In civil engineering, health monitoring of structure have been treated as an important subject. Health monitoring by using experimental measurements such as strain, acceleration, velocity, displacement, rotation and other parameters has been used for detecting changes, which may indicate damage or degradation. In recent, the applications of health monitoring of large structure have been facilitated by the developments in measurement, communications and computational technology gradually. Especially, large civil structures as bridges are damaged by fatigue loads or unexpected load such as earthquakes and finally reach to failure. Thus, a structural health monitoring and damage detection methods have been developed and attracted a great deal of public attention in recent decades. Actually many research efforts have been conducted to develop a health monitoring and damage detection techniques of existing civil structures. However, these methods are needed to improve to apply to a real civil structure. The purpose of this study is to develop a practical instrument to identify dynamic parameters of real civil structural systems.
128Structural Health Monitoring (SHM) of Civil Structures
As newer and more reliable ways of construction were developed, civilization began to spread out further and retain functional infrastructure for longer periods of time.[...]
Read more17Health Monitoring of Civil Infrastructure and Materials
Despite the generally long life span of concrete structures, they cannot be considered maintenance-free. Several incidents of catastrophic failures remind the engineering world that monitoring of structures is imperative nowadays both for prevention of loss of life and property and also for effective infrastructure management based on a usually finite budget. Due to the variety of structural sizes, shapes, and uses, as well the possible vulnerabilities of the different types of structures, different tools must be used, many times complementary, in order to lead to reliable assessment results. Indeed, the reliability of in situ implementation is a key issue for any health monitoring technique along with other characteristics such as testing speed and cost-effectiveness. Several nondestructive testing (NDT) techniques have already been established, showing their suitability in certain aspects of material and structural characterization and behavior monitoring. As an example, the use of ultrasonic pulse velocity can be mentioned, the correlation of which with the quality of concrete is well documented. Other techniques based on elastic waves such as impact and impulse response, as well as the radar method, have proven their suitability in distinguishing delaminations and inhomogeneities. The assessment based on the above-mentioned methods as well as a number of others, like acoustic emission, radiography, vibration modal analysis, and slightly destructive surface strength methods in conjunction with visual inspection, provides a valuable platform for decision making concerning the maintenance, based on more robust engineering criteria than solely the experience of the engineer. However, it is a common impression that most NDT techniques have not at all reached their full potential especially with regard to in situ implementation. Therefore, the current special issue intends to examine all possible tools for economic and timely infrastructure condition assessment, with emphasis on reliability and connection of the monitoring results with the proper maintenance action that should be taken. The challenges are even higher since new and innovative materials are being increasingly used. These materials include high performance concrete, textile reinforced concrete, and nanomodified and recycled materials, which offer better capabilities for sustainable structures; however their assessment through the same techniques used for conventional concrete should not be taken for granted. In this special issue, the latest advances in different topics of civil structural health monitoring (SHM) are highlighted. More specifically, recent findings in elastic wave methods (acoustic emission, impact-echo, and ultrasonics) are reported. Vibration methodologies which are the most suitable for global bridge SHM are discussed, while the use of radar is reviewed and applied. Advancements in automated robotic inspection and online monitoring of bridge components are also discussed. The issue includes studies on corrosion detection, reinforcing and self-sensing elements for SHM. Algorithms incorporating pattern recognition clustering for the characterization of the location and degree of damage could not but be a strong part of the issue, while monitoring of self-healing and textile-reinforced materials is also discussed. The dual importance of monitoring of old structures is stressed out: their structural safety as well as their cultural heritage significance. The methodologies are successfully tested in several case studies as reported herein. We believe that the present special issue reflects on the recent advances in SHM and NDT for civil structures and materials complemented with insightful findings of various assessment techniques. We wish to thank all the authors for submitting their work in the issue and their patience during the review process. Dimitrios G. Aggelis Ninel Alver Hwa Kian Chai
Read more669Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to recent technological advancements in sensors, as well as high-speed internet and cloud-based computation. Since the introduction of deep learning (DL) in civil engineering, particularly in SHM, this emerging and promising tool has attracted significant attention among researchers. The main goal of this paper is to review the latest publications in SHM using emerging DL-based methods and provide readers with an overall understanding of various SHM applications. After a brief introduction, an overview of various DL methods (e.g., deep neural networks, transfer learning, etc.) is presented. The procedure and application of vibration-based, vision-based monitoring, along with some of the recent technologies used for SHM, such as sensors, unmanned aerial vehicles (UAVs), etc. are discussed. The review concludes with prospects and potential limitations of DL-based methods in SHM applications.
Read more7Optimization of Sensors for Structure Damage Detection Using Deep Learning Approach
Structural health monitoring (SHM) based on long-term safety and efficacy has attracted much attention. The success of SHM methods depends on the information content of the measurements; in addition, there are challenges in processing SHM in terms of the optimal number and location of sensors. In this study, we provide a convenient method for structural damage detection using vibration data from plane steel frames. We apply 1-D convolutional neural networks (1D-CNNs) to present an influential sensor selection analysis to maintain performance and optimize the number and location of sensors. Finding the damage location based on the optimal number and location of sensors will significantly reduce the detection time and the number of installed sensors. The proposed structural damage detection method uses stress analysis to find positions with large displacements, then divides the detection zones, selects highly discriminate sensors, analyzes the influence of sensor combinations within each zone to achieve optimization of sensor number as well as position selection, and establishes CNN models of the overall structure for damage detection of the joints. The proposed method was practically validated on benchmark data from the Qatar University Grandstand Simulator (QUGS). The experimental results show that the sensor demand rate is only 16.67% compared to the previous optimal number and location of sensors with no restrictions on the mounting position. Moreover, only four CNN models are required to predict damage/undamaged for the entire structure (30 connections). The accuracy of damage detection is improved to 96.62% using sensor combinations with influence.
Read more2Chapter 10 - Structural health monitoring and nondestructive evaluation applications of the stress, vibration, and wave analysis in aerospace composites
Chapter 10 - Structural health monitoring and nondestructive evaluation applications of the stress, vibration, and wave analysis in aerospace composites
Read more178SMC structural health monitoring benchmark problem using monitored data from an actual cable-stayed bridge
A structural health monitoring (SHM) system provides an efficient way to diagnose the condition of critical and large-scale structures such as long-span bridges. With the development of SHM techniques, numerous condition assessment and damage diagnosis methods have been developed to monitor the evolution of deterioration and long-term structural performance of such structures, as well as to conduct rapid damage and post-disaster assessments. However, the condition assessment and the damage detection methods described in the literature are usually validated by numerical simulation and/or laboratory testing of small-scale structures with assumed deterioration models and artificial damage, which makes the comparison of different methods invalid and unconvincing to a certain extent. This paper presents a full-scale bridge benchmark problem organized by the Center of Structural Monitoring and Control at the Harbin Institute of Technology. The benchmark bridge structure, the SHM system, the finite element model of the bridge, and the monitored data are presented in detail. Focusing on two critical and vulnerable components of cable-stayed bridges, two benchmark problems are proposed on the basis of the field monitoring data from the full-scale bridge, that is, condition assessment of stay cables (Benchmark Problem 1) and damage detection of bridge girders (Benchmark Problem 2). For Benchmark Problem 1, the monitored cable stresses and the fatigue properties of the deteriorated steel wires and cables are presented. The fatigue life prediction model and the residual fatigue life assessment of the cables are the foci of this problem. For Benchmark Problem 2, several damage patterns were observed for the cable-stayed bridge. The acceleration time histories, together with the environmental conditions during the damage development process of the bridge, are provided. Researchers are encouraged to detect and to localize the damage and the damage development process. All the datasets and detailed descriptions, including the cable stresses, the acceleration datasets, and the finite element model, are available on the Structural Monitoring and Control website (http://smc.hit.edu.cn). Copyright © 2013 John Wiley & Sons, Ltd.
Read more5Structural Health Monitoring Using Carbon Nanotube Yarns: Sensing Concept and Applications in Composites
first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing: Column Width: Background: Open AccessAbstract Structural Health Monitoring Using Carbon Nanotube Yarns: Sensing Concept and Applications in Composites † by Jandro L. Abot Department of Mechanical Engineering, The Catholic University of America, Washington, DC 20064, USA † Presented at the 5th International Symposium on Sensor Science (I3S 2017), Barcelona, Spain, 27–29 September 2017. Proceedings 2017, 1(8), 852; https://doi.org/10.3390/proceedings1080852 Published: 4 December 2017 (This article belongs to the Proceedings of Proceedings of the 5th International Symposium on Sensor Science (I3S 2017)) Download Download PDF Download PDF with Cover Download XML Versions Notes Non-destructive evaluation and structural health monitoring techniques can provide frequent or immediate feedback of the condition of a structure including potential damage. However, these techniques cannot detect initiating damage in composite materials with high compaction or multifaceted construction. More critically, they are unable to achieve damage detection without altering the microstructure of the composite material. An alternative method of strain monitoring and damage detection that may offer the advantages of structural health monitoring without their drawbacks consists of using piezoresistive-based carbon nanotube (CNT) yarns integrated in polymers and composite materials. The concept is that the CNT yarns form a continuous sensor circuit and their inherent piezoresistive sensitivity detects strain within the host material through resistance measurements without adding much weight or altering the integrity of the host material. This presentation includes a summary of the piezoresistive response of CNT yarns and the concept and latest experimental results on damage detection in laminated polymeric composite materials and distributed and localized strain measurement. Experimental results also show the ability of a combination of different yarn sensors to detect the exact location and extent of delamination in real time. CNT yarn sensors may provide an adaptive, practical, and sensitive structural health monitoring technique. © 2017 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Share and Cite MDPI and ACS Style Abot, J.L. Structural Health Monitoring Using Carbon Nanotube Yarns: Sensing Concept and Applications in Composites. Proceedings 2017, 1, 852. https://doi.org/10.3390/proceedings1080852 AMA Style Abot JL. Structural Health Monitoring Using Carbon Nanotube Yarns: Sensing Concept and Applications in Composites. Proceedings. 2017; 1(8):852. https://doi.org/10.3390/proceedings1080852 Chicago/Turabian Style Abot, Jandro L. 2017. "Structural Health Monitoring Using Carbon Nanotube Yarns: Sensing Concept and Applications in Composites" Proceedings 1, no. 8: 852. https://doi.org/10.3390/proceedings1080852 Find Other Styles Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here. Article Metrics No No Article Access Statistics Multiple requests from the same IP address are counted as one view.
Read more54Health monitoring of structures - Multiple delamination dynamics in composite beams
In this paper, we discuss the dynamics of beams with multiple delaminations. The objective of the study is to use the dynamic response of the delaminated beams in health monitoring of composite structures. As a first step, we present experimental results on the vibrations of a cantilever beam with multiple delaminations. These experiments are conducted by exciting the beam with piezoelectric actuators. The response is detected by using a high-speed video camera to study the existence of delamination opening modes in a beam with multiple delaminations. Then, an analysis of natural frequencies and mode shapes, for a delaminated beam, is presented by using analytical techniques. The measured dynamic responses of the beam with multiple delaminations are also presented. The experimentally detected nonlinear response is discussed. Introduction Delaminations or interlayer cracks and impact damages are typical defects observed in composite structures. The presence of these defects changes the dynamic characteristics of the structure . Some of the specific changes in the observed dynamic characteristics include changes in natural frequencies, changes in the mode shapes and changes in damping ratios. These changes can be used to identify the existence, location and magnitude of a delamination or an impact damage, before they can grow to their critical sizes. Studies, to date, are concerned with the dynamics of beams and plates with a single delamination. In this paper, we specifically discuss the structural dynamics of a beam with multiple delaminations. This information can be used to develop health-monitoring techniques for composite beams with multiple delaminations. In an earlier paper, Luo and Hanagud studied the effects of defects, like saw-cuts, impact damage and delamination, on the structural dynamic characteristics of composite beams. They have shown that perturbations in natural frequencies and modes of a beam, due to defects, can be used for health monitoring of structures. In particular, it has been shown that an integral equation that considers perturbations in curvature modes and natural frequencies can be very effectively used to detect local defects. To distinguish delaminations from other types of monitored (identified) defects Luo and Hanagud have discussed nonlinear effects like superharmonic response in the dynamic response of a harmonically excited delaminated beam. They considered only a single delamination. In this paper we study beams with multiple delaminations. More specifically, we discuss dynamic response and the changes in natural frequencies, mode shapes due to multiple delaminations in a composite beam. One of the earliest models for vibration analysis of composite beams with delaminations was proposed by Ramkumar et al. This model simply used four Timoshenko beams connected at the delamination edges to model a composite beam with one throughwidth delamination. The predicted frequencies, based on this model, were consistently lower than the results of experimental measurements. Wang et al. improved the analytical solution by including coupling between flexural and axial vibrations of the delaminated sublaminates. Using an isotropic beam with splits and the classical beam model, they found that the calculated natural frequencies were closer to experimental results. With similar considerations, Nagesh Gummadi and Hanagud formulated a finite element solution for arbitrary composite beams. In the finite element models, they considered a classical composite beam model as well as the beam model with high order shear deformations. Mujumdar and Suryanarayan have proposed a model which imposed a constraint between the delaminated sublaminates to force them to have the same flexural displacement. This model was unable to * Ph.D. Student, School of Aerospace Engineering † Professor, School of Aerospace Engineering, AIAA Member Copyright © 1999 The American Institute of Aeronautics and Astronautics Inc. All rights reserved
Read more7Decentralized bridge health monitoring using wireless smart sensors
Wireless Smart Sensor Networks (WSSN) facilitates a new paradigm to structural health monitoring (SHM) for civil infrastructure. Conventionally, SHM systems employing wired sensors and central data acquisition have been used to characterize the state of a structure; however, wide-spread implementation has been limited due to difficulties in cabling, high equipment cost, and long setup time. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. Wireless smart sensors have shown their tremendous potential for SHM in recent full-scale bridge monitoring examples. However, structural damage identification in WSSNs, a primary objective of SHM, has yet to reach its full potential. This paper presents an implementation of the stochastic dynamic damage locating vector (SDDLV) method on the Imote2 sensor platform and experimental validation in a laboratory environment. The WSSN application is developed based on the Illinois SHM Project (ISHMP) Services Toolsuite (http://shm.cs.uiuc.edu), combining decentralized data aggregation, system identification, receptance-based damage detection, and global damage assessment. The laboratory experiment uses a three-dimensional truss structure with a network of Imote2 sensors for decentralized damage identification. Future efforts to deploy a long-term structural health monitoring system for a fullscale steel truss bridge are also described.
Read moreStructural Health Monitoring of existing structures and infrastructures combining on-site and satellite data
<p>In the last years, existing structures and transport infrastructures, especially those made using reinforced concrete, have experienced significant safety criticalities implying also a relevant social and economic impacts. Structural Health Monitoring techniques represent a reliable response to the problem available to scientists and engineers. A multidisciplinary approach combing knowledge from several research fields and using different kind of technologies would be preferable for this type of application. Most of developed methods for structural damage detection on civil structures and infrastructures is generally based on the evaluation of displacements, eigenfrequencies, damping factors, mode shapes, etc., and their variation over time, by means of on-site installed sensors. In recent years, thanks to the rapid evolution of interferometric SAR processing techniques, a large amount of “satellite measurements” are available for both geophysical phenomena and building monitoring in terms of displacement rate over time. This paper presents an overview on the 2019-2021 WP6 Reluis Project aiming to contribute to the discussion about the opportunity and the modalities to merge information retrieved both by on-site and remote sensing measurements and to define a shared strategy to detect damage on existing structures and infrastructures in operational conditions.</p>
Read moreSHM/NDE Research at the Laboratory of Active Materials and Smart Structures
This paper reviews recent structural health monitoring (SHM) and nondestructive evaluation (NDE) research at the Laboratory for Active Materials and Smart Structures (LAMSS) of the University of South Carolina, USA. A common theme throughout our research efforts is the judicious combination of theoretical exploration, numerical simulation, and experimental measurements. Both passive and active SHM methods have been pursued.The active SHM research has focused on detecting various types of composite damage using guided-wave interrogation and sensing. The composite damage considered covered both seeded delaminations and barely visible impact damage (BVID).The passive SHM research was focused on recording acoustic emission (AE) wave signals created during fatigue loading of aerospace-grade sheet-metal coupons. The AE signals were analyzed for finding specific signatures associated with fatigue crack growth. It was found that not all AE signals were associated with fatigue crack growth, some resulting from the interaction of the faying surfaces.The NDE research was focused on developing novel methods for damage detection with particular focus on composite materials. Remarkable results were obtained in using angle beam transducers (ABT) to selectively excite either quasi-S0 or quasi-SH0 guided waves in composite materials. Eddy current methods were used to detect composites flaws and damage.KeywordsStructural health monitoring (SHM)Nondestructive evaluations (NDE)Acoustic emission (AE)Fatigue crack growthHigh cycle fatigue (HCF) experimentAE signal mode separationPredictive modeling
Read more3Design of dynamic building Information system based on structural health monitoring information
In order to avoid the safety problems of the public building structure in the dense passenger flow environment, the structural health monitoring system is combined with the Building Information Modeling (BIM) method. This paper proposed a dynamic building information management system based on Structural Health Monitoring (SHM) information to ensure the security of its passenger flow information for a crowded exhibition hall. The continuous development of BIM (building information modeling) technology has greatly promoted the development of the construction industry. We can achieve real-time updating and visualization of sensor monitoring data and effectively manage different types of monitoring information as well as improve the controllability and safety of building structure monitoring by introducing BIM technology into structural health monitoring. A static building information model (BIM) was established to generate dynamic passenger flow information through video data learning, and provide a basis for structural health monitoring system for structural safety analysis and emergency response functions under dense passenger flow conditions. A dynamic building information management system suitable for structural health monitoring was built to display the dynamic network of traffic capacity in real time, so that the building information model is dynamic and predictable. The establishment for the combination mechanism of BIM and SHM system improved the data information circulation of BIM system. It could carry out dynamic health monitoring management and early warning control of building structures, realize information sharing in the process of health monitoring, and effectively improve the safety and operational efficiency of public building structures.
Read moreThe construction of a civil engineering structural health monitoring platform based on intelligent algorithms
In order to solve the problem of abnormal structural health monitoring data of large-span bridges, the construction of civil engineering structural health monitoring platform based on intelligent algorithm is proposed. This paper utilizes the Internet of Things RFID technology to deploy health monitoring sensor nodes and process the bridge structural health monitoring data, so as to realize the large-span bridge structural health monitoring. The experimental results show that the structural health monitoring method designed in this paper for large-span bridges is effective, and the accuracy rate between the measured data values and the real values is 90%, which is highly reliable and has certain application value. Conclusion: The designed structural health monitoring method for large-span bridges has a high degree of agreement between the main girder vertical deformation variables and the actual main girder vertical deformation variables at different monitoring points, which proves that the adopted structural health monitoring method for large-span bridges has a good accuracy and has certain application value.
Read more82Structural damage detection and localization using NETSHM
Structural health monitoring (SHM) is an important application area for wireless sensor networks. SHM techniques attempt to autonomously detect and localize damage in large civil structures. Structural engineers often implement and test SHM algorithms in a higher level language such as C/Matlab. In this paper, we describe the design and evaluation of NETSHM, a sensor network system that allows structural engineers to program SHM applications in Mat-lab or C at a high level of abstraction. In particular, structural engineers do not have to understand the intricacies of wireless networking, or the details of sensor data acquisition. We have implemented a damage detection technique and a damage localization technique on a complete NETSHM prototype. Our experiments on small and medium-scale structures show that NETSHM is able to detect and localized damage perfectly with very few false-positives and no false negatives, and that it is robust even in realistic wireless environments.
Read more150Experimental Damage Identification of Carbon/Epoxy Composite Beams Using Curvature Mode Shapes
Many composite materials and structures are susceptible to defects, which can significantly reduce the strength of structures and may grow to failure. To avoid the catastrophic failure of structures, development of a reliable method of structural health monitoring is one of the most important keys in maintaining the integrity and safety of structures. Dynamic response-based damage detection offers a simple procedure as an alternative to the conventional nondestructive evaluation techniques. However, this technique depends on the quality of measured data for its identification accuracy. In this article, experimental aspects of dynamic response-based damage detection technique on carbon/ epoxy composites are addressed. Smart piezoelectric materials are used as sensors or actuators to acquire the curvature modes of structures. These materials are surface-bonded to the beams. An impulse hammer is used as an actuating source as well. Four types of damage detection algorithms are evaluated for several possible damage configurations with two different excitation sources. The quality of damage identification with the four different detection algorithms is discussed. These experimental damage identification techniques using curvature modes and piezoelectric materials can be effectively used in damage detection and health monitoring of composite structures.
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