each single element of the structure. Full article
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23 pages, 6389 KiB  
Article
TLS for Dynamic Measurement of the Elastic Line of Bridges
by Serena Artese and Raffaele Zinno
Appl. Sci. 2020, 10(3), 1182; https://0-doi-org.brum.beds.ac.uk/10.3390/app10031182 - 10 Feb 2020
Cited by 24 | Viewed by 3229
Abstract
The evaluation of the structural health of a bridge and the monitoring of its bearing capacity are performed by measuring different parameters. The most important ones are the displacements due to fixed or mobile loads, whose monitoring can be performed using several methods, [...] Read more.
The evaluation of the structural health of a bridge and the monitoring of its bearing capacity are performed by measuring different parameters. The most important ones are the displacements due to fixed or mobile loads, whose monitoring can be performed using several methods, both conventional and innovative. Terrestrial Laser Scanner (TLS) is effectively used to obtain the displacements of the decks for static loads, while for dynamic measurements, several punctual sensors are in general used. The proposed system uses a TLS, set as a line scanner and positioned under the bridge deck. The TLS acquires a vertical section of the intrados, or a line along a section to be monitored. The instantaneous deviations between the lines detected in dynamic conditions and the reference one acquired with the unloaded bridge, allow to extract the displacements and, consequently, the elastic curve. The synchronization of TLS acquisitions and load location, obtained from a Global Navigation Satellite System GNSS receiver or from a video, is an important feature of the method. Three tests were carried out on as many bridges. The first was performed during the maneuvers of a heavy truck traveling on a bridge characterized by a simply supported metal structure deck. The second concerned a prestressed concrete bridge with cantilever beams. The third concerned the pylon of a cantilever spar cable-stayed bridge during a load test. The results show high precision and confirm the usefulness of this method both for performing dynamic tests and for monitoring bridges. Full article
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17 pages, 4867 KiB  
Article
Categorization of the Condition of Railway Embankments Using a Multi-Attribute Utility Theory
by Meho Saša Kovačević, Mario Bačić, Irina Stipanović and Kenneth Gavin
Appl. Sci. 2019, 9(23), 5089; https://0-doi-org.brum.beds.ac.uk/10.3390/app9235089 - 25 Nov 2019
Cited by 11 | Viewed by 3342
Abstract
In the current economic climate, it is crucial to optimize the use of all resources regarding railway infrastructure maintenance. In this paper, a multi-attribute decision support framework is applied to categorize railway embankments in order to prioritize maintenance activities. The paper describes a [...] Read more.
In the current economic climate, it is crucial to optimize the use of all resources regarding railway infrastructure maintenance. In this paper, a multi-attribute decision support framework is applied to categorize railway embankments in order to prioritize maintenance activities. The paper describes a methodology to first determine the current condition of embankments using a combination of ground penetrating radar (GPR) surveys, visual inspection, and historical data about maintenance activities. These attributes are then used for the development of a multi-attribute utility theory model, which can be used as a support for decision making process for maintenance planning. The methodology is demonstrated for the categorization of 181 km of railway embankments in Croatia. Full article
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20 pages, 10703 KiB  
Article
An Overall Deformation Monitoring Method of Structure Based on Tracking Deformation Contour
by Xi Chu, Zhixiang Zhou, Guojun Deng, Xin Duan and Xin Jiang
Appl. Sci. 2019, 9(21), 4532; https://0-doi-org.brum.beds.ac.uk/10.3390/app9214532 - 25 Oct 2019
Cited by 16 | Viewed by 2881
Abstract
In structural deformation monitoring, traditional methods are mainly based on the deformation data measured at several individual points. As a result, only the discrete deformation, not the overall one, can be obtained, which hinders the researcher from a better and all-round understanding on [...] Read more.
In structural deformation monitoring, traditional methods are mainly based on the deformation data measured at several individual points. As a result, only the discrete deformation, not the overall one, can be obtained, which hinders the researcher from a better and all-round understanding on the structural behavior. At the same time, the surrounding area around the measuring structure is usually complicated, which notably escalates the difficulty in accessing the deformation data. In dealing with the said issues, a digital image-based method is proposed for the overall structural deformation monitoring, utilizing the image perspective transformation and edge detection. Due to the limitation on camera sites, the lens is usually not orthogonal to the measuring structure. As a result, the obtained image cannot be used to extract the deformation data directly. Thus, the perspective transformation algorithm is used to obtain the orthogonal projection image of the test beam under the condition of inclined photography, which enables the direct extraction of deformation data from the original image. Meanwhile, edge detection operators are used to detect the edge of structure’s orthogonal projection image, to further characterize the key feature of structural deformation. Using the operator, the complete deformation data of structural edge are obtained by locating and calibrating the edge pixels. Based on the above, a series of load tests has been carried out using a steel–concrete composite beam to validate the proposed method, with the implementation of traditional dial deformation gauges. It has been found that the extracted edge lines have an obvious sawtooth effect due to the illumination environment. The sawtooth effect makes the extracted edge lines slightly fluctuate around the actual contour of the structure. On this end, the fitting method is applied to minimize the fluctuation and obtain the linear approximation of the actual deflection curve. The deformation data obtained by the proposed method have been compared with the one measured by the dial meters, indicating that the measurement error of the proposed method is less than 5%. However, since the overall deformation data are continuously measured by the proposed method, it can better reflect the overall deformation of the structure, and moreover the structural health state, when compared with the traditional “point” measurements. Full article
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15 pages, 6767 KiB  
Article
Modeling of Temperature Time-Lag Effect for Concrete Box-Girder Bridges
by Kang Yang, Youliang Ding, Peng Sun, Hanwei Zhao and Fangfang Geng
Appl. Sci. 2019, 9(16), 3255; https://0-doi-org.brum.beds.ac.uk/10.3390/app9163255 - 09 Aug 2019
Cited by 25 | Viewed by 3812
Abstract
It is common to assume the relationship between temperature and temperature response is instantaneous in bridge health monitoring systems. However, a time-lag effect between temperature and thermal strain response has been documented by the analysis of monitored field data of concrete box-girder s. [...] Read more.
It is common to assume the relationship between temperature and temperature response is instantaneous in bridge health monitoring systems. However, a time-lag effect between temperature and thermal strain response has been documented by the analysis of monitored field data of concrete box-girder s. This effect is clearly reflected by the ring feature in the temperature-strain correlation curve. Inevitably, the time-lag effect has an adverse impact on the accuracy and reliability of state assessment and real-time warning for structural health monitoring (SHM) systems. To mitigate the influence of the time-lag effect, a phase-shifting method is proposed based on the Fourier series expansion fitting method. The time-domain signal is firstly converted into the frequency domain signal to compute the phase difference between temperature data and response strain data at each decomposed order. Subsequently, the total phase difference can be obtained by weighted summation. The signal processing effectively reduces the hysteresis loop area and enhances the correlation between the structural response data and the temperature data. When processing the daily data in different seasons, it is found that after subtraction by the proposed method, the linear feature becomes dominant in the relationship between temperature and the strain during long-term observation. Full article
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18 pages, 5229 KiB  
Article
Structural Reliability Estimation with Participatory Sensing and Mobile Cyber-Physical Structural Health Monitoring Systems
by Ekin Ozer and Maria Q. Feng
Appl. Sci. 2019, 9(14), 2840; https://0-doi-org.brum.beds.ac.uk/10.3390/app9142840 - 16 Jul 2019
Cited by 27 | Viewed by 3271
Abstract
With the help of community participants, smartphones can become useful wireless sensor network (WSN) components, form a self-governing structural health monitoring (SHM) system, and merge structural mechanics with participatory sensing and server computing. This paper presents a methodology and framework of such a [...] Read more.
With the help of community participants, smartphones can become useful wireless sensor network (WSN) components, form a self-governing structural health monitoring (SHM) system, and merge structural mechanics with participatory sensing and server computing. This paper presents a methodology and framework of such a cyber-physical system (CPS) that generates a bridge finite element model (FEM) integrated with vibration measurements from smartphone WSNs and centralized/distributed computational facilities, then assesses structural reliability based on updated FEMs. Structural vibration data obtained from smartphones are processed on a server to identify modal frequencies of an existing bridge. Without design drawings and supportive documentation but field measurements and observations, FEM of the bridge is drafted with uncertainties in the structural mass, stiffness, and boundary conditions (BCs). Then, 2700 FEMs are autonomously generated, and the baseline FEM is updated by minimizing the error between the crowdsourcing-based modal identification results and the FEM analysis. Furthermore, using 151 strong ground motion records from databases, the bridge response time history simulations are conducted to obtain displacement demand distribution. Finally, based on reference performance criteria, structural reliability of the bridge is estimated. Integrating the cyber (FEM analysis) and the physical (the bridge structure and measured vibration characteristics) worlds, this crowdsourcing-based CPS can provide a powerful tool for supporting rapid, remote, autonomous, and objective infrastructure-related decision-making. This study presents a new example of the emerging fourth industrial revolution from structural engineering and SHM perspective. Full article
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19 pages, 4745 KiB  
Article
Longitudinal Displacement Behavior and Girder End Reliability of a Jointless Steel-Truss Arch Railway Bridge during Operation
by Hanwei Zhao, Youliang Ding, Satish Nagarajaiah and Aiqun Li
Appl. Sci. 2019, 9(11), 2222; https://0-doi-org.brum.beds.ac.uk/10.3390/app9112222 - 30 May 2019
Cited by 18 | Viewed by 3960
Abstract
The long length and complex service load form conflicts with the low limits of longitudinal and transverse displacements of jointless bridge design. The longitudinal displacements of the Nanjing Dashengguan Yangtze River Bridge, a jointless steel-truss arch railway bridge, and its girder end reliability [...] Read more.
The long length and complex service load form conflicts with the low limits of longitudinal and transverse displacements of jointless bridge design. The longitudinal displacements of the Nanjing Dashengguan Yangtze River Bridge, a jointless steel-truss arch railway bridge, and its girder end reliability are investigated in this article. The time–frequency characteristics of the longitudinal displacements of bearings and expansion joints are analyzed using the empirical wavelet transform. The long-term characteristics of the longitudinal displacements of bearings and expansion joints in the operation period are explored. Furthermore, the relative transverse displacements of the bridge girder end are calculated using longitudinal displacement monitoring data. The mechanical behaviors of the expansion device under relative transverse displacements are studied. The reliability of expansion devices and crossing trains under the effects of relative transverse displacements is studied using kernel density estimation. The main results demonstrate that: (1) The longitudinal displacements of bearings and expansion joints are mainly influenced by environmental temperature. (2) The maximum relative transverse displacement of the expansion joint is close to 1 mm in long-term bridge operation, with the transverse rail deflection at the expansion device approaching 1 mm, which reduces the stability of cross high-speed trains. Full article
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Review

Jump to: Editorial, Research

29 pages, 658 KiB  
Review
Health Monitoring of Civil Infrastructures by Subspace System Identification Method: An Overview
by Hoofar Shokravi, Hooman Shokravi, Norhisham Bakhary, Seyed Saeid Rahimian Koloor and Michal Petrů
Appl. Sci. 2020, 10(8), 2786; https://0-doi-org.brum.beds.ac.uk/10.3390/app10082786 - 17 Apr 2020
Cited by 47 | Viewed by 4779
Abstract
Structural health monitoring (SHM) is the main contributor of the future’s smart city to deal with the need for safety, lower maintenance costs, and reliable condition assessment of structures. Among the algorithms used for SHM to identify the system parameters of structures, subspace [...] Read more.
Structural health monitoring (SHM) is the main contributor of the future’s smart city to deal with the need for safety, lower maintenance costs, and reliable condition assessment of structures. Among the algorithms used for SHM to identify the system parameters of structures, subspace system identification (SSI) is a reliable method in the time-domain that takes advantages of using extended observability matrices. Considerable numbers of studies have specifically concentrated on practical applications of SSI in recent years. To the best of author’s knowledge, no study has been undertaken to review and investigate the application of SSI in the monitoring of civil engineering structures. This paper aims to review studies that have used the SSI algorithm for the damage identification and modal analysis of structures. The fundamental focus is on data-driven and covariance-driven SSI algorithms. In this review, we consider the subspace algorithm to resolve the problem of a real-world application for SHM. With regard to performance, a comparison between SSI and other methods is provided in order to investigate its advantages and disadvantages. The applied methods of SHM in civil engineering structures are categorized into three classes, from simple one-dimensional (1D) to very complex structures, and the detectability of the SSI for different damage scenarios are reported. Finally, the available software incorporating SSI as their system identification technique are investigated. Full article
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