Showing papers on "Structural health monitoring published in 2012"

Vibration-based methods for structural and machinery fault diagnosis based on nonlinear dynamics tools

Abstract: This study explains and demonstrates the utilisation of different nonlinear-dynamics-based procedures for the purposes of structural health monitoring as well as for monitoring of robot joints.

Use of FBG Sensors for SHM in Aerospace Structures

Abstract: This paper details some significant findings on the use of the fiber Bragg grating (FBG) sensors for structural health monitoring (SHM) in aerospace fiber reinforced polymer (FRP) structures. A diminutive sensor provides a capability of imbedding inside FRP structures to monitor vital locations of damage. Some practical problems associated with the implementation of FBG based SHM systems in the aerospace FRP structures such as the difficulty of embedding FBG sensors during the manufacturing process and interrelation of distortion to FBG spectra due to internal damage, and other independent effects will be thoroughly studied. An innovative method to interpret FBG signals for identifying damage inside the structures will also be discussed.

A modified monkey algorithm for optimal sensor placement in structural health monitoring

Abstract: Proper placement of sensors plays a key role in construction and implementation of an effective structural health monitoring (SHM) system. This paper outlines a novel methodology called the modified monkey algorithm (MA) for the optimum design of SHM system sensor arrays, which is very different from the conventional method and is simple to implement. The integer coding method instead of the binary coding method is proposed to code the solution. The Euclidean distance operator and the stochastic perturbation mechanism of the harmony search algorithm are employed to improve the local and global search capability. A computational case of a high-rise building has been implemented to demonstrate the effectiveness of the modified method. The obtained sensor placements using the modified MA are compared with those gained by the existing MA using the integer coding method and the famous forward sequential sensor placement algorithm. Results showed that the innovations in the MA proposed in this paper could improve the convergence of the algorithm and the method is effective in solving combinatorial optimization problems such as optimal sensor placement.

Features for damage detection with insensitivity to environmental and operational variations

Abstract: This paper explores and compares the application of three different approaches to the data normalization problem in structural health monitoring (SHM), which concerns the removal of confounding trends induced by varying operational conditions from a measured structural response that correlates with damage. The methodologies for singling out or creating damage-sensitive features that are insensitive to environmental influences explored here include cointegration, outlier analysis and an approach relying on principal component analysis. The application of cointegration is a new idea for SHM from the field of econometrics, and this is the first work in which it has been comprehensively applied to an SHM problem. Results when applying cointegration are compared with results from the more familiar outlier analysis and an approach that uses minor principal components. The ability of these methods for removing the effects of environmental/operational variations from damage-sensitive features is demonstrated and compared with benchmark data from the Brite-Euram project DAMASCOS (BE97 4213), which was collected from a Lamb-wave inspection of a composite panel subject to temperature variations in an environmental chamber.

Instrumentation, Nondestructive Testing, and Finite-Element Model Updating for Bridge Evaluation Using Strain Measurements

Abstract: A baseline finite element model was developed for bridge management and calibration using nondestructive test data. The model calibration technique was evaluated on the Vernon Avenue Bridge over the Ware River in Barre, Massachusetts. This newly constructed bridgewas instrumented throughout its construction phases in preparation for a static truck load test performed before the bridge opening. The strain data collected during the load test was used to calibrate a detailed baseline finite element model in an effort to represent the 3D system behavior of the bridge. Three methods of load ratings were used and compared: (1) conventional method, (2) conventional method updated by using NDT data, and (3) finite element model calibrated with NDT data. DOI: 10.1061/(ASCE)BE.1943-5592.0000228. © 2012 American Society of Civil Engineers. CE Database subject headings: Bridges; Superstructures; Full-scale tests; Field tests; Nondestructive tests; Strain; Measurement; Finite element method; Load tests; Structural health monitoring. Author keywords: Bridge; Superstructure; Full scale; Field testing; Strain measurements; Finite elements; Model calibration; Load testing; Load rating; Structural health monitoring; SHM.

Wireless Measurement System for Structural Health Monitoring With High Time-Synchronization Accuracy

Abstract: Structural health monitoring (SHM) systems have excellent potential to improve the regular operation and maintenance of structures. Wireless networks (WNs) have been used to avoid the high cost of traditional generic wired systems. The most important limitation of SHM wireless systems is time-synchronization accuracy, scalability, and reliability. A complete wireless system for structural identification under environmental load is designed, implemented, deployed, and tested on three different real bridges. Our contribution ranges from the hardware to the graphical front end. System goal is to avoid the main limitations of WNs for SHM particularly in regard to reliability, scalability, and synchronization. We reduce spatial jitter to 125 ns, far below the 120 μs required for high-precision acquisition systems and much better than the 10-μs current solutions, without adding complexity. The system is scalable to a large number of nodes to allow for dense sensor coverage of real-world structures, only limited by a compromise between measurement length and mandatory time to obtain the final result. The system addresses a myriad of problems encountered in a real deployment under difficult conditions, rather than a simulation or laboratory test bed.

Enhanced composites integrity through structural health monitoring

Abstract: This paper discusses the topic of how the integrity of safety-critical structural composites can be enhanced by the use of structural health monitoring (SHM) techniques. The paper starts with a presentation of how the certification of flight-critical composite structures can be achieved within the framework of civil aviation safety authority requirements. Typical composites damage mechanisms, which make this process substantially different from that for metallic materials are discussed. The opportunities presented by the use of SHM techniques in future civil aircraft developments are explained. The paper then focuses on active SHM with piezoelectric wafer active sensors (PWAS). After reviewing the PWAS-based SHM options, the paper follows with a discussion of the specifics of guided wave propagation in composites and PWAS-tuning effects. The paper presents a number of experimental results for damage detection in simple flat unidirectional and quasi-isotropic composite specimens. Calibrated through holes of increasing diameter and impact damage of various energies and velocities are considered. The paper ends with conclusions and suggestions for further work.

Predictive modeling of electromechanical impedance spectroscopy for composite materials

Abstract: The advancement of composite materials in aircraft structures has led to an increased need for effective structural health monitoring technologies that are able to detect and assess damage present in composite structures. The study presented in this article is interested in understanding self-sensing piezoelectric wafer sensors to conduct electromechanical impe- dance spectroscopy in glass fiber reinforced polymer composite to perform structural health monitoring. For this objec- tive, multi-physics-based finite element method is used to model the electromechanical behavior of a free piezoelectric wafer active sensor and its interaction with the host structure on which it is bonded. The multi-physics-based modeling permits the input and output variables to be expressed directly in electric terms, while the two-way electromechanical conversion is done internally in the multi-physics-based finite element method formulation. The impedance responses are also studied in conditions when the sensor bonding layer is subject to degradation and when the sensor itself is sub- jected to breakage, respectively. To reach the goal of using the electromechanical impedance spectroscopy approach to detect damage, several damage models are generated on simplified orthotropic structure and laminated glass fiber rein- forced polymer structures. The effects of the modeling are carefully studied through experimental validation. A good match has been observed for low and high frequencies.

State-of-the-Art Review of Technologies for Pipe Structural Health Monitoring

Abstract: Advances in electronics, sensor technology, information science, electrical and computer engineering give rise to emerging technologies, some of which could be applied to the inspection, monitoring, and condition assessment of buried water mains. This paper presents a state of the review of sensor technologies used for monitoring indicators pointing to pipe structural deterioration. The potential for multi-sensor system and sensor data fusion for condition-based maintenance are also discussed.

Intelligent health monitoring of aerospace composite structures based on dynamic strain measurements

Abstract: This work presents a study on an intelligent system for structural health monitoring of aerospace structures based on dynamic strain measurements, in order to identify in an exhaustive way the structural state condition Four fiber Bragg grating (FBG) optical sensors were used for collecting strain data, representing the dynamic response of the structure and the expert system that was developed was based on the collected response data Multi-sensor data fusion in a feature-level approach was followed Advanced signal processing and pattern recognition techniques such as discrete wavelet transform (DWT) and support vector machines (SVM) were used in the system For the current analysis, independent component analysis (ICA) was additionally used for the reduction of feature space The results showed that SVMs using non-linear kernel is a powerful and promising pattern recognition scheme for damage diagnosis The system was developed and experimentally validated on a flat stiffened composite panel, representing a section of a typical aeronautical structure Within the frame of the present work the flat stiffened panel was manufactured using carbon fiber pre-pregs Damage was simulated by slightly varying the mass of the panel in different zones of the structure by adding lumped masses The analysis of operational dynamic responses was employed to identify both the damage and its position Numerical simulation with finite element analysis (FEA) was also used as a support tool

Long-term condition assessment of suspenders under traffic loads based on structural monitoring system : application to the Tsing Ma Bridge

Abstract: SUMMARY Structural health monitoring (SHM) system provides an efficient way to the diagnosis and prognosis of critical and large-scale civil infrastructures like long-span bridges. This paper presents a long-term condition assessment approach of suspenders in a cable-suspension bridge under in-service traffic loads based on structural monitoring technique. The traffic loads identified from a monitoring system, including both highway and railway traffic loads, and the finite element model of the bridge are employed to determine the axial force response of the suspender. The stochastic axial force response in the suspender is described by a filtered Poisson process, through which the maximum value distribution of axial forces in its design reference period can be derived using the Poisson Process theory. In this paper, the long-term deterioration process of steel wires in the suspender considers simultaneously the uniform and pitting corrosion and the corrosion fatigue induced by both cyclic loading and environmental attack. Such a stochastic and coupled corrosion fatigue process of steel wires is simulated using the Monte Carlo method, and the time-variant conditions of the suspender are subsequently assessed in a probabilistic way, such as crack depth, number of broken wires, ultimate strength, etc. In particular, two load conditions—the train loads alone and the combination of train load and road traffic load—are examined within this procedure in order to investigate their respective effects on the deterioration. By employing first-order reliability method, the reliability indexes of the suspender under the traffic loads are further estimated in terms of the safety under the extreme traffic load distribution in the design reference period and the serviceability specified in the design specification. The discussions of the life-cycle reliability indexes of the suspender provide guidance to the future decision making related to maintenance and replacement of suspenders, and it may also shed light on the long-term condition assessment of other structural members. Copyright © 2010 John Wiley & Sons, Ltd.

Effect of varying axial load under fixed boundary condition on admittance signatures of electromechanical impedance technique

Abstract: In recent years, researchers in the field of structural health monitoring have been rigorously striving to replace the conventional nondestructive evaluation techniques with the smart material–based structural health monitoring techniques. These techniques possess distinct advantages over the conventional techniques, such as capable of providing autonomous, real-time, reliable, and cost-efficient monitoring. For instance, the electromechanical impedance technique employing smart piezo-impedance transducer (lead zirconate titanate) is known for its sensitivity in detecting damage. The admittance signatures of the electromechanical impedance technique for structural health monitoring are susceptible to variation in the static load applied on the host structure, which should not be ignored. This article presents a series of experimental, analytical, and numerical studies conducted to investigate the effect of varying axial load in the presence of fixed boundary condition on the admittance signatures. Theoret...

MUSIC‐ANN Analysis for Locating Structural Damages in a Truss‐Type Structure by Means of Vibrations

Abstract: This article will present a methodology for damage detection, location, and quantification based on vibration signature analysis and a comprehensive experimental study to assess the utility of the proposed structural health monitoring applied to a five-bay truss-type structure. The MUltiple SIgnal Classification (MUSIC) algorithm introduced first by Jiang and Adeli for health monitoring of structures in 2007 is fused with artificial neural networks (ANN) for an automated result. The developed methodology is based on feeding the amplitude of the natural frequencies as input of an artificial neural network, being the novelty of the proposed methodology its ability to identify, locate, and quantify the severity of damages with precision such as: external and internal corrosion and cracks in an automated monitoring process. Results show the proposed methodology is effective for detecting a healthy structure, a structure with external and internal corrosion, and a structure with crack. Therefore, the proposed fusion of MUSIC-ANN algorithms can be regarded as a simple, effective, and automated tool without requiring sophisticated equipment. The algorithms are moving toward establishing a practical and reliable structural health monitoring methodology, which will help in evaluating the condition of the structure in order to detect damages early and to make the corresponding maintenance decisions in the structures.

SHM benchmark for high-rise structures: a reduced-order finite element model and field measurement data

Abstract: The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of realworld monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reducedorder FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

Soft capacitive sensor for structural health monitoring of large-scale systems

Abstract: SUMMARY Structural integrity of infrastructures can be preserved if damage is diagnosed, localized, and repaired in time. During the past decade, there has been a considerable effort to automate the process of structural health monitoring, which is complicated by the inherent large size of civil structures. Hence, a need has arisen to develop new approaches that enable more effective health monitoring. In this paper, a new sensing technique for damage localization on large civil structures is proposed. Specifically, changes in strain are detected using a capacitance sensor built with a soft, stretchable dielectric polymer with attached stretchable metal film electrodes. A change in strain causes a measurable change in the capacitance of the sensor, which can be directly monitored when the sensor is fixed to a structure. The proposed method is shown here to permit an accurate detection of cracks. The proposed system deploys a layer of dielectric polymer on the surface of a structural element, and regularly monitors any change in capacitance, giving in turn information about the structural state. The smart material is composed of inexpensive silicone elastomers, which make the monitoring system a promising application for large surfaces. Results from tests conducted on small-scale specimens showed that the technology is capable of detecting cracks, and tests conducted on large-size specimens demonstrated that several sensor patches organized on a sensor sheet are capable of localizing a crack. The sensor strain also exhibits a high correlation with the loss of stiffness. Copyright © 2010 John Wiley & Sons, Ltd.

Impact localization in composite structures of arbitrary cross section

Abstract: This article proposes an in situ structural health monitoring method able to locate the impact source and to determine the flexural Lamb mode A0 velocity in composite structures with unknown lay-up...

Nonparametric analysis of structural health monitoring data for identification and localization of changes: Concept, lab, and real-life studies:

Abstract: Structural health monitoring systems integrate novel experimental technologies, analytical methods, and information technologies for a number of objectives such as detecting structural changes and damage as well as assessing the condition, safety, and serviceability of the monitored structure. The objective of this article is to present a correlation-based methodology as an effective nonparametric data analysis approach for detecting and localizing structural changes using strain data under operational loading conditions. While several methods have been explored in the literature, the focus of this article is to explore a practical and cost-effective (in terms of sensor, data acquisition, and analysis) methodology to identify structural problems. The methodology presented here is based on tracking correlation coefficients between strain time histories at different locations. After discussing the background, the effectiveness of the methodology is first demonstrated on a laboratory test structure. A unique...

Multi-objective Optimization of Sensor and Excitation Layouts for Frequency Response Function-Based Structural Damage Identification

Abstract: :i¾?The accuracy of many damage identification methods depends significantly on the quality of measurements collected by sensors, such as accelerometers, concerning the response characteristics of a structure. Often the number of sensors used to collect measurements is limited due to available funds, equipment, and access. In addition, the excitation location can significantly affect a sensor's ability to collect quality measurement information. Therefore, both the location and number of sensors and the location of the excitation must be optimized to maximize the quality of information collected. A multi-objective optimization approach is presented that minimizes the number of sensors specified while maximizing the sensitivity of the frequency response functions FRFs collected at each specified sensor location with respect to all possible damaged structural elements. The multiple Pareto-optimal sensor/excitation layouts obtained aid in determining the number of sensors required to obtain an effective level of measurement information. The benefit of using Pareto-optimal sensor/excitation layouts is investigated by using the optimized layouts to collect measurement information for a FRF-based structural damage identification method. Trial results confirm that an increase in damage identification accuracy and efficiency is achieved when Pareto-optimal sensor/excitation layouts are used instead of nonoptimal layouts. In addition, the Pareto-optimal layouts improved damage identification accuracy in noisy measurement environments due to increasing the quality of measurements collected.

Deploying Wireless Sensor Networks with Fault Tolerance for Structural Health Monitoring

Abstract: Structural health monitoring (SHM) brings new challenges to wireless sensor networks (WSNs) : large volume of data, sophisticated computing, engineering-driven optimal deployment, and so forth. In this paper, we address two important challenges: sensor placement and decentralized computing. We propose a solution to place sensors at strategic locations to achieve the best estimates of geometric properties of a structure. To make the deployed network resilient to faults caused by communication errors, unstable network connectivity, and sensor faults, we present an approach, called FTSHM (fault tolerance in SHM), to repairing the network to guarantee a specified degree of fault tolerance. FTSHM searches the repairing points in clusters and places a set of backup sensors at those points by satisfying civil engineering requirements. FTSHM also includes a SHM algorithm suitable for decentralized computing in energy-constrained WSNs, with the objective to guarantee that the WSN for SHM remains connected in the event of a sensor fault thus prolonging the WSN lifetime under connectivity and data delivery constraints. We demonstrate the advantages of FTSHM through simulations and experiments on a real civil structure.

Bridge Monitoring Using Brillouin Fiber-Optic Sensors

Abstract: We report the results of a static load test performed on a road-bridge with a span length of 44.40 m. The tests were performed by a portable prototype instrument exploiting stimulated Brillouin scattering in optical fibers for deformation and temperature measurements. The optical fiber sensor was able to provide the strain distribution along a supporting beam of the bridge with a spatial resolution of 3 meters and a strain resolution of ±15 μe. Comparison of fiber-optic measurements with finite-elements-method (FEM) simulations, as well as with data collected by vibrating wire strain gauges, confirmed the validity of the SBS-based approach in monitoring the deformation of large structures.

In-service condition assessment of bridge deck using long-term monitoring data of strain response

Abstract: Continuous awareness of the evolution of the structural condition of bridge structures is of great value for bridge owners, as it allows them to make informed decisions regarding the maintenance and management of these public facilities. Structural condition assessment via monitoring has gained in popularity in recent years, because it can provide structural engineers with plentiful information on the structural condition through various sensors. A key issue for successful application of monitoring technologies for condition assessment is how to realize meaningful interpretations of monitoring data. In this study, an approach to structural condition assessment of in-service bridge deck making use of long-term monitoring data of strain response is proposed and applied to the instrumented Tsing Ma Bridge. The proposed method consists of structural assessment at two levels: (1) deck truss component level and (2) deck cross-section level. As long-term monitoring data of dynamic strain under the in-ser...