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Civil Structural Health Monitoring: Techniques, Systems and Applications
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Civil Structural Health Monitoring: Techniques, Systems and Applications

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

Deadline for manuscript submissions: 20 October 2025 | Viewed by 5406

Special Issue Editors

Prof. Dr. Fei Kang

E-Mail Website
Guest Editor
School of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China
Interests: dam safety monitoring; support vector machines; Gaussian processes; evolutionary computation; inverse analysis; structural health monitoring
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yonglong Li

E-Mail Website
Guest Editor
Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610000, China
Interests: dam inspection robot; AI for civil engineering; automation; control system

Special Issue Information

Dear Colleagues,

Civil structures and infrastructures, such as bridges, high-rise buildings, towers, dams, tunnels, and so forth, occupy a major position in the economy and play a vital role in facilitating daily life for the world population. However, accidental structural damage can cause significant economic and human casualties. Structures subjected to dead load, live load, natural hazards, and anthropogenic activities are referred to as the censorious elements in the construction systems. Thus, structural health monitoring is necessary for the longevity of the building and the safety of the public. Structural health monitoring is the process of implementing a damage detection and characterization strategy for engineering structures. Structural health monitoring pertains to the life of a structure and diagnoses the ‘‘state” of the constituted materials in different parts of the structure. This Special Issue aims to discuss the latest research advances in the field of civil structural health monitoring (such as the detection of damage and data processing algorithms, modelling and simulation, sensor development and experimentation, materials research, etc.) in the form of reviews and case studies. The future of this field is very bright, and will help to drive futuristic and intelligent infrastructure. 

Prof. Dr. Fei Kang
Prof. Dr. Yonglong Li
Guest Editors

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Keywords

  • structural health monitoring
  • damage identification
  • numerical simulation
  • sensor experiments
  • underwater defect detection
  • machine learning
  • dams
  • case studies

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Published Papers (6 papers)

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Research

14 pages, 14880 KiB  
Article
Dynamic Inversion Method for Concrete Gravity Dam on Soft Rock Foundation
by Guanglin Yin, Chaoning Lin, Taozhen Sheng, Wenbo Xue, Tongchun Li and Siyu Chen
Appl. Sci. 2025, 15(9), 4750; https://doi.org/10.3390/app15094750 - 25 Apr 2025
Viewed by 282
Abstract
This study presents a dynamic inversion method for the concrete gravity dam on a soft rock foundation, aiming to accurately characterize the time-dependent trend of the dam’s mechanical properties. Conventional static inversion methods often overlook temporal variations in material behavior, particularly the long-term [...] Read more.
This study presents a dynamic inversion method for the concrete gravity dam on a soft rock foundation, aiming to accurately characterize the time-dependent trend of the dam’s mechanical properties. Conventional static inversion methods often overlook temporal variations in material behavior, particularly the long-term weakening of soft rock foundations under environmental influences. To address this limitation, an improved particle swarm optimization (PSO) algorithm is developed for dynamic parameter inversion, combining real-time monitoring data with finite element modeling to evaluate the time-varying elastic modulus of the foundation. The results reveal an exponential decay in the foundation’s elastic modulus (from 4.67 GPa to approximately 3.83 GPa), while the dam body maintains a stable modulus of 20.74 GPa. Comparative analyses demonstrate that the dynamic inversion approach, which accounts for time-dependent parameter degradation, significantly improves the displacement prediction accuracy of the dam. The results highlight the critical importance of incorporating temporal mechanical property variations in inversion analyses to ensure reliable structural assessments and enhance long-term dam safety management. Full article
(This article belongs to the Special Issue Civil Structural Health Monitoring: Techniques, Systems and Applications)
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28 pages, 34976 KiB  
Article
Model Updating of Bridges Using Measured Influence Lines
by Doron Hekič, Jan Kalin, Aleš Žnidarič, Peter Češarek and Andrej Anžlin
Appl. Sci. 2025, 15(8), 4514; https://doi.org/10.3390/app15084514 - 19 Apr 2025
Viewed by 228
Abstract
In developing a digital twin of a real structure, finite element model updating (FEMU) is essential for refining the model’s response based on measured data, enabling the detection of structural damage or hidden reserves over time. This case study focused on a 40-year-old [...] Read more.
In developing a digital twin of a real structure, finite element model updating (FEMU) is essential for refining the model’s response based on measured data, enabling the detection of structural damage or hidden reserves over time. This case study focused on a 40-year-old multi-span concrete roadway bridge, equipped with permanent bridge weigh-in-motion (B-WIM) and structural health monitoring (SHM) systems. Bridge responses from two calibration vehicles were used to derive strain influence lines (ILs) from mid-span B-WIM strain transducers mounted on the main girders. The error-domain model falsification (EDMF) methodology was applied to perform strain IL-based FEMU and the more conventional frequency-based, MAC-based, and combined frequency and MAC-based FEMU. Boundary conditions and three Young’s modulus adjustment factors, representing different groups of structural elements, were updated. The strain IL-based updated FE model, with averages of 35% and 50% stiffness increases for the two main girders, showed strong agreement with independently measured mid-span vertical displacements. Maximum values deviated not more than 5%. In contrast, the frequency and MAC-based updated FE model underestimated displacements by 25–30%. These findings highlight the potential of using B-WIM for FEMU and SHM on such types of bridges, particularly when the response under traffic load is of interest. Full article
(This article belongs to the Special Issue Civil Structural Health Monitoring: Techniques, Systems and Applications)
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21 pages, 7374 KiB  
Article
Inverse Analysis of Thermal Parameters of Arch Dam Concrete Based on Walrus Optimization Algorithm
by Youle Wang, Zhengjian Miao, Rui Song, Junchi Zhou, Yuheng Pan and Feng Wang
Appl. Sci. 2025, 15(4), 2155; https://doi.org/10.3390/app15042155 - 18 Feb 2025
Viewed by 384
Abstract
In the simulation of concrete thermal stress fields, thermal parameters are crucial for calculating the concrete temperature field. In actual construction, due to the adjustment of the concrete mixing ratio and the changing external environment (temperature fluctuations, cooling conditions, solar radiation, thermal insulation [...] Read more.
In the simulation of concrete thermal stress fields, thermal parameters are crucial for calculating the concrete temperature field. In actual construction, due to the adjustment of the concrete mixing ratio and the changing external environment (temperature fluctuations, cooling conditions, solar radiation, thermal insulation measures, etc.), there are significant differences between the thermal parameters obtained in tests and the actual working conditions, which affect the simulation accuracy. Therefore, the inverse analysis of concrete thermal parameters under real working conditions can be carried out based on the measured temperature data. A method for inverse analysis of thermal parameters of arch dams using the walrus optimization algorithm (WaOA) is proposed. To verify the accuracy of the inversion parameters, twelve classical test functions are used to compare the three algorithms to evaluate their fitness. The efficiency difference is analyzed by nonparametric methods such as Fredman and Wilcoxon rank sum test. The results consistently indicate that the walrus optimization algorithm performs better. Furthermore, the WaOA is utilized for the parameter inversion of an arch dam in the downstream area of the Jinsha River. We bring the inversion results into different dam sections to calculate the temperature field during construction, which effectively verifies the efficient solution ability of the WaOA for the inverse analysis of concrete thermal parameters under complex engineering backgrounds. Full article
(This article belongs to the Special Issue Civil Structural Health Monitoring: Techniques, Systems and Applications)
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16 pages, 3872 KiB  
Article
Influence of Boundary Conditions on the Three-Dimensional Temperature Field of a Box Girder in the Natural Environment: A Case Study
by Bin Yan, Hexin Fu, Haiting Su and Benguang Hou
Appl. Sci. 2025, 15(3), 1378; https://doi.org/10.3390/app15031378 - 29 Jan 2025
Viewed by 589
Abstract
The inhomogeneous distribution of temperature in bridges causes stresses and strains inside the structure, thus affecting the safety and durability of bridges. Therefore, the study of temperature action in bridge structures is crucial; boundary conditions of the temperature field are critical to study [...] Read more.
The inhomogeneous distribution of temperature in bridges causes stresses and strains inside the structure, thus affecting the safety and durability of bridges. Therefore, the study of temperature action in bridge structures is crucial; boundary conditions of the temperature field are critical to study them. In this study, the calculation method of the boundary conditions for the three-dimensional temperature field of box girders in the natural environment is investigated by taking box girders as the object, which integrates the solar radiation, environmental radiation, structural shading effect, and convective heat transfer between the inner and outer surfaces of box girders. The effects of the atmospheric transparency coefficient and concrete short-wave absorptivity on the temperature field distribution of box girders were also investigated. It is shown that the calculation results obtained by the method in this study are in good agreement with the measured results, and the method can effectively simulate the three-dimensional temperature field of the box girder. The atmospheric transparency coefficient and the short-wave absorptivity of concrete have a significant effect on the temperature field distribution of box girders, and materials with lower short-wave absorptivity can be used in the design of box girders to reduce the structural temperature. Full article
(This article belongs to the Special Issue Civil Structural Health Monitoring: Techniques, Systems and Applications)
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31 pages, 50761 KiB  
Article
Intelligent Structural Health Monitoring and Noncontact Measurement Method of Small Reservoir Dams Using UAV Photogrammetry and Anomaly Detection
by Sizeng Zhao, Fei Kang, Lina He, Junjie Li, Yiqing Si and Yiping Xu
Appl. Sci. 2024, 14(20), 9156; https://doi.org/10.3390/app14209156 - 10 Oct 2024
Cited by 3 | Viewed by 1329
Abstract
This study proposes a UAV-based remote measurement method for accurately locating pedestrians and other small targets within small reservoir dams. To address the imprecise coordinate information in reservoir areas after prolonged operations, a transformation method for converting UAV coordinates into the local coordinate [...] Read more.
This study proposes a UAV-based remote measurement method for accurately locating pedestrians and other small targets within small reservoir dams. To address the imprecise coordinate information in reservoir areas after prolonged operations, a transformation method for converting UAV coordinates into the local coordinate system without relying on preset parameters is introduced, accomplished by integrating the Structure from Motion (SfM) algorithm to calculate the transformation parameters. An improved YOLOv8 network is introduced for the high-precision detection of small pedestrian targets, complemented by a laser rangefinder to facilitate accurate 3D locating of targets from varying postures and positions. Furthermore, the integration of a thermal infrared camera facilitates the detection and localization of potential seepage. The experimental validation and application across two real small reservoir dams confirm the accuracy and applicability of the proposed approach, demonstrating the efficiency of the proposed routine UAV surveillance strategy and proving its potential to establish electronic fences and enhance maintenance operations. Full article
(This article belongs to the Special Issue Civil Structural Health Monitoring: Techniques, Systems and Applications)
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16 pages, 6273 KiB  
Article
Load Effect Analysis Method of Cable-Stayed Bridge for Long-Span Track Based on Adaptive Filtering Method
by Peng Ding, Xiaogang Li, Sheng Chen, Xiangsheng Huang, Xiaohu Chen and Yong Qi
Appl. Sci. 2024, 14(16), 7057; https://doi.org/10.3390/app14167057 - 12 Aug 2024
Cited by 1 | Viewed by 1312
Abstract
Aiming at the problems of large capacity, narrow transverse width, large excitation, high safety level, and difficulty in accurately grasping the working state of the cable-stayed bridge for the long-span track, this research obtains the structural response data in real time by establishing [...] Read more.
Aiming at the problems of large capacity, narrow transverse width, large excitation, high safety level, and difficulty in accurately grasping the working state of the cable-stayed bridge for the long-span track, this research obtains the structural response data in real time by establishing a health monitoring system. The adaptive filtering method was employed to separate the train load response and the temperature load response. Then, a train load effect analysis method based on the influence line and a temperature load effect analysis method based on the correlation were proposed to assess the operational status of the bridge in real time and objectively. The Chongqing Nanjimen Railway Track Bridge (hereinafter Chongqing Nanjimen track bridge) project was utilized as a case study to demonstrate the application of these methods. The results show that the adaptive filtering method can effectively separate the response of train and temperature loads. The normalized cross-correlation (NCC) results of the measured train load response and the influence line’s finite element calculation show a high degree of fit between the measured values and the theory, proving that no significant anomalies are found in the bridge. There is a strong correlation between the ambient temperature difference and the Pearson correlation coefficient of structural response, which indicates that the Chongqing Nanjimen track bridge is currently in normal working condition. Full article
(This article belongs to the Special Issue Civil Structural Health Monitoring: Techniques, Systems and Applications)
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