Advanced Methodologies and Technologies in Structural Monitoring

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 34154

Special Issue Editor


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Guest Editor
Department of Structural and Geotechnical Engineering, University “La Sapienza”, Via Eudossiana 18, 00184 Rome, Italy
Interests: thin-walled beams; structural stability; dynamic identification; structural monitoring; damage detection; perturbative approaches; optimal sensor placement; civil engineering
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Special Issue Information

Dear Colleagues,

The Special Issue “Advanced Methodologies and Technologies in Structural Monitoring” aims to collect the last findings in SHM. Both methodologies and technological advancements are welcome, as well as specific laboratory or in situ experimental studies or validations. Contributions can focus from the scale of material modelling to the structural one.

The topics of applications will include (but not be limited to):

  • Damage Detection
  • Modelling of Damages, Fractures, Defects and Cracks
  • Dynamic Identification
  • Inverse Problems in Structural Engineering
  • Model Updating
  • Machine learning in SHM
  • Sensor Network, Optimal Sensor Placement and Instrumentation Design
  • Sensor Technologies
  • Remote Monitoring

Dr. Egidio Lofrano
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural health monitoring
  • dynamic identification
  • damage detection
  • inverse problem
  • machine learning in SHM
  • sensor network
  • optimal sensor placement
  • sensor technologies
  • remote monitoring
  • instrumentation design

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Published Papers (10 papers)

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Research

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11 pages, 3306 KiB  
Article
The Quality Assessment of Timber Structural Joints Using the Coaxial Correlation Method
by Viktors Kurtenoks, Aleksis Kurajevs, Karina Buka-Vaivade, Dmitrijs Serdjuks, Vjaceslavs Lapkovskis, Viktors Mironovs, Andrejs Podkoritovs and Martins Vilnitis
Buildings 2023, 13(8), 1929; https://doi.org/10.3390/buildings13081929 - 28 Jul 2023
Viewed by 593
Abstract
With the growing popularity of timber structures, the requirement for reliable and non-destructive methods to assess the quality and condition of structural joints becomes increasingly essential. A novel coaxial correlations method is investigated to assess the degradation of panel-to-panel moment joints in timber [...] Read more.
With the growing popularity of timber structures, the requirement for reliable and non-destructive methods to assess the quality and condition of structural joints becomes increasingly essential. A novel coaxial correlations method is investigated to assess the degradation of panel-to-panel moment joints in timber structures. The method involves analysing the response data obtained from accelerometers placed on both sides of the joint and comparing the readings to evaluate the joint’s condition. A specific joint solution to simulate the degradation of the moment joint in laboratory conditions is selected based on its simplicity and the ease with which its degradation can be simulated. The joint consists of angle brackets joined with timber screws and bolts to plywood panels. Gradually unscrewing the timber screws reduces the joint’s stiffness to simulate wear and tear over time. The experimental setup includes static loading and finite element modelling (FEM) to determine the rotational stiffness of the investigated joint at each degradation level. A dynamic experiment using vibration loading with sweep signal in the frequency range of 10 Hz to 2000 Hz is conducted to assess the quality of the joint. The conducted research provides valuable insights into the behaviour of timber panel-to-panel connections. The findings highlight the relationship between joint stiffness, vertical displacements, and the proposed dimensionless parameter, volume root mean square value (RMSvol), which offers a more comprehensive assessment of the joint’s condition in three spatial directions. As a result of the research, it has been established that, in the case of linear-type connections, unlike point-type joints, there is a possibility of signal scattering, so it is recommended that power comparisons and evaluations of the response signals from both accelerometers at the initial stage of applying the coaxial correlations method are performed. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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12 pages, 4783 KiB  
Article
Non-Destructive Damage Detection of Structural Joint by Coaxial Correlation Method in 6D Space
by Karina Buka-Vaivade, Viktors Kurtenoks and Dmitrijs Serdjuks
Buildings 2023, 13(5), 1151; https://doi.org/10.3390/buildings13051151 - 26 Apr 2023
Cited by 2 | Viewed by 1000
Abstract
Failure of joints can lead to structural collapse. It is vital to monitor joint stiffness during operation to prevent such failures. This paper proposes a novel method for the quality assessment of structural joints using coaxial correlation in 6D space. Coaxially placed 6D [...] Read more.
Failure of joints can lead to structural collapse. It is vital to monitor joint stiffness during operation to prevent such failures. This paper proposes a novel method for the quality assessment of structural joints using coaxial correlation in 6D space. Coaxially placed 6D sensors on either side of the joint implemented by 3D accelerometers and 3D gyroscopes with wide frequency range, automatic synchronisation between the input signal and receivers and response signal averaging are presented. The root mean square (RMS) value from the obtained signals convolution is proposed as a measure of the similarity between two signals for monitoring joint degradation. The method’s effectiveness was tested on steel beam splice connection, where it was found that the RMS of convolution signals in 6D space showed a direct correlation between the calculated RMS value in X, Y, GX, and GY axes directions and the stiffness grades of the joint. The paper concludes that the nature of the RMS during the degradation of the joint may change in different axes, and wrongly chosen axes may lead to wrong conclusions regarding the state of the investigated joint, especially in the case of complex joints, so that the measurements in 6D provide higher reliability of the result interpretation. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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28 pages, 4122 KiB  
Article
Using RPA for Performance Monitoring of Dynamic SHM Applications
by Edison Atencio, Sayedmilad Komarizadehasl, José Antonio Lozano-Galant and Matías Aguilera
Buildings 2022, 12(8), 1140; https://doi.org/10.3390/buildings12081140 - 01 Aug 2022
Cited by 6 | Viewed by 3211
Abstract
Robotic Process Automation (RPA) is a source of growing applications in a number of industries both as an individual technology and as a complement to other technologies (such as Internet of Things (IoT)). RPA allows the automation of human activities on a computer, [...] Read more.
Robotic Process Automation (RPA) is a source of growing applications in a number of industries both as an individual technology and as a complement to other technologies (such as Internet of Things (IoT)). RPA allows the automation of human activities on a computer, especially when these activities are repetitive and high in volume. RPA saves man-hours and increases the productive capacity of the processes. The application of RPA in civil engineering is still in its early stages, and there has been little work on the subject in the literature. This paper presents RPA technology, for the first time in the literature, as a long-term management, control, and auto fault correction process for a low-cost accelerometer that can be used in SHM applications. However, this process requires a significant number of man-hours to stay operational, given the architecture of its applications. With the application of an RPA implementation workflow formulated based on the Design Science Research Method (DSRM), the management and control of the data acquisition process of a low-cost accelerometer located on a structural column are automated and put into operation in this study. RPA also made it possible to automatically detect and notify users of errors in the process, restart the process, and bring the process back online every time errors occurred. In this way, an automated process was obtained that operated continually and freed up human labour. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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24 pages, 8875 KiB  
Article
Multiple Tests for Dynamic Identification of a Reinforced Concrete Multi-Span Arch Bridge
by Vincenzo Gattulli, Francesco Potenza and Giulio Piccirillo
Buildings 2022, 12(6), 833; https://doi.org/10.3390/buildings12060833 - 15 Jun 2022
Cited by 4 | Viewed by 1576
Abstract
This paper presents the results of an experimental dynamic campaign carried out on a reinforced concrete multi-span arch bridge. Five expeditious ambient vibration tests were conducted separately on five spans (one test in each span) of the bridge using only six piezoelectric uniaxial [...] Read more.
This paper presents the results of an experimental dynamic campaign carried out on a reinforced concrete multi-span arch bridge. Five expeditious ambient vibration tests were conducted separately on five spans (one test in each span) of the bridge using only six piezoelectric uniaxial accelerometers. Modal parameters were identified through the well-known Enhanced Frequency Domain Decomposition (EFDD) procedure developed using Matlab R2021b software. At the same time, a finite element model was accurately implemented through a commercial software (Midas Civil) to evaluate the main modal features. A manual model update was successively pursued varying the elastic modulus of the reinforced concrete to make the identified and numerical modes as close as possible. A complete and suitable instrumentation to perform global experimental dynamic tests is not always available. Recursive/Multiple tests have different advantages: handy, easily executable, and could provide a more robust identification thanks to a statical characterization. The paper aims to highlight the peculiarities of recursive/multiple dynamic tests on multi-span arch bridges. The procedure also provides useful suggestions for designing a permanent and continuous vibration-based monitoring system. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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15 pages, 5676 KiB  
Article
Detecting Damage Evolution of Masonry Structures through Computer-Vision-Based Monitoring Methods
by Marialuigia Sangirardi, Vittorio Altomare, Stefano De Santis and Gianmarco de Felice
Buildings 2022, 12(6), 831; https://doi.org/10.3390/buildings12060831 - 14 Jun 2022
Cited by 18 | Viewed by 2316
Abstract
Detecting the onset of structural damage and its progressive evolution is crucial for the assessment and maintenance of the built environment. This paper describes the application of a computer-vision-based methodology for structural health monitoring to a shake table investigation. Three rubble stone masonry [...] Read more.
Detecting the onset of structural damage and its progressive evolution is crucial for the assessment and maintenance of the built environment. This paper describes the application of a computer-vision-based methodology for structural health monitoring to a shake table investigation. Three rubble stone masonry walls, one unreinforced and two reinforced, were tested under natural earthquake base inputs, progressively scaled up to collapse. White noise signals were also applied for dynamic identification purposes. Throughout the experiments, videos were recorded, under both white noise excitation and environmental vibrations, with the table at rest. The videos were preprocessed with motion magnification algorithms and analyzed through a principal component analysis. The natural frequencies of the walls were detected and their progressive decay was associated with damage accumulation. Results agreed with those obtained from another measurement system available in the laboratory and were consistent with the crack pattern development surveyed during the tests. The proposed approach proved useful to derive information on the progressive deterioration of the structural properties, showing the feasibility of this methodology for real field applications. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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20 pages, 6758 KiB  
Article
Defect Identification of Concrete Piles Based on Numerical Simulation and Convolutional Neural Network
by Chuan-Sheng Wu, Jian-Qiang Zhang, Ling-Ling Qi and De-Bing Zhuo
Buildings 2022, 12(5), 664; https://doi.org/10.3390/buildings12050664 - 17 May 2022
Cited by 6 | Viewed by 3032
Abstract
Defects in pile foundations, such as neck defects, bulge imperfections, weak concretes, cracks, and broken piles, can cause a decrease in the bearing capacity and the structural stability of the foundation. Identification of the type of defect is vital in formulating a reasonable [...] Read more.
Defects in pile foundations, such as neck defects, bulge imperfections, weak concretes, cracks, and broken piles, can cause a decrease in the bearing capacity and the structural stability of the foundation. Identification of the type of defect is vital in formulating a reasonable repair plan for the pile foundation. In this study, the authors proposed a scheme to identify the types of defects in concrete piles based on a convolution neural network and a low-strain pile integrity test (LSPIT). A batch modeling method of defective pile foundations using Python script was also proffered. The different degrees of signals of five types of defective pile foundations were simulated by this method. The original data were decomposed and reconstructed by wavelet packet decomposition (WPT). To prevent the data from losing too much information after WPT, the data of 400 × 1 after decomposition and reconstruction were processed by dimension-raising to obtain the data of 20 × 20 × 1. Then, the multidimensional feature index of 20 × 20 × 2 was generated by index fusion with the original data. Finally, the data were input onto convolutional neural network (CNN) as a training parameter. Following an improvement of the dataset, the recognition accuracy of the type of defect in the pile foundation by the proposed identification scheme reached 94.4%. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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25 pages, 6927 KiB  
Article
Instantaneous Spectral Entropy: An Application for the Online Monitoring of Multi-Storey Frame Structures
by Marco Civera and Cecilia Surace
Buildings 2022, 12(3), 310; https://doi.org/10.3390/buildings12030310 - 05 Mar 2022
Cited by 21 | Viewed by 2228
Abstract
Damage assessment techniques based on entropy measurements have been recently proposed for the structural health monitoring of civil structures and infrastructures. A quasi-real-time approach, based on the use of instantaneous spectral entropy (ISE) over an uninterrupted stream of data, is discussed here. The [...] Read more.
Damage assessment techniques based on entropy measurements have been recently proposed for the structural health monitoring of civil structures and infrastructures. A quasi-real-time approach, based on the use of instantaneous spectral entropy (ISE) over an uninterrupted stream of data, is discussed here. The methodology is proposed for the detection of sudden damage-related structural changes (more specifically, linear stiffness reductions and nonlinear breathing cracks). The method operates by framing the continuous stream of vibration signals and comparing the single frames to a known baseline. The approach is also suitable for nonstationary signals originating from nonlinearly behaving structures. The procedure is validated on an experimental benchmark: a laboratory-scaled model of a three-storey single-span frame metallic structure. Three different definitions of entropy and six candidate time–frequency/time-scale transforms have been tested to find the optimal settings. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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16 pages, 3959 KiB  
Article
Anchor Force Monitoring Using Impedance Technique with Single-Point Mount Lead-Zirconate-Titanate Interface: A Feasibility Study
by Thanh-Cao Le, Duc-Duy Ho and Thanh-Canh Huynh
Buildings 2021, 11(9), 382; https://doi.org/10.3390/buildings11090382 - 27 Aug 2021
Cited by 6 | Viewed by 1868
Abstract
As a key load-bearing element in a prestressed structure, the anchor should be appropriately monitored to secure its as-built prestressing force. In previous studies, the impedance-based prestress force monitoring technique through a mountable lead–Zirconate–Titanate (PZT) interface was developed. However, the previous design of [...] Read more.
As a key load-bearing element in a prestressed structure, the anchor should be appropriately monitored to secure its as-built prestressing force. In previous studies, the impedance-based prestress force monitoring technique through a mountable lead–Zirconate–Titanate (PZT) interface was developed. However, the previous design of the PZT interface uses a two-point mount technique through two bonding layers, causing inconveniences during installation and replacement processes. To address this issue, we propose an alternative PZT interface model for prestress force monitoring based on the impedance method. The proposed model uses a single-point mounting technique that allows it to be more conveniently installed and replaced on a host structure. First, the electromechanical impedance of the proposed PZT interface is theoretically derived. The proof-of-concept of the proposed PZT interface for impedance monitoring is then shown by finite element modelling. Afterwards, a lab-scaled experiment is conducted on an anchoring system to demonstrate the practical application feasibility of the proposed technique. The obtained results show that the proposed technique can produce impedance responses that are highly sensitive to the prestress force. The performance of the proposed model for impedance-based prestress force monitoring is found to be comparable with the previous techniques (the washer-type mount and the two-point mount). Due to its advantage of simple design, the newly designed PZT interface is promising for the future development of the impedance-based anchor force monitoring systems in practice. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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Review

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30 pages, 2292 KiB  
Review
Practical Implementation of Structural Health Monitoring in Multi-Story Buildings
by Arvindan Sivasuriyan, Dhanasingh Sivalinga Vijayan, Wojciech Górski, Łukasz Wodzyński, Magdalena Daria Vaverková and Eugeniusz Koda
Buildings 2021, 11(6), 263; https://doi.org/10.3390/buildings11060263 - 20 Jun 2021
Cited by 57 | Viewed by 14122
Abstract
This study investigated operational and structural health monitoring (SHM) as well as damage evaluations for building structures. The study involved damage detection and the assessment of buildings by placing sensors and by assuming weak areas, and considered situations of assessment and self-monitoring. From [...] Read more.
This study investigated operational and structural health monitoring (SHM) as well as damage evaluations for building structures. The study involved damage detection and the assessment of buildings by placing sensors and by assuming weak areas, and considered situations of assessment and self-monitoring. From this perspective, advanced sensor technology and data acquisition techniques can systematically monitor a building in real time. Furthermore, the structure’s response and behavior were observed and recorded to predict the damage to the building. In this paper, we discuss the real-time monitoring and response of buildings, which includes both static and dynamic analyses along with numerical simulation studies such as finite element analysis (FEA), and recommendations for the future research and development of SHM are made. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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Other

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15 pages, 4192 KiB  
Perspective
A Perspective on AI-Based Image Analysis and Utilization Technologies in Building Engineering: Recent Developments and New Directions
by Ivan Paduano, Andrea Mileto and Egidio Lofrano
Buildings 2023, 13(5), 1198; https://doi.org/10.3390/buildings13051198 - 30 Apr 2023
Cited by 5 | Viewed by 2333
Abstract
Artificial Intelligence (AI) is a trending topic in many research areas. In recent years, even building, civil, and structural engineering have also started to face with several new techniques and technologies belonging to this field, such as smart algorithms, big data analysis, deep [...] Read more.
Artificial Intelligence (AI) is a trending topic in many research areas. In recent years, even building, civil, and structural engineering have also started to face with several new techniques and technologies belonging to this field, such as smart algorithms, big data analysis, deep learning practices, etc. This perspective paper collects the last developments on the use of AI in building engineering, highlighting what the authors consider the most stimulating scientific advancements of recent years, with a specific interest in the acquisition and processing of photographic surveys. Specifically, the authors want to focus both on the applications of artificial intelligence in the field of building engineering, as well as on the evolution of recently widespread technological equipment and tools, emphasizing their mutual integration. Therefore, seven macro-categories have been identified where these issues are addressed: photomodeling; thermal imaging; object recognition; inspections assisted by UAVs; FEM and BIM implementation; structural monitoring; and damage identification. For each category, the main new innovations and the leading research perspectives are highlighted. The article closes with a brief discussion of the primary results and a viewpoint for future lines of research. Full article
(This article belongs to the Special Issue Advanced Methodologies and Technologies in Structural Monitoring)
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