Showing papers on "Structural health monitoring published in 2005"
TL;DR: The importance of implementing long-term structural health monitoring systems for large-scale bridges, in order to secure structural and operational safety and issue early warnings on damage or deterioration prior to costly repair or even catastrophic collapse, has been recognized by bridge administrative authorities.
879 citations
TL;DR: In this paper, a damage detection method based on principal component analysis (PCA) applied to vibration features identified during the monitoring of the structure is proposed for structural health monitoring under varying environmental and operational conditions.
489 citations
TL;DR: A methodology for applying diffuse ultrasonic waves to the problem of detecting structural damage in the presence of unmeasured temperature changes and it is shown that a probability of detection of over 95% can be achieved with a small number of baseline waveforms.
353 citations
TL;DR: In this article, a formulation for modeling the transient GW field excited using arbitrary shaped surface-bonded piezos in isotropic plates based on the 3D linear elasticity equations is presented.
Abstract: Among the various schemes being considered for structural health monitoring (SHM), guided wave (GW) testing in particular has shown great promise. While GW testing using hand-held transducers for non-destructive evaluation (NDE) is a well established technology, GW testing for SHM using surface-bonded/embedded piezoelectric wafer transducers (piezos) is relatively in its formative years. Little effort has been made towards a precise characterization of GW excitation using piezos and often the various parameters involved are chosen without mathematical foundation. In this work, a formulation for modeling the transient GW field excited using arbitrary shaped surface-bonded piezos in isotropic plates based on the 3D linear elasticity equations is presented. This is then used for the specific cases of rectangular and ring-shaped actuators, which are most commonly used in GW SHM. Equations for the output voltage response of surface-bonded piezo-sensors in GW fields are derived and optimization of the actuator/sensor dimensions is done based on these. Finally, numerical and experimental results establishing the validity of these models are discussed.
278 citations
Journal Article•
TL;DR: Evaluating the performance of a multi-hop wireless data acquisition system for structural health monitoring (SHM) on a large seismic test structure used by civil engineers indicates that Wisden can reliably deliver time-synchronized tri-axial structural vibration data reliably across multiple hops with low latencies for sampling rates up to 200 Hz.
Abstract: While sensor network research has made significant strides in the past few years, the literature has relatively few examples of papers that have evaluated and validated a complete experimental system. In this paper we discuss our deployment experiences and evaluate the performance of a multi-hop wireless data acquisition system (called Wisden) for structural health monitoring (SHM) on a large seismic test structure used by civil engineers. Our experiments indicate that, with the latest sensor network hardware, Wisden can reliably deliver time-synchronized tri-axial structural vibration data reliably across multiple hops with low latencies for sampling rates up to 200Hz. This performance was achieved by iteratively refining the system design using a series of test deployments. Our experiences suggested the need for careful onset detection in order to preserve the fidelity of the structure’s frequency response. Furthermore, the high damping characteristics of large structures motivated an exploration of the processing, sampling, and communication limits of current platforms.
273 citations
TL;DR: A local PCA-based damage detection method is applied for the structural health monitoring of a real bridge using vibration data measured in situ over a one-year period.
271 citations
TL;DR: In this paper, a support vector machine (SVM) technique is applied to formulate regression models which quantify the effect of temperature on modal frequencies for the cable-stayed Ting Kau Bridge (Hong Kong), which has been instrumented with a long-term structural health monitoring system.
261 citations
TL;DR: In this article, a multi-disciplinary research program on fiber bragg grating sensors involving the School of Civil and Structural Engineering at Nanyang Technological University in Singapore is reported.
250 citations
Abstract: In this paper we review the state of the art in an emerging new technology: embedded ultrasonic non-destructive evaluation (NDE). Embedded ultrasonic NDE permits active structural health monitoring, i.e. the on-demand interrogation of the structure to determine its current state of structural health. The enabling element of embedded ultrasonic NDE is the piezoelectric wafer active sensor (PWAS). We begin by reviewing the guided wave theory in plate, tube, and shell structures, with special attention to Lamb waves. The mechanisms of Lamb wave excitation and detection with embeddable PWAS transducers is presented. It is shown analytically and verified experimentally that Lamb wave mode tuning can be achieved by the judicious combination of PWAS dimensions, frequency value, and Lamb mode characteristics. Subsequently, we address in turn the use of pitch-catch, pulse-echo, and phased array ultrasonic methods for Lambwave damage detection. In each case, the conventional ultrasonic NDE results are contrasted with embedded NDE results. Detection of cracks, disbonds, delaminations, and diffuse damage in metallic and composite structures are exemplified. Other techniques, such as the time reversal method and the migration technique, are also presented. The paper ends with conclusions and suggestions for further work.
243 citations
TL;DR: In this paper, the use of the electro-mechanical (E/M) impedance method for health monitoring of thin-wall aircraft panels and aerospace structures is described, which accounts for axial and flexural vibrations of the structure and considers both the structural dynamics and the sensor dynamics.
Abstract: The use of the electro-mechanical (E/M) impedance method for health monitoring of thin plates and aerospace structures is described. As a nondestructive evaluation technology, the E/M impedance method allows us to identify the local dynamics of the structure directly through the E/M impedance signatures of piezoelectric wafer active sensors (PWAS) permanently mounted to the structure. An analytical model for 2-D thin-wall structures, which predicts the E/M impedance response at PWAS terminals, was developed and validated. The model accounts for axial and flexural vibrations of the structure and considers both the structural dynamics and the sensor dynamics. Calibration experiments performed on circular thin plates with centrally attached PWAS showed that the presence of damage modifies the high-frequency E/M impedance spectrum causing frequency shifts, peak splitting, and appearance of new harmonics. Overall-statistics damage metrics and probabilistic neural network (PNN) are used to classify the spectral data and identify damage severity. On thin-wall aircraft panels, the presence of damage influences the sensors E/M impedance spectrum. When crack damage is in the PWAS medium field, changes in the distribution of harmonics take place and when crack damage is in the PWAS near field, changes in both the harmonics and the dereverberated response are observed. These effects are successfully classified with PNN and overall-statistics metrics, respectively. This proves that permanently attached PWAS in conjunction with the E/M impedance method can be successfully used in structural health monitoring to detect the presence of incipient damage through the examination and classification of the high-frequency E/M impedance spectra.
222 citations
30 Apr 2005
TL;DR: In this article, the performance of a multi-hop wireless data acquisition system for structural health monitoring (SHM) on a large seismic test structure used by civil engineers is evaluated.
Abstract: While sensor network research has made significant strides in the past few years, the literature has relatively few examples of papers that have evaluated and validated a complete experimental system. In this paper, we discuss our deployment experiences and evaluate the performance of a multi-hop wireless data acquisition system (called Wisden) for structural health monitoring (SHM) on a large seismic test structure used by civil engineers. Our experiments indicate that, with the latest sensor network hardware, Wisden can reliably deliver time-synchronized tri-axial structural vibration data reliably across multiple hops with low latencies for sampling rates up to 200 Hz. This performance was achieved by iteratively refining the system design using a series of test deployments. Our experiences suggested the need for careful onset detection in order to preserve the fidelity of the structure's frequency response. Furthermore, the high damping characteristics of large structures motivated an exploration of the processing, sampling, and communication limits of current platforms.
TL;DR: In this paper, a neural networks-based damage detection method using the modal properties is presented, which can effectively consider the modelling errors in the baseline finite element model from which the training patterns are to be generated.
TL;DR: Experimental results show that the local temporal coherence is effective in discriminating structural damage from both temperature changes and modest changes in surface conditions; results are compared to those obtained from time domain and spectrogram differencing.
Abstract: Permanently mounted ultrasonic transducers have the potential to interrogate large areas of a structure, and thus be effective global sensors for structural health monitoring. Recorded signals, although very sensitive to damage, are long, complex, and difficult to interpret compared to pulse echo and through transmission signals customary for nondestructive testing. These diffuse signals also are quite sensitive to environmental effects such as temperature and surface condition changes. Waveform comparison methods such as time domain differencing and spectral analysis, although effective for detecting changes, are generally unsuccessful in discriminating damage from environmental effects. This paper considers the local temporal coherence as another means of comparing two waveforms in order to provide a quantitative measure of the change in shape of a signal compared to a reference as a function of time from transmit. Experimental results show that the local temporal coherence is effective in discriminating structural damage from both temperature changes and modest changes in surface conditions; results are compared to those obtained from time domain and spectrogram differencing. The advantages of this methodology are the simplicity of the transducers, the applicability to a wide range of structures, and the straightforward signal processing.
Book•
27 May 2005
TL;DR: In this paper, the authors proposed a method for measuring the Vibration Elements of a bridge in order to determine the amount of stress in the bridge and the effect of external and internal stress on the bridge.
Abstract: PREFACE. ACKNOWLEDGEMENTS. SUMMARY. 1 INTRODUCTION. 1.1 Scope of Applications. 1.2 Laws and Regulations. 1.3 Theories on the Development of the AVM. 2 OBJECTIVES OF APPLICATIONS. 2.1 System Identification. 2.1.1 Eigenfrequencies and Mode Shapes. 2.1.2 Damping. 2.1.3 Deformations and Displacements. 2.1.4 Vibration Intensity. 2.1.5 Trend Cards. 2.2 Stress Test. 2.2.1 Determination of Static and Dynamic Stresses. 2.2.2 Determination of the Vibration Elements. 2.2.3 Stress of Individual Structural Members. 2.2.4 Determination of Forces in Tendons and Cables. 2.3 Assessment of Stresses. 2.3.1 Structural Safety. 2.3.2 Structural Member Safety. 2.3.3 Maintenance Requirements and Intervals. 2.3.4 Remaining Operational Lifetime. 2.4 Load Observation (Determination of External Influences). 2.4.1 Load Collective. 2.4.2 Stress Characteristic. 2.4.3 Verification of Load Models. 2.4.4 Determination of Environmental Influences. 2.4.5 Determination of Specific Measures. 2.4.6 Check on the Success of Rehabilitation Measures. 2.4.7 Dynamic Effects on Cables and Tendons. 2.4.8 Parametric Excitation. 2.5 Monitoring of the Condition of Structures. 2.5.1 Assessment of Individual Objects. 2.5.2 Periodic Monitoring. 2.5.3 BRIMOS- Recorder. 2.5.4 Permanent Monitoring. 2.5.5 Subsequent Measures. 2.6 Application of Ambient Vibration Testing to Structures for Railways. 2.6.1 Sleepers. 2.6.2 Noise and Vibration Problems. 2.7 Limitations. 2.7.1 Limits of Measuring Technology. 2.7.2 Limits of Application. 2.7.3 Limits of Analysis. 2.7.4 Perspectives. References. 3 FEEDBACK FROM MONITORING TO BRIDGE DESIGN. 3.1 Economic Background. 3.2 Lessons Learned. 3.2.1 Conservative Design. 3.2.2 External versus Internal Pre-stressing. 3.2.3 Influence of Temperature. 3.2.4 Displacement. 3.2.5 Large Bridges versus Small Bridges. 3.2.6 Vibration Intensities. 3.2.7 Damping Values of New Composite Bridges. 3.2.8 Value of Patterns. 3.2.9 Understanding of Behaviour. 3.2.10 Dynamic Factors. References. 4 PRACTICAL MEASURING METHODS. 4.1 Execution of Measuring. 4.1.1 Test Planning. 4.1.2 Levelling of the Sensors. 4.1.3 Measuring the Structure. 4.2 Dynamic Analysis. 4.2.1 Calculation Models. 4.2.2 State of the Art. 4.3 Measuring System. 4.3.1 BRIMOS(r). 4.3.2 Sensors. 4.3.3 Data-Logger. 4.3.4 Additional Measuring Devices and Methods. 4.4 Environmental Influence. 4.5 Calibration and Reliability. 4.6 Remaining Operational Lifetime. 4.6.1 Rainflow Algorithm. 4.6.2 Calculation of Stresses by FEM. 4.6.3 S-N Approach and Damage Accumulation. 4.6.4 Remaining Service Lifetime by Means of Existing Traffic Data and Additional Forward and Backward Extrapolation. 4.6.5 Conclusions and Future Work. References. 5 PRACTICAL EVALUATION METHODS. 5.1 Plausibility of Raw Data. 5.2 AVM Analysis. 5.2.1 Recording. 5.2.2 Data Reduction. 5.2.3 Data Selection. 5.2.4 Frequency Analysis, ANPSD (Averaged Normalized Power Spectral Density). 5.2.5 Mode Shapes. 5.2.6 Damping. 5.2.7 Deformations. 5.2.8 Vibration Coefficients. 5.2.9 Counting of Events. 5.3 Stochastic Subspace Identification Method. 5.3.1 The Stochastic Subspace Identification (SSI) Method. 5.3.2 Application to Bridge Z24. 5.4 Use of Modal Data in Structural Health Monitoring. 5.4.1 Finite Element Model Updating Method. 5.4.2 Application to Bridge Z24. 5.4.3 Conclusions. 5.5 External Tendons and Stay Cables. 5.5.1 General Information. 5.5.2 Theoretical Bases. 5.5.3 Practical Implementation. 5.5.4 State of the Art. 5.5.5 Rain-Wind Induced Vibrations of Stay Cables. 5.5.6 Assessment. 5.6 Damage Identification and Localization. 5.6.1 Motivation for SHM. 5.6.2 Current Practice. 5.6.3 Condition and Damage Indices. 5.6.4 Basic Philosophy of SHM. 5.7 Damage Prognosis. 5.7.1 Sensing Developments. 5.7.2 Data Interrogation Procedure for Damage Prognosis. 5.7.3 Predictive Modelling of Damage Evolution. 5.8 Animation and the Modal Assurance Criterion (MAC). 5.8.1 Representation of the Calculated Mode Shapes. 5.8.2 General Requirements. 5.8.3 Correlation of Measurement and Calculation (MAC). 5.8.4 Varying Number of Eigenvectors. 5.8.5 Complex Eigenvector Measurement. 5.8.6 Selection of Suitable Check Points using the MAC. 5.9 Ambient Vibration Derivatives (AVD(r)). 5.9.1 Aerodynamic Derivatives. 5.9.2 Applications of the AVM. 5.9.3 Practical Implementation. References. 6 THEORETICAL BASES. 6.1 General Survey on the Dynamic Calculation Method. 6.2 Short Description of Analytical Modal Analysis. 6.3 Equation of Motion of Linear Structures. 6.3.1 SDOF System. 6.3.2 MDOF System. 6.3.3 Influence of Damping. 6.4 Dynamic Calculation Method for the AVM. 6.5 Practical Evaluation of Measurements. 6.5.1 Eigenfrequencies. 6.5.2 Mode Shapes. 6.5.3 Damping. 6.6 Theory on Cable Force Determination. 6.6.1 Frequencies of Cables as a Function of the Inherent Tensile Force. 6.6.2 Influence of the Bending Stiffness. 6.6.3 Influence of the Support Conditions. 6.6.4 Comparison of the Defined Cases with Experimental Results. 6.6.5 Measurement Data Adjustment for Exact Cable Force Determination. 6.7 Transfer Functions Analysis. 6.7.1 Mathematical Backgrounds. 6.7.2 Transfer Functions in the Vibration Analysis. 6.7.3 Applications (Examples). 6.8 Stochastic Subspace Identification. 6.8.1 Stochastic State-Space Models. 6.8.2 Stochastic System Identification. References. 7 OUTLOOK. 7.1 Decision Support Systems. 7.2 Sensor Technology and Sensor Networks. 7.2.1 State-of-the-Art Sensor Technology. 7.3 Research Gaps and Opportunities. 7.4 International Collaboration. 7.4.1 Collaboration Framework. 7.4.2 Activities. 8 EXAMPLES FOR APPLICATION. 8.1 Aitertal Bridge, Post-tensional T-beam (1956). 8.2 Donaustadt Bridge, Cable-Stayed Bridge in Steel (1996). 8.3 F9 Viaduct Donnergraben, Continuous Box Girder (1979). 8.4 Europa Bridge, Continuous Steel Box Girder (1961). 8.5 Gasthofalm Bridge, Composite Bridge (1979). 8.6 Kao Ping Hsi Bridge, Cable-Stayed Bridge (2000). 8.7 Inn Bridge Roppen, Concrete Bridge (1936). 8.8 Slope Bridge Saag, Bridge Rehabilitation (1998). 8.9 Flyover St Marx, Permanent Monitoring. 8.10 Mur Bridge in St Michael, Bridge Rehabilitation. 8.11 Rosen Bridge in Tulln, Concrete Cable-Stayed Bridge (1995). 8.12 VOEST Bridge, Steel Cable-Stayed Bridge (1966). 8.13 Taichung Bridge, Cable-Stayed Bridge. APPENDIX. Nomenclature. INDEX.
TL;DR: In this paper, a new adaptive tracking technique based on the least-squares estimation approach is proposed to identify the time-varying structural parameters, which is capable of tracking the abrupt changes of system parameters from which the event and severity of the structural damage may be detected.
Abstract: An important objective of health monitoring systems for civil infrastructures is to identify the state of the structure and to detect the damage when it occurs. System identification and damage detection, based on measured vibration data, have received considerable attention recently. Frequently, the damage of a structure may be reflected by a change of some parameters in structural elements, such as a degradation of the stiffness. Hence it is important to develop data analysis techniques that are capable of detecting the parametric changes of structural elements during a severe event, such as the earthquake. In this paper, we propose a new adaptive tracking technique, based on the least-squares estimation approach, to identify the time-varying structural parameters. In particular, the new technique proposed is capable of tracking the abrupt changes of system parameters from which the event and the severity of the structural damage may be detected. The proposed technique is applied to linear structures, including the Phase I ASCE structural health monitoring benchmark building, and a nonlinear elastic structure to demonstrate its performance and advantages. Simulation results demonstrate that the proposed technique is capable of tracking the parametric change of structures due to damages.
TL;DR: In this paper, the authors present a procedure based on principal component analysis which is able to perform detection, isolation and reconstruction of a faulty sensor, which is assessed using an experimental application.
Abstract: For a reliable on-line vibration monitoring of structures, it is necessary to have accurate sensor information. However, sensors may sometimes be faulty or may even become unavailable due to failure or maintenance activities. The problem of sensor validation is therefore a critical part of structural health monitoring. The objective of the present study is to present a procedure based on principal component analysis which is able to perform detection, isolation and reconstruction of a faulty sensor. Its efficiency is assessed using an experimental application.
01 Dec 2005
TL;DR: Wang et al. as discussed by the authors developed a bridge health monitoring system based on optical fiber sensing technology for tunnel structures and other infrastructure, and used it for post-earthquake evaluation of bridges.
Abstract: Foreword Preface Chapter I: Global perspectives on structural health monitoring of civil structures. Are civil structural engineers 'risk averse'? Can civionics help?, A.A. Mufti, B. Bakht, G. Tadros, A.T. Horosko, and G. Sparks Monitoring technologies for maintenance and management of urban highways in Japan, Y. Adachi The role of sensing and measurement in achieving FHWA's strategic vision for highway infrastructure, S.B.Chase Recent development of bridge health monitoring system in Korea, H.M. Koh, S. Kim, and J.F. Choo A strategy to implement structural health monitoring on bridges, C. Sikorsky Sensors - not just for research anymore, N.P. Vitillo Investigation of the dynamic properties of the Brooklyn Bridge, Q. Ye, G. Fanjiang, and B. Yanev Chapter II: Monitoring issues in ancient and modern structures. Distributed sensing technologies for monitoring frpstrengthened structures, Z.S. Wu and C.Q. Yang Problems and perspectives in monitoring of ancient masonry structures, A. De Stefano and R. Ceravolo Monitoring and response of CFRP prestressed concrete bridge, N.F. Grace Design of temporary and permanent arrays to assess dynamic parameters in historical and monumental buildings, P. Clemente and D. Rinaldis FRP-Strengthened structures: Monitoring issues from Quebec applications, P. Labossiere, P. Rochette, K.W. Neale, and M. Demers Structural and material monitoring of historical objects, M. Drdack Chapter III: Sensing of structural parameters and extreme events. Internal and external sensing for post-earthquake evaluation of bridges, M. Saud Saudi, R. Nelson, and P. Laplace Application of em stress sensors in large steel cables, M.L.Wang, G. Wang, and Y. Zhao Enhancing durability of structures by monitoring strain and cracking behavior, B. Hillemeier, H. Scheel, and W. Habel Development of an earthquake damage detection system for bridge structures, H. Kobayashi andS. Unjoh Determination of rebar forces based on the exterior crack opening displacement measurement of reinforced concrete, T. Matsumoto and M.N. Islam Monitoring system based on optical fiber sensing technology for tunnel structures and other infrastructure, K. Fujihashi, K. Kurihara, K. Hirayama, and S. Toyoda Development of FBG sensors for structural health monitoring in civil infrastructures, Z. Zhou and J. Ou Chapter IV: Smart sensors, imaging and NDT of civil structures. Monitoring of a smart concrete beam, Q.B. Li, L. Li, and F. Zhang Fiber optic nerve systems with optical correlation domain technique for smart structures and smart materials, K. Hotate Use of active sensors for health monitoring of transportation infrastructure, S. Nazarian Health monitoring of concrete structures using self-diagnosis materials, H. Inada, Y. Okuhara, and H. Kumagai Application of image analysis to steel structural engineering, K. Tateishi and T. Hanji Shape memory alloy based smart civil structures with self-sensing and repairing capabilities, H. Li, C. Mao, Z. Liu, and J. Ou Smart sensors and integrated SHM system for offshore structures, Z. Duan, J. Ou, Z. Zhou, and X. Zhao Chapter V: Sensor system design, data quality, processing, and interpretation. Design considerations for sensing systems to ensure data quality, R. Zhang and E. Aktan Practical implementations of intelligent monitoring systems in HIT, J.Ou Health monitoring, damage prognosis and service-life prediction - issues related to implementation, V.M. Karbhari Adaptive event detection for shm system monitoring, D.K. McNeill and L. Card A note on interpretation of shm data for bridges, B. Bakht Chapter VI: Sensor and instrumentation performance and reliability instrumentation performance during long-term bridge monitoring, I.N. Robertson, G.P. Johnson, and S. Wang Stability and reliability of fiber-optic measurement systems -
TL;DR: In this paper, a methodology for automatic damage identification and localization is presented, where the structure is assumed to be instrumented with an array of actuators and sensors to excite and record its dynamic response, including vibration and wave propagation effects.
Abstract: Development of efficient methodologies to determine the presence, location, and severity of hidden damage in critical structural components is an important task in the design and construction of structural health monitoring systems in aging as well as new structures. In this article, a methodology for automatic damage identification and localization is presented. The structure is assumed to be instrumented with an array of actuators and sensors to excite and record its dynamic response, including vibration and wave propagation effects. In the vibrational approach, the data consist of the modal response of the structure produced by the actuators while in the wave propagation approach, they are the broadband signals due to ultrasonic waves propagating in the structures. Both types of signals are affected by the presence of defects. The approximate location and severity of an unknown defect is determined using a damage correlation index calculated from the frequency response function (FRF) of the structure. ...
TL;DR: The use of modal information is discussed, as well as the direct use of forced and ambient vibrations for structural health monitoring in this paper, and different strategies can be deduced which depend on the type of measurement data (time/frequency domain) but also on the frequency spectrum.
Abstract: This paper gives an overview on the current status of vibration-based methods for Structural Health Monitoring. All these methods have in common that a structural change due to a damage results in a more or less pronounced change of the dynamic behavior. The use of modal information is discussed, as well as the direct use of forced and ambient vibrations. From this information, different strategies can be deduced which depend on the type of measurement data (time/frequency domain) but also on the frequency spectrum. The incorporation of actuation and sensing devices into the structure leads to modern concepts of Smart Structural Health Monitoring. Examples from civil and aerospace engineering show the applicability of these methods.
TL;DR: In this article, the performance of the MICA and MICA2 Mote is investigated through shaking table tests employing a two-storey steel structure, and its performance for wireless measurement and specific risk monitoring applications, such as damage detection in the structure, is presented.
Abstract: Buildings are subjected to natural hazards, such as earthquakes and winds, and artificial hazards, such as fires and crimes, during their long-term use. Risk monitoring using a network of wireless sensors is one of the most promising emerging technologies for mitigation of these hazards. Recently, a smart sensor based on the Berkeley Mote platform was introduced, and an application to the next generation of structural health monitoring and control was proposed. The Mote has on-board microprocessor and ready-made wireless communication capabilities. In this paper, the performance of the MICA and MICA2 Mote is investigated through shaking table tests employing a two-storey steel structure. The acceleration sensor is tested, and its performance for wireless measurement and specific risk monitoring applications, such as damage detection in the structure, is presented. The MICA2 Mote is shown to have sufficient performance for the intended purpose. Copyright © 2005 John Wiley & Sons, Ltd.
TL;DR: A hybrid piezoelectric/fiber optic diagnostic system has been developed for quick non-destructive evaluation and long term health monitoring of aerospace vehicles and structures as discussed by the authors, which consists of three major parts: a diagnostic layer with a network of pieziolectric elements and fiber gratings to offer a simple and efficient way to integrate a large network of transducers onto a structure; diagnostic hardware consisting of an arbitrary waveform generator and a high speed fiber grating demodulation unit together with a high-speed data acquisition card to provide actuation input, data collection,
Abstract: A hybrid piezoelectric/fiber optic diagnostic system has been developed for quick non-destructive evaluation and long term health monitoring of aerospace vehicles and structures. The hybrid diagnostic system uses piezoelectric actuators to input a controlled excitation to the structure and fiber optic sensors to capture the corresponding structural response. The system consists of three major parts: a diagnostic layer with a network of piezoelectric elements and fiber gratings to offer a simple and efficient way to integrate a large network of transducers onto a structure; diagnostic hardware consisting of an arbitrary waveform generator and a high speed fiber grating demodulation unit together with a high speed data acquisition card to provide actuation input, data collection, and information processing; and diagnostic software to determine the condition of the structure. This paper presents key development issues related to the manufacturing of the hybrid piezoelectric/fiber optic diagnostic layer and integration of a highly portable diagnostic hardware. Validation and proof testing of this integrated diagnostic system are also presented.
TL;DR: A method to improve pattern recognition and damage detection by supplementing Intelligent Structural Health Monitoring with fuzzy sets is introduced, using data simulated from finite element analysis of a prestressed concrete bridge without a priori known levels of damage.
TL;DR: In this article, an aluminum plate monitored by piezoelectric active sensors is used to validate the performance of the prototype unit in structural health monitoring applications, and a novel damage detection methodology is proposed that uses the characteristic equation roots obtained from an autoregressive with exogenous input time-series model.
Abstract: SUMMARY The recent years have witnessed an increasing interest in using wireless structural monitoring as a low-cost alternative to tethered monitoring systems. Previous work considered wireless sensors strictly as passive elements in the monitoring system, responsible only for collection of response measurements. This paper explores expansion of the wireless structural monitoring paradigm by including actuation capabilities in the design of a wireless active sensing unit. To validate the performance of the prototype unit in structural health monitoring applications, an aluminum plate monitored by piezoelectric active sensors is used. Piezoelectric actuators mounted to the surface of the plate are commanded by the wireless active sensing unit to excite and record the element. System identification models are then used to model the linear relationship between the input excitation and the corresponding plate response. A novel damage detection methodology is proposed that uses the characteristic equation roots obtained from an autoregressive with exogenous input time-series model. Complex roots (poles) of the model’s characteristic equation are sensitive to structural damage causing a change in their location on the complex plane. Using the mean value of pole clusters, the migration of model poles are shown to be well correlated to the severity of crack damage intentionally introduced in the plate. Copyright # 2005 John Wiley & Sons, Ltd.
TL;DR: In this paper, a damage identification procedure based on dynamic response for fiber reinforced polymer (FRP) sandwich composites is evaluated, in which the damage magnitude is quantified based on the relationship between the changes of mechanical properties and the related changes of dynamic responses (i.e., the curvature mode shapes in this study).
TL;DR: This paper proposes to use statistical pattern recognition methods to address damage classification and data mining issues associated with the examination of large numbers of impedance signals for health monitoring applications to develop a robust damage classifier.
08 Mar 2005
TL;DR: This paper proposes a, WSN based, novel framework that triggers smart events from sensor data that improves the lifespan of the network and simplifies data management.
Abstract: Wireless sensor network (WSN) gives the characteristics of an effective, feasible and fairly reliable monitoring system which shows promise for structural health monitoring (SHM) applications. Monitoring of civil structures generates a large amount of sensor data that is used for structural anomaly detection. Efficiently dealing with this large amount of data in a resource-constrained WSN is a challenge. This paper proposes a, WSN based, novel framework that triggers smart events from sensor data. These events are useful for both intelligent data recording and video camera control. The operation of this framework consists of active & passive sensing modes. In passive mode, selected nodes can intelligently interpret local sensor data to trigger appropriate events. In active mode, most of the sensing nodes perform high frequency sampling and record useful data. Unnecessary data is suppressed which improves the lifespan of the network and simplifies data management.
TL;DR: In this paper, a guided Lamb wave-based damage identification scheme and an online structural health monitoring (online-SHM) system with an integrated piezoelectric actuator-sensor network are developed.
Abstract: A guided Lamb wave-based damage identification scheme and an online structural health monitoring (online-SHM) system with an integrated piezoelectric actuator-sensor network are developed. The proposed methodology is applied to the quantitative diagnosis of through-hole-type defect in the CF-EP quasi-isotropic laminate with the aid of an artificial neural network algorithm. For this purpose, a variety of composite laminates with stochastic damages are considered, and the corresponding three-dimensional dynamic FEM simulations are conducted. To describe a Lamb wave excited by the PZT actuator, models for both the piezoelectric actuator and sensor coupled with the composite laminates are established. A wavelet transform-based signal processing package (SPP) is devised to purify the acquired wave signals, and further extract characteristics from the energy spectra of Lamb waves over the time-scale domain. A concept of ‘digital damage fingerprints’ is introduced, with which a damage parameters database (DPD) ...
TL;DR: In this paper, the authors describe the principles involved in serial multiplexing of two kinds of optical fibers, namely long gage and acoustic sensors, which offer promise in structural health monitoring of large civil structural systems.
Abstract: Structural health monitoring with optical fibers provides practical sensing capabilities in many applications including in aeronautics and mechanical structures. A variety of optical fiber sensors have been used including Bragg gratings, intensity or amplitude sensors, and Fabry–Perot ones. Civil structures pose further challenges in monitoring mainly due to their large dimensions, diversity as well as heterogeneity of materials involved, and hostile construction environment. Monitoring of strains, deformations, and deflections provides clues essential for evaluation of design parameters and behavior under service loads. Long gage distributed or multiplexed sensors are excellent candidates for such applications. On the other hand, detection of structural damage and anomalies such as cracking in concrete, splintering of fibers in composites, and fracturing of welds and connections are best accomplished by acoustic sensors. This paper describes principles involved in serial multiplexing of two kinds of optical fibers, namely long gage and acoustic sensors. Both sensor types offer promise in structural health monitoring of large civil structural systems. Representative examples are introduced and described in detail.
TL;DR: In this article, a multivariate time delay embedding is used to reconstruct the dynamical attractor of a composite beam, bolted at either end to steel plates to detect both the presence and magnitude of damage to the connection.
TL;DR: In this paper, a typical monolithic glass fibre reinforced polymer composite T-joint is modeled and tested for structural health monitoring (SHM) and the performance of embedded optical fiber Bragg sensors in such joints has been shown to be satisfactory and the effects of artificially induced disbonds on the strain distribution have been determined via finite element modelling and have been experimentally verified.