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Sensors and Sensor Networks for Structural Health Monitoring
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Sensors and Sensor Networks for Structural Health Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 December 2017) | Viewed by 150055

Special Issue Editors

Dr. Branko Glisic

E-Mail Website
Guest Editor
Dpt. of Civil and Environmental Eng., Princeton University, Princeton, NJ 08544, USA
Interests: advanced sensing technologies, universal SHM methods, data analysis and management, and prognostics and the decision-making theory; smart kinetic, deployable and adaptable structures; holistic analysis of heritage structures, and engineering arts
Special Issues, Collections and Topics in MDPI journals
Dr. Daniele Zonta

E-Mail Website
Co-Guest Editor
1. Department of Civil, Environmental and Mechanical Engineering, University of Trento, 38123 Trento, Italy
2. Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow G11XJ, UK
Interests: smart structures; structural health monitoring; structural reliability; Bayesian decision-making; infrastructure management; fiber optic sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural health monitoring (SHM) uses sensors to provide reliable, accurate, in-time and actionable information on the health condition and performance of structures. SHM allows the optimization of design and maintenance of structures, improves their safety and resilience, while reducing operational costs. Therefore, SHM is more and more accepted and used in real-life settings. SHM involves sensing and data analysis, and thus, its effectiveness depends on the technological advances in these fields.

The aim of this Special Issue is to illustrate the current state-of-the-art in sensing techniques as applied to civil SHM. We invite papers covering any advance in sensors and sensor network for civil structures, including new sensors and sensing technologies; self-sensing materials; innovative sensor networks; novel data analysis algorithms for sensor networks; innovative application of existing technologies; any other ground-breaking technological solution showing the possibilities of civil SHM.

Prof. Dr. Branko Glisic
Prof. Dr. Daniele Zonta
Guest Editors

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Keywords

  • Civil structural health monitoring (SHM)
  • New sensors and sensing technologies
  • Self-sensing materials
  • Innovative sensors networks
  • Novel data analysis algorithms
  • Innovative application of existing technologies
  • Other ground-breaking technological solutions

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Published Papers (21 papers)

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Research

21 pages, 4849 KiB  
Article
Identifying Time Periods of Minimal Thermal Gradient for Temperature-Driven Structural Health Monitoring
by John Reilly and Branko Glisic
Sensors 2018, 18(3), 734; https://doi.org/10.3390/s18030734 - 1 Mar 2018
Cited by 22 | Viewed by 4916
Abstract
Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable [...] Read more.
Temperature changes play a large role in the day to day structural behavior of structures, but a smaller direct role in most contemporary Structural Health Monitoring (SHM) analyses. Temperature-Driven SHM will consider temperature as the principal driving force in SHM, relating a measurable input temperature to measurable output generalized strain (strain, curvature, etc.) and generalized displacement (deflection, rotation, etc.) to create three-dimensional signatures descriptive of the structural behavior. Identifying time periods of minimal thermal gradient provides the foundation for the formulation of the temperature–deformation–displacement model. Thermal gradients in a structure can cause curvature in multiple directions, as well as non-linear strain and stress distributions within the cross-sections, which significantly complicates data analysis and interpretation, distorts the signatures, and may lead to unreliable conclusions regarding structural behavior and condition. These adverse effects can be minimized if the signatures are evaluated at times when thermal gradients in the structure are minimal. This paper proposes two classes of methods based on the following two metrics: (i) the range of raw temperatures on the structure, and (ii) the distribution of the local thermal gradients, for identifying time periods of minimal thermal gradient on a structure with the ability to vary the tolerance of acceptable thermal gradients. The methods are tested and validated with data collected from the Streicker Bridge on campus at Princeton University. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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14 pages, 3895 KiB  
Article
Statistical Analysis of Stress Signals from Bridge Monitoring by FBG System
by Xiao-Wei Ye, You-Hua Su and Pei-Sen Xi
Sensors 2018, 18(2), 491; https://doi.org/10.3390/s18020491 - 7 Feb 2018
Cited by 44 | Viewed by 6799
Abstract
In this paper, a fiber Bragg grating (FBG)-based stress monitoring system instrumented on an orthotropic steel deck arch bridge is demonstrated. The FBG sensors are installed at two types of critical fatigue-prone welded joints to measure the strain and temperature signals. A total [...] Read more.
In this paper, a fiber Bragg grating (FBG)-based stress monitoring system instrumented on an orthotropic steel deck arch bridge is demonstrated. The FBG sensors are installed at two types of critical fatigue-prone welded joints to measure the strain and temperature signals. A total of 64 FBG sensors are deployed around the rib-to-deck and rib-to-diagram areas at the mid-span and quarter-span of the investigated orthotropic steel bridge. The local stress behaviors caused by the highway loading and temperature effect during the construction and operation periods are presented with the aid of a wavelet multi-resolution analysis approach. In addition, the multi-modal characteristic of the rainflow counted stress spectrum is modeled by the method of finite mixture distribution together with a genetic algorithm (GA)-based parameter estimation approach. The optimal probability distribution of the stress spectrum is determined by use of Bayesian information criterion (BIC). Furthermore, the hot spot stress of the welded joint is calculated by an extrapolation method recommended in the specification of International Institute of Welding (IIW). The stochastic characteristic of stress concentration factor (SCF) of the concerned welded joint is addressed. The proposed FBG-based stress monitoring system and probabilistic stress evaluation methods can provide an effective tool for structural monitoring and condition assessment of orthotropic steel bridges. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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15 pages, 4196 KiB  
Article
Calibration of Elasto-Magnetic Sensors on In-Service Cable-Stayed Bridges for Stress Monitoring
by Carlo Cappello, Daniele Zonta, Hassan Ait Laasri, Branko Glisic and Ming Wang
Sensors 2018, 18(2), 466; https://doi.org/10.3390/s18020466 - 5 Feb 2018
Cited by 48 | Viewed by 8782
Abstract
The recent developments in measurement technology have led to the installation of efficient monitoring systems on many bridges and other structures all over the world. Nowadays, more and more structures have been built and instrumented with sensors. However, calibration and installation of sensors [...] Read more.
The recent developments in measurement technology have led to the installation of efficient monitoring systems on many bridges and other structures all over the world. Nowadays, more and more structures have been built and instrumented with sensors. However, calibration and installation of sensors remain challenging tasks. In this paper, we use a case study, Adige Bridge, in order to present a low-cost method for the calibration and installation of elasto-magnetic sensors on cable-stayed bridges. Elasto-magnetic sensors enable monitoring of cable stress. The sensor installation took place two years after the bridge construction. The calibration was conducted in two phases: one in the laboratory and the other one on site. In the laboratory, a sensor was built around a segment of cable that was identical to those of the cable-stayed bridge. Then, the sample was subjected to a defined tension force. The sensor response was compared with the applied load. Experimental results showed that the relationship between load and magnetic permeability does not depend on the sensor fabrication process except for an offset. The determination of this offset required in situ calibration after installation. In order to perform the in situ calibration without removing the cables from the bridge, vibration tests were carried out for the estimation of the cables’ tensions. At the end of the paper, we show and discuss one year of data from the elasto-magnetic sensors. Calibration results demonstrate the simplicity of the installation of these sensors on existing bridges and new structures. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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16 pages, 5325 KiB  
Article
Development of a High-Sensitivity Wireless Accelerometer for Structural Health Monitoring
by Li Zhu, Yuguang Fu, Raymond Chow, Billie F. Spencer, Jong Woong Park and Kirill Mechitov
Sensors 2018, 18(1), 262; https://doi.org/10.3390/s18010262 - 17 Jan 2018
Cited by 88 | Viewed by 12831
Abstract
Structural health monitoring (SHM) is playing an increasingly important role in ensuring the safety of structures. A shift of SHM research away from traditional wired methods toward the use of wireless smart sensors (WSS) has been motivated by the attractive features of wireless [...] Read more.
Structural health monitoring (SHM) is playing an increasingly important role in ensuring the safety of structures. A shift of SHM research away from traditional wired methods toward the use of wireless smart sensors (WSS) has been motivated by the attractive features of wireless smart sensor networks (WSSN). The progress achieved in Micro Electro-Mechanical System (MEMS) technologies and wireless data transmission, has extended the effectiveness and range of applicability of WSSNs. One of the most common sensors employed in SHM strategies is the accelerometer; however, most accelerometers in WSS nodes have inadequate resolution for measurement of the typical accelerations found in many SHM applications. In this study, a high-resolution and low-noise tri-axial digital MEMS accelerometer is incorporated in a next-generation WSS platform, the Xnode. In addition to meeting the acceleration sensing demands of large-scale civil infrastructure applications, this new WSS node provides powerful hardware and a robust software framework to enable edge computing that can deliver actionable information. Hardware and software integration challenges are presented, and the associate resolutions are discussed. The performance of the wireless accelerometer is demonstrated experimentally through comparison with high-sensitivity wired accelerometers. This new high-sensitivity wireless accelerometer will extend the use of WSSN to a broader class of SHM applications. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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14 pages, 11029 KiB  
Article
Virtual Environments for Visualizing Structural Health Monitoring Sensor Networks, Data, and Metadata
by Rebecca Napolitano, Anna Blyth and Branko Glisic
Sensors 2018, 18(1), 243; https://doi.org/10.3390/s18010243 - 16 Jan 2018
Cited by 34 | Viewed by 5503
Abstract
Visualization of sensor networks, data, and metadata is becoming one of the most pivotal aspects of the structural health monitoring (SHM) process. Without the ability to communicate efficiently and effectively between disparate groups working on a project, an SHM system can be underused, [...] Read more.
Visualization of sensor networks, data, and metadata is becoming one of the most pivotal aspects of the structural health monitoring (SHM) process. Without the ability to communicate efficiently and effectively between disparate groups working on a project, an SHM system can be underused, misunderstood, or even abandoned. For this reason, this work seeks to evaluate visualization techniques in the field, identify flaws in current practices, and devise a new method for visualizing and accessing SHM data and metadata in 3D. More precisely, the work presented here reflects a method and digital workflow for integrating SHM sensor networks, data, and metadata into a virtual reality environment by combining spherical imaging and informational modeling. Both intuitive and interactive, this method fosters communication on a project enabling diverse practitioners of SHM to efficiently consult and use the sensor networks, data, and metadata. The method is presented through its implementation on a case study, Streicker Bridge at Princeton University campus. To illustrate the efficiency of the new method, the time and data file size were compared to other potential methods used for visualizing and accessing SHM sensor networks, data, and metadata in 3D. Additionally, feedback from civil engineering students familiar with SHM is used for validation. Recommendations on how different groups working together on an SHM project can create SHM virtual environment and convey data to proper audiences, are also included. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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16 pages, 1092 KiB  
Article
Introduction to State Estimation of High-Rate System Dynamics
by Jonathan Hong, Simon Laflamme, Jacob Dodson and Bryan Joyce
Sensors 2018, 18(1), 217; https://doi.org/10.3390/s18010217 - 13 Jan 2018
Cited by 46 | Viewed by 4774
Abstract
Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s [...] Read more.
Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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17 pages, 8525 KiB  
Article
A Tensor-Based Structural Damage Identification and Severity Assessment
by Ali Anaissi, Mehrisadat Makki Alamdari, Thierry Rakotoarivelo and Nguyen Lu Dang Khoa
Sensors 2018, 18(1), 111; https://doi.org/10.3390/s18010111 - 2 Jan 2018
Cited by 35 | Viewed by 5814
Abstract
Early damage detection is critical for a large set of global ageing infrastructure. Structural Health Monitoring systems provide a sensor-based quantitative and objective approach to continuously monitor these structures, as opposed to traditional engineering visual inspection. Analysing these sensed data is one of [...] Read more.
Early damage detection is critical for a large set of global ageing infrastructure. Structural Health Monitoring systems provide a sensor-based quantitative and objective approach to continuously monitor these structures, as opposed to traditional engineering visual inspection. Analysing these sensed data is one of the major Structural Health Monitoring (SHM) challenges. This paper presents a novel algorithm to detect and assess damage in structures such as bridges. This method applies tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies, i.e., structural damage. To evaluate this approach, we collected acceleration data from a sensor-based SHM system, which we deployed on a real bridge and on a laboratory specimen. The results show that our tensor method outperforms a state-of-the-art approach using the wavelet energy spectrum of the measured data. In the specimen case, our approach succeeded in detecting 92.5% of induced damage cases, as opposed to 61.1% for the wavelet-based approach. While our method was applied to bridges, its algorithm and computation can be used on other structures or sensor-data analysis problems, which involve large series of correlated data from multiple sensors. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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6107 KiB  
Article
Field Demonstration of Real-Time Wind Turbine Foundation Strain Monitoring
by Tim Rubert, Marcus Perry, Grzegorz Fusiek, Jack McAlorum, Pawel Niewczas, Amanda Brotherston and David McCallum
Sensors 2018, 18(1), 97; https://doi.org/10.3390/s18010097 - 31 Dec 2017
Cited by 10 | Viewed by 6151
Abstract
Onshore wind turbine foundations are generally over-engineered as their internal stress states are challenging to directly monitor during operation. While there are industry drivers to shift towards more economical foundation designs, making this transition safely will require new monitoring techniques, so that the [...] Read more.
Onshore wind turbine foundations are generally over-engineered as their internal stress states are challenging to directly monitor during operation. While there are industry drivers to shift towards more economical foundation designs, making this transition safely will require new monitoring techniques, so that the uncertainties around structural health can be reduced. This paper presents the initial results of a real-time strain monitoring campaign for an operating wind turbine foundation. Selected reinforcement bars were instrumented with metal packaged optical fibre strain sensors prior to concrete casting. In this paper, we outline the sensors’ design, characterisation and installation, and present 67 days of operational data. During this time, measured foundation strains did not exceed 95 μ ϵ , and showed a strong correlation with both measured tower displacements and the results of a foundation finite element model. The work demonstrates that real-time foundation monitoring is not only achievable, but that it has the potential to help operators and policymakers quantify the conservatism of their existing design codes. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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6832 KiB  
Article
Integrity Testing of Pile Cover Using Distributed Fibre Optic Sensing
by Yi Rui, Cedric Kechavarzi, Frank O’Leary, Chris Barker, Duncan Nicholson and Kenichi Soga
Sensors 2017, 17(12), 2949; https://doi.org/10.3390/s17122949 - 19 Dec 2017
Cited by 41 | Viewed by 9615
Abstract
The integrity of cast-in-place foundation piles is a major concern in geotechnical engineering. In this study, distributed fibre optic sensing (DFOS) cables, embedded in a pile during concreting, are used to measure the changes in concrete curing temperature profile to infer concrete cover [...] Read more.
The integrity of cast-in-place foundation piles is a major concern in geotechnical engineering. In this study, distributed fibre optic sensing (DFOS) cables, embedded in a pile during concreting, are used to measure the changes in concrete curing temperature profile to infer concrete cover thickness through modelling of heat transfer processes within the concrete and adjacent ground. A field trial was conducted at a high-rise building construction site in London during the construction of a 51 m long test pile. DFOS cables were attached to the reinforcement cage of the pile at four different axial directions to obtain distributed temperature change data along the pile. The monitoring data shows a clear development of concrete hydration temperature with time and the pattern of the change varies due to small changes in concrete cover. A one-dimensional axisymmetric heat transfer finite element (FE) model is used to estimate the pile geometry with depth by back analysing the DFOS data. The results show that the estimated pile diameter varies with depth in the range between 1.40 and 1.56 m for this instrumented pile. This average pile diameter profile compares well to that obtained with the standard Thermal Integrity Profiling (TIP) method. A parametric study is conducted to examine the sensitivity of concrete and soil thermal properties on estimating the pile geometry. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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5064 KiB  
Article
Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines
by Ulrike Dackermann, Yang Yu, Ernst Niederleithinger, Jianchun Li and Herbert Wiggenhauser
Sensors 2017, 17(12), 2938; https://doi.org/10.3390/s17122938 - 18 Dec 2017
Cited by 25 | Viewed by 7099
Abstract
This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband [...] Read more.
This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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2581 KiB  
Article
Wireless Concrete Strength Monitoring of Wind Turbine Foundations
by Marcus Perry, Grzegorz Fusiek, Pawel Niewczas, Tim Rubert and Jack McAlorum
Sensors 2017, 17(12), 2928; https://doi.org/10.3390/s17122928 - 16 Dec 2017
Cited by 14 | Viewed by 7143
Abstract
Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses [...] Read more.
Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses of structural health. Here, we demonstrate the field application of a dense, wireless thermocouple network to monitor the strength development of an onshore, reinforced-concrete wind turbine foundation. Up-to-date methods in fly ash concrete strength and maturity modelling are used to estimate the distribution and evolution of foundation strength over 29 days of curing. Strength estimates are verified by core samples, extracted from the foundation base. In addition, an artificial neural network, trained using temperature data, is exploited to demonstrate that distributed concrete strengths can be estimated for foundations using only sparse thermocouple data. Our techniques provide a practical alternative to computational models, and could assist site operators in making more informed decisions about foundation design, construction, operation and maintenance. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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4643 KiB  
Article
Optimal Multi-Type Sensor Placement for Structural Identification by Static-Load Testing
by Numa Joy Bertola, Maria Papadopoulou, Didier Vernay and Ian F. C. Smith
Sensors 2017, 17(12), 2904; https://doi.org/10.3390/s17122904 - 14 Dec 2017
Cited by 49 | Viewed by 5071
Abstract
Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called [...] Read more.
Assessing ageing infrastructure is a critical challenge for civil engineers due to the difficulty in the estimation and integration of uncertainties in structural models. Field measurements are increasingly used to improve knowledge of the real behavior of a structure; this activity is called structural identification. Error-domain model falsification (EDMF) is an easy-to-use model-based structural-identification methodology which robustly accommodates systematic uncertainties originating from sources such as boundary conditions, numerical modelling and model fidelity, as well as aleatory uncertainties from sources such as measurement error and material parameter-value estimations. In most practical applications of structural identification, sensors are placed using engineering judgment and experience. However, since sensor placement is fundamental to the success of structural identification, a more rational and systematic method is justified. This study presents a measurement system design methodology to identify the best sensor locations and sensor types using information from static-load tests. More specifically, three static-load tests were studied for the sensor system design using three types of sensors for a performance evaluation of a full-scale bridge in Singapore. Several sensor placement strategies are compared using joint entropy as an information-gain metric. A modified version of the hierarchical algorithm for sensor placement is proposed to take into account mutual information between load tests. It is shown that a carefully-configured measurement strategy that includes multiple sensor types and several load tests maximizes information gain. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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29299 KiB  
Article
Active Wireless System for Structural Health Monitoring Applications
by Ricardo Perera, Alberto Pérez, Marta García-Diéguez and José Luis Zapico-Valle
Sensors 2017, 17(12), 2880; https://doi.org/10.3390/s17122880 - 11 Dec 2017
Cited by 60 | Viewed by 6579
Abstract
The use of wireless sensors in Structural Health Monitoring (SHM) has increased significantly in the last years. Piezoelectric-based lead zirconium titanate (PZT) sensors have been on the rise in SHM due to their superior sensing abilities. They are applicable in different technologies such [...] Read more.
The use of wireless sensors in Structural Health Monitoring (SHM) has increased significantly in the last years. Piezoelectric-based lead zirconium titanate (PZT) sensors have been on the rise in SHM due to their superior sensing abilities. They are applicable in different technologies such as electromechanical impedance (EMI)-based SHM. This work develops a flexible wireless smart sensor (WSS) framework based on the EMI method using active sensors for full-scale and autonomous SHM. In contrast to passive sensors, the self-sensing properties of the PZTs allow interrogating with or exciting a structure when desired. The system integrates the necessary software and hardware within a service-oriented architecture approach able to provide in a modular way the services suitable to satisfy the key requirements of a WSS. The framework developed in this work has been validated on different experimental applications. Initially, the reliability of the EMI method when carried out with the proposed wireless sensor system is evaluated by comparison with the wireless counterpart. Afterwards, the performance of the system is evaluated in terms of software stability and reliability of functioning. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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6751 KiB  
Article
Development of a High Precision Displacement Measurement System by Fusing a Low Cost RTK-GPS Sensor and a Force Feedback Accelerometer for Infrastructure Monitoring
by Gunhee Koo, Kiyoung Kim, Jun Yeon Chung, Jaemook Choi, Nam-Yeol Kwon, Doo-Young Kang and Hoon Sohn
Sensors 2017, 17(12), 2745; https://doi.org/10.3390/s17122745 - 28 Nov 2017
Cited by 25 | Viewed by 7347
Abstract
A displacement measurement system fusing a low cost real-time kinematic global positioning system (RTK-GPS) receiver and a force feedback accelerometer is proposed for infrastructure monitoring. The proposed system is composed of a sensor module, a base module and a computation module. The sensor [...] Read more.
A displacement measurement system fusing a low cost real-time kinematic global positioning system (RTK-GPS) receiver and a force feedback accelerometer is proposed for infrastructure monitoring. The proposed system is composed of a sensor module, a base module and a computation module. The sensor module consists of a RTK-GPS rover and a force feedback accelerometer, and is installed on a target structure like conventional RTK-GPS sensors. The base module is placed on a rigid ground away from the target structure similar to conventional RTK-GPS bases, and transmits observation messages to the sensor module. Then, the initial acceleration, velocity and displacement responses measured by the sensor module are transmitted to the computation module located at a central monitoring facility. Finally, high precision and high sampling rate displacement, velocity, and acceleration are estimated by fusing the acceleration from the accelerometer, the velocity from the GPS rover, and the displacement from RTK-GPS. Note that the proposed displacement measurement system can measure 3-axis acceleration, velocity as well as displacement in real time. In terms of displacement, the proposed measurement system can estimate dynamic and pseudo-static displacement with a root-mean-square error of 2 mm and a sampling rate of up to 100 Hz. The performance of the proposed system is validated under sinusoidal, random and steady-state vibrations. Field tests were performed on the Yeongjong Grand Bridge and Yi Sun-sin Bridge in Korea, and the Xihoumen Bridge in China to compare the performance of the proposed system with a commercial RTK-GPS sensor and other data fusion techniques. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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7626 KiB  
Article
Crack Monitoring Method for an FRP-Strengthened Steel Structure Based on an Antenna Sensor
by Zhiping Liu, Kai Chen, Zongchen Li and Xiaoli Jiang
Sensors 2017, 17(10), 2394; https://doi.org/10.3390/s17102394 - 20 Oct 2017
Cited by 28 | Viewed by 7256
Abstract
Fiber-reinforced polymer (FRP) has been increasingly applied to steel structures for structural strengthening or crack repair, given its high strength-to-weight ratio and high stiffness-to-weight ratio. Cracks in steel structures are the dominant hidden threats to structural safety. However, it is difficult to monitor [...] Read more.
Fiber-reinforced polymer (FRP) has been increasingly applied to steel structures for structural strengthening or crack repair, given its high strength-to-weight ratio and high stiffness-to-weight ratio. Cracks in steel structures are the dominant hidden threats to structural safety. However, it is difficult to monitor structural cracks under FRP coverage and there is little related research. In this paper, a crack monitoring method for an FRP-strengthened steel structure deploying a microstrip antenna sensor is presented. A theoretical model of the dual-substrate antenna sensor with FRP is established and the sensitivity of crack monitoring is studied. The effects of the weak conductivity of carbon fiber reinforced polymers (CFRPs) on the performance of crack monitoring are analyzed via contrast experiments. The effects of FRP thickness on the performance of the antenna sensor are studied. The influence of structural strain on crack detection coupling is studied through strain–crack coupling experiments. The results indicate that the antenna sensor can detect cracks in steel structures covered by FRP (including CFRP). FRP thickness affects the antenna sensor’s performance significantly, while the effects of strain can be ignored. The results provide a new approach for crack monitoring of FRP-strengthened steel structures with extensive application prospects. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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5478 KiB  
Article
Monitoring Bridge Dynamic Responses Using Fiber Bragg Grating Tiltmeters
by Feng Xiao, Gang S. Chen and J. Leroy Hulsey
Sensors 2017, 17(10), 2390; https://doi.org/10.3390/s17102390 - 20 Oct 2017
Cited by 36 | Viewed by 7719
Abstract
In bridge health monitoring, tiltmeters have been used for measuring rotation and curvature; however, their application in dynamic parameter identification has been lacking. This study installed fiber Bragg grating (FBG) tiltmeters on the bearings of a bridge and monitored the dynamic rotational angle. [...] Read more.
In bridge health monitoring, tiltmeters have been used for measuring rotation and curvature; however, their application in dynamic parameter identification has been lacking. This study installed fiber Bragg grating (FBG) tiltmeters on the bearings of a bridge and monitored the dynamic rotational angle. The dynamic features, including natural frequencies and mode shapes, have been identified successfully. The innovation presented in this paper is the first-time use of FBG tiltmeter readings to identify the natural frequencies of a long-span steel girder bridge. The identified results have been verified using a bridge finite element model. This paper introduces a new method for the dynamic monitoring of a bridge using FBG tiltmeters. Limitations and future research directions are also discussed in the conclusion. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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15054 KiB  
Article
A Research on Low Modulus Distributed Fiber Optical Sensor for Pavement Material Strain Monitoring
by Lingjian Meng, Linbing Wang, Yue Hou and Guannan Yan
Sensors 2017, 17(10), 2386; https://doi.org/10.3390/s17102386 - 19 Oct 2017
Cited by 42 | Viewed by 5367
Abstract
The accumulated irreversible deformation in pavement under repeated vehicle loadings will cause fatigue failure of asphalt concrete. It is necessary to monitor the mechanical response of pavement under load by using sensors. Previous studies have limitations in modulus accommodation between the sensor and [...] Read more.
The accumulated irreversible deformation in pavement under repeated vehicle loadings will cause fatigue failure of asphalt concrete. It is necessary to monitor the mechanical response of pavement under load by using sensors. Previous studies have limitations in modulus accommodation between the sensor and asphalt pavement, and it is difficult to achieve the distributed monitoring goal. To solve these problems, a new type of low modulus distributed optical fiber sensor (DOFS) for asphalt pavement strain monitoring is fabricated. Laboratory experiments have proved the applicability and accuracy of the newly-designed sensor. This paper presents the results of the development. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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3379 KiB  
Article
Detection of Interfacial Debonding in a Rubber–Steel-Layered Structure Using Active Sensing Enabled by Embedded Piezoceramic Transducers
by Qian Feng, Qingzhao Kong, Jian Jiang, Yabin Liang and Gangbing Song
Sensors 2017, 17(9), 2001; https://doi.org/10.3390/s17092001 - 1 Sep 2017
Cited by 39 | Viewed by 5474
Abstract
Rubber–steel-layered structures are used in many engineering applications. Laminated rubber–steel bearing, as a type of seismic isolation device, is one of the most important applications of the rubber–steel-layered structures. Interfacial debonding in rubber–steel-layered structures is a typical failure mode, which can severely reduce [...] Read more.
Rubber–steel-layered structures are used in many engineering applications. Laminated rubber–steel bearing, as a type of seismic isolation device, is one of the most important applications of the rubber–steel-layered structures. Interfacial debonding in rubber–steel-layered structures is a typical failure mode, which can severely reduce their load-bearing capacity. In this paper, the authors developed a simple but effective active sensing approach using embedded piezoceramic transducers to provide an in-situ detection of the interfacial debonding between the rubber layers and steel plates. A sandwiched rubber–steel-layered specimen, consisting of one rubber layer and two steel plates, was fabricated as the test specimen. A novel installation technique, which allows the piezoceramic transducers to be fully embedded into the steel plates without changing the geometry and the surface conditions of the plates, was also developed in this research. The active sensing approach, in which designed stress waves can propagate between a pair of the embedded piezoceramic transducers (one as an actuator and the other one as a sensor), was employed to detect the steel–rubber debonding. When the rubber–steel debonding occurs, the debonded interfaces will attenuate the propagating stress wave, so that the amplitude of the received signal will decrease. The rubber–steel debonding was generated by pulling the two steel plates in opposite directions in a material-testing machine. The changes of the received signal before and after the debonding were characterized in a time domain and further quantified by using a wavelet packet-based energy index. Experiments on the healthy rubber–steel-layered specimen reveal that the piezoceramic-induced stress wave can propagate through the rubber layer. The destructive test on the specimen demonstrates that the piezoceramic-based active sensing approach can effectively detect the rubber–steel debonding failure in real time. The active sensing approach is often used in structures with “hard” materials, such as steel, concrete, and carbon fiber composites. This research lays a foundation for extending the active sensing approach to damage detection of structures involving “soft” materials, such as rubber. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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5102 KiB  
Article
Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors
by Bitao Wu, Huaxi Lu, Bo Chen and Zhicheng Gao
Sensors 2017, 17(7), 1657; https://doi.org/10.3390/s17071657 - 19 Jul 2017
Cited by 31 | Viewed by 5936
Abstract
A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local [...] Read more.
A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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15375 KiB  
Article
Development and Application of a Structural Health Monitoring System Based on Wireless Smart Aggregates
by Shi Yan, Haoyan Ma, Peng Li, Gangbing Song and Jianxin Wu
Sensors 2017, 17(7), 1641; https://doi.org/10.3390/s17071641 - 17 Jul 2017
Cited by 75 | Viewed by 12585
Abstract
Structural health monitoring (SHM) systems can improve the safety and reliability of structures, reduce maintenance costs, and extend service life. Research on concrete SHMs using piezoelectric-based smart aggregates have reached great achievements. However, the newly developed techniques have not been widely applied in [...] Read more.
Structural health monitoring (SHM) systems can improve the safety and reliability of structures, reduce maintenance costs, and extend service life. Research on concrete SHMs using piezoelectric-based smart aggregates have reached great achievements. However, the newly developed techniques have not been widely applied in practical engineering, largely due to the wiring problems associated with large-scale structural health monitoring. The cumbersome wiring requires much material and labor work, and more importantly, the associated maintenance work is also very heavy. Targeting a practical large scale concrete crack detection (CCD) application, a smart aggregates-based wireless sensor network system is proposed for the CCD application. The developed CCD system uses Zigbee 802.15.4 protocols, and is able to perform dynamic stress monitoring, structural impact capturing, and internal crack detection. The system has been experimentally validated, and the experimental results demonstrated the effectiveness of the proposed system. This work provides important support for practical CCD applications using wireless smart aggregates. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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3927 KiB  
Article
A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures
by Gwanghee Heo and Joonryong Jeon
Sensors 2017, 17(7), 1620; https://doi.org/10.3390/s17071620 - 12 Jul 2017
Cited by 13 | Viewed by 4598
Abstract
In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with [...] Read more.
In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size. Full article
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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