Tesi: "Structural analysis (Engineering) Structural health monitoring"

1

Lajnef, Nizar. "Self-powered sensing in structural health and usage monitoring". Diss., Connect to online resource - MSU authorized users, 2008.

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Thesis (Ph.D.)--Michigan State University. Dept. of Civil and Environmental Engineering, 2008.
Title from PDF t.p. (viewed on July 2, 2009) Includes bibliographical references (p. 127-133). Also issued in print.

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2

Singh-Levett, Ishan. "Real-time integral based structural health monitoring". Thesis, University of Canterbury. Mechanical Engineering, 2006. http://hdl.handle.net/10092/1171.

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Structural Health Monitoring (SHM) is a means of identifying damage from the structural response to environmental loads. Real-time SHM offers rapid assessment of structural safety by owners and civil defense authorities enabling more optimal response to major events. This research presents an real-time, convex, integral-based SHM methods for seismic events that use only acceleration measurements and infrequently measured displacements, and a non-linear baseline model including hysteretic dynamics and permanent deformation. The method thus identifies time-varying pre-yield and post-yield stiffness, elastic and plastic components of displacement and final residual displacement. For a linear baseline model it identifies only timevarying stiffness. Thus, the algorithm identifies all key measures of structural damage affecting the immediate safety or use of the structure, and the long-term cost of repair and retrofit. The algorithm is tested with simulated and measured El Centro earthquake response data from a four storey non-linear steel frame structure and simulated data from a two storey non-linear hybrid rocking structure. The steel frame and rocking structures exhibit contrasting dynamic response and are thus used to highlight the impact of baseline model selection in SHM. In simulation, the algorithm identifies stiffness to within 3.5% with 90% confidence, and permanent displacement to within 7.5% with 90% confidence. Using measured data for the frame structure, the algorithm identifies final residual deformation to within 1.5% and identifies realistic stiffness values in comparison to values predicted from pushover analysis. For the rocking structure, the algorithm accurately identifies the different regimes of motion and linear stiffness comparable to estimates from previous research. Overall, the method is seen to be accurate, effective and realtime capable, with the non-linear baseline model more accurately identifying damage in both of the disparate structures examined.

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3

Silva, Muñoz Rodrigo. "Structural Health Monitoring Using Embedded Fiber Optic Strain Sensors". Fogler Library, University of Maine, 2008. http://www.library.umaine.edu/theses/pdf/SilvaMunozR2008.pdf.

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4

Shinde, Abhijeet Dipak. "A wavelet packet based sifting process and its application for structural health monitoring". Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0824104-222824/.

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Thesis (M.S.)--Worcester Polytechnic Institute.
Keywords: Wooden Structure; Damage Detection; Structural Health Monitoring; Instantaneous Modal Parameters; Wavelet Analysis; Time Varying Systems; Sifting Process. Includes bibliographical references (p. 77-82).

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5

Hera, Adriana. "Instantaneous modal parameters and their applications to structural health monitoring". Link to electronic dissertation, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-121905-163738/.

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Dissertation (Ph.D..) -- Worcester Polytechnic Institute.
Keywords: structural health monitoring; wavelet transform; time varying vibration modes; instantaneous modal parameters. Includes bibliographical references (p.181-186).

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6

Lu, Yinghui. "Analysis and modeling of diffuse ultrasonic signals for structural health monitoring". Diss., Available online, Georgia Institute of Technology, 2007, 2007. http://etd.gatech.edu/theses/available/etd-07052007-225427/.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008.
Durgin, Gregory, Committee Member ; Vachtsevanos, George, Committee Member ; Michaels, Thomas, Committee Member ; Michaels, Jennifer, Committee Chair ; Jacobs, Laurence, Committee Member.

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7

Akin, Tugba. "Structural Monitoring And Analysis Of Steel Truss Railroad Bridges". Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614825/index.pdf.

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Railroad bridges are the most important connection parts of railroad networks. These bridges are exposed to heavier train loads compared to highway bridges as well as various detrimental ambient conditions during their life span. The railroad bridges in Turkey are mostly constructed during the late Ottoman and first periods of the Turkish Republic
therefore, they are generally close to about 100 years of age
their inspection and maintenance works are essential. Structural health monitoring (SHM) techniques are widely used around the world in order to increase the effectiveness of the inspection and maintenance works and also evaluate structural reliability. Application of SHM methods on railway bridges by static and dynamic measurements over short and long durations give important structural information about bridge members&rsquo
load level and overall bridge structure in terms of vibration frequencies, deflections, etc. Structural Reliability analysis provides further information about the safety of a structural system and becomes even more efficient when combined with the SHM studies. In this study, computer modeling and SHM techniques are used for identifying structural condition of a steel truss railroad bridge in Usak, Turkey, which is composed of six spans with 30 m length each. The first two spans of the bridge were rebuilt about 50 years ago, which had construction plans and are selected as pilot case for SHM and evaluation studies in this thesis. Natural frequencies are obtained by using 4 accelerometers and a dynamic data acquisition system (DAS). Furthermore, mid span vertical deflection member strains and bridge accelerations are obtained using a DAS permanently left on site and then compared with the computer model analyses results. SHM system is programmed for triggering by the rail load sensors developed at METU and an LVDT to collect mid span deflection high speed data from all sensors during train passage. The DAS is also programmed to collect slow speed data (once at every 15 minutes) for determination of average ambient conditions such as temperature and humidity and all bridge sensors during long term monitoring. Structural capacity and reliability indices for stress levels of bridge members are determined for the measured and simulated train loads to determine structural condition of bridge members and connections. Earthquake analyses and design checks for bridge members are also conducted within the scope of this study.

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8

Ojeda, Alejandro P. "MATLAB implementation of an operational modal analysis technique for vibration-based structural health monitoring". Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/74412.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 72-73).
Vibration-based structural health monitoring (SHM) has become an attractive solution for the global monitoring and evaluation of damage in structures. Numerous damage detection schemes used in vibration-based SHM require knowledge of the modal properties of the structure under evaluation in its current state. The technique of operational modal analysis allows for these modal properties to be obtained by using the structure's dynamic response to ambient excitation. Using MATLAB, a type of operational modal analysis technique called time domain decomposition (TDD) based on [15] was implemented. The MATLAB TDD implementation was applied to the dynamic responses from two finite element models of simply-supported beams and their modal frequencies and shapes were extracted. The first three modal frequencies were obtained with less than 6 percent error from the actual values and the fundamental mode shape values obtained contained negligible deviations from the actual mode shape values. However, the higher order mode shapes obtained were more inaccurate, suggesting limitations to the current MATLAB TDD implementation. Lastly, changes to the moment of inertia of the simply-supported beam models were used to simulate damage in the finite element models and cause their fundamental mode frequency to change. The MATLAB TDD implementation was able to distinguish changes in the fundamental frequency of both finite element models with a resolution of approximately 1.7 radians per second (7.2 percent).
by Alejandro P. Ojeda.
M.Eng.

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9

Essegbey, John W. "Piece-wise Linear Approximation for Improved Detection in Structural Health Monitoring". University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342729241.

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10

Terrell, Thomas. "Structural health monitoring for damage detection using wired and wireless sensor clusters". Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5055.

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Sensing and analysis of a structure for the purpose of detecting, tracking, and evaluating damage and deterioration, during both regular operation and extreme events, is referred to as Structural Health Monitoring (SHM). SHM is a multi-disciplinary field, with a complete system incorporating sensing technology, hardware, signal processing, networking, data analysis, and management for interpretation and decision making. However, many of these processes and subsequent integration into a practical SHM framework are in need of development. In this study, various components of an SHM system will be investigated. A particular focus is paid to the investigation of a previously developed damage detection methodology for global condition assessment of a laboratory structure with a decking system. First, a review of some of the current SHM applications, which relate to a current UCF Structures SHM study monitoring a full-scale movable bridge, will be presented in conjunction with a summary of the critical components for that project. Studies for structural condition assessment of a 4-span bridge-type steel structure using the SHM data collected from laboratory based experiments will then be presented. For this purpose, a time series analysis method using ARX models (Auto-Regressive models with eXogeneous input) for damage detection with free response vibration data will be expanded upon using both wired and wireless acceleration data. Analysis using wireless accelerometers will implement a sensor roaming technique to maintain a dense sensor field, yet require fewer sensors. Using both data types, this ARX based time series analysis method was shown to be effective for damage detection and localization for this relatively complex laboratory structure. Finally, application of the proposed methodologies on a real-life structure will be discussed, along with conclusions and recommendations for future work.
ID: 029810361; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (M.S.C.E.)--University of Central Florida, 2011.; Includes bibliographical references (p. 102-114).
M.S.C.E.
Masters
Civil, Environmental and Construction Engineering
Engineering and Computer Science
Civil Engineering

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11

Weston, Daniel Frederick. "Existing and future plans for the structural health monitoring of the Indian River Inlet Bridge". Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 248 p, 2006. http://proquest.umi.com/pqdweb?did=1163250401&sid=1&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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12

Gökçe, Hasan Burak. "Structural identification through monitoring, modeling and predictive analysis under uncertainty". Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5222.

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Bridges are critical components of highway networks, which provide mobility and economical vitality to a nation. Ensuring the safety and regular operation as well as accurate structural assessment of bridges is essential. Structural Identification (St-Id) can be utilized for better assessment of structures by integrating experimental and analytical technologies in support of decision-making. St-Id is defined as creating parametric or nonparametric models to characterize structural behavior based on structural health monitoring (SHM) data. In a recent study by the ASCE St-Id Committee, St-Id framework is given in six steps, including modeling, experimentation and ultimately decision making for estimating the performance and vulnerability of structural systems reliably through the improved simulations using monitoring data. In some St-Id applications, there can be challenges and considerations related to this six-step framework. For instance not all of the steps can be employed; thereby a subset of the six steps can be adapted for some cases based on the various limitations. In addition, each step has its own characteristics, challenges, and uncertainties due to the considerations such as time varying nature of civil structures, modeling and measurements. It is often discussed that even a calibrated model has limitations in fully representing an existing structure; therefore, a family of models may be well suited to represent the structure's response and performance in a probabilistic manner. The principle objective of this dissertation is to investigate nonparametric and parametric St-Id approaches by considering uncertainties coming from different sources to better assess the structural condition for decision making. In the first part of the dissertation, a nonparametric St-Id approach is employed without the use of an analytical model.; It is recommended that a family-of-models approach is suitable for structures that have less redundancy, high operational importance, are deteriorated, and are performing under close capacity and demand levels.; The new methodology, which is successfully demonstrated on both lab and real-life structures, can identify and locate the damage by tracking correlation coefficients between strain time histories and can locate the damage from the generated correlation matrices of different strain time histories. This methodology is found to be load independent, computationally efficient, easy to use, especially for handling large amounts of monitoring data, and capable of identifying the effectiveness of the maintenance. In the second part, a parametric St-Id approach is introduced by developing a family of models using Monte Carlo simulations and finite element analyses to explore the uncertainty effects on performance predictions in terms of load rating and structural reliability. The family of models is developed from a parent model, which is calibrated using monitoring data. In this dissertation, the calibration is carried out using artificial neural networks (ANNs) and the approach and results are demonstrated on a laboratory structure and a real-life movable bridge, where predictive analyses are carried out for performance decrease due to deterioration, damage, and traffic increase over time. In addition, a long-span bridge is investigated using the same approach when the bridge is retrofitted. The family of models for these structures is employed to determine the component and system reliability, as well as the load rating, with a distribution that incorporates various uncertainties that were defined and characterized. It is observed that the uncertainties play a considerable role even when compared to calibrated model-based predictions for reliability and load rating, especially when the structure is complex, deteriorated and aged, and subjected to variable environmental and operational conditions.
ID: 031001436; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Adviser: F. Necati ?çatba?ƒ.; Title from PDF title page (viewed June 24, 2013).; Thesis (Ph.D.)--University of Central Florida, 2012.; Includes bibliographical references (p. 173-187).
Ph.D.
Doctorate
Civil, Environmental, and Construction Engineering
Engineering and Computer Science
Civil Engineering

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13

Pertsch, Alexander Thomas. "An intelligent stand-alone ultrasonic device for monitoring local damage growth in civil structures". Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31716.

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Thesis (M. S.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Jacobs, Laurence J.; Committee Co-Chair: Wang, Yang; Committee Member: Kim, Jin-Yeon. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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14

Cobb, Adam. "A state estimation framework for ultrasonic structural health monitoring of fastener hole fatigue cracks". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22537.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Michaels, Jennifer; Committee Member: Habetler, Thomas; Committee Member: Jacobs, Laurence; Committee Member: Michaels, Thomas; Committee Member: Vachtsevanos, George.

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15

Lantz, Gabriel Antoine. "Crack detection using a passive wireless strain sensor". Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/45773.

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Nearly one third of the 604,426 bridges in the United-States are either structurally deficient or functionally obsolete. Monitoring these bridges is essential to avoid catastrophic accidents. In steel bridges fatigue induced crack/rupture, which is one of the most common modes of failure, can be avoided if the crack is detected at the early stages of its formation. Cracks usually originate at stress concentration areas but their precise origin is random. Such strain concentration can be monitored with traditional strain gages, but their installation requires lengthy wires and equipment, which are expensive and labor intensive. Therefore wireless sensors are being developed to cope with these problems. In this work, a passive wireless strain sensor based on RFID technology is described. The sensor is a patch antenna that resonates at a certain frequency, which shifts in presence of strain. The relation between the resonance frequency and the strain is approximately linear. The slope of the relation is called sensitivity. The behavior of the sensor's sensitivity is studied using experimental work and simulations that couple electromagnetism and mechanics. The sensitivity measured in experiments and in simulations in presence of uniform strain is different. This difference is lower for the sensitivity in presence of a crack, probably due to a parameter variation that is currently not accurately modeled in the simulations.

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Chilelli, Sean Kelty. "Structural health monitoring with fiber Bragg grating sensors embedded into metal through ultrasonic additive manufacturing". The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563529169604482.

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17

Liu, Albert Darien. "THE EFFECT OF SENSOR MASS, SENSOR LOCATION, AND DELAMINATION LOCATION OF DIFFERENT COMPOSITE STRUCTURES UNDER DYNAMIC LOADING". DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/917.

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This study investigated the effect of sensor mass, sensor location, and delamination location of different composite structures under dynamic loading. The study pertains to research of the use of accelerometers and dynamic response as a cost-effective and reliable method of structural health monitoring in composite structures. The composite structures in this research included carbon fiber plates, carbon fiber-foam sandwich panels, and carbon-fiber honeycomb sandwich panels. The composite structures were manufactured with the use of a Tetrahedron MTP-8 heat press. All work was conducted in the Cal Poly Aerospace Structures/Composites Laboratory. Initial delaminations were placed at several locations along the specimen, including the bending mode node line locations. The free vibration of the composite structure was forced through a harmonic horizontal vibration test using an Unholtz-Dickie shake system. A sinusoidal sweep input was considered for the test. The dynamic response of the composite test specimens were measured using piezoelectric accelerometers. Measurements were taken along horizontal and vertical locations on the surfaces of the composite structures. Square inch grids were marked on the surfaces to create a meshed grid system. Accelerometer measurements were taken at the center of the grids. The VIP Sensors 1011A piezoelectric accelerometer was used to measure vibration response. The measurements were then compared to response measurements taken from a PCB Piezotronics 353B04 single access accelerometer to determine the effects of sensor mass. Deviations in bending mode natural frequency and differences in mode shape amplitude became the criteria for evaluating the effect of sensor mass, sensor location, and delamination location. Changes in damping of the time response were also studied. The experimental results were compared to numerical models created using a finite element method. The experimental results and numerical values were shown to be in good agreement. The sensor mass greatly affected the accuracy and precision of vibration response measurements in the composites structures. The smaller weight and area of the VIP accelerometer helped to minimize the decrease in accuracy and precision due to sensor mass. The effect of sensor location was found to be coupled with the effect of sensor mass and the bending mode shape. The sensor location did not affect the vibration response measurements when the sensor mass was minimized. Off-center horizontal sensor placement showed the possibility of measuring vibration torsion modes. The effect of delamination changed the bending mode shape of the composite structure, which corresponded to a change in natural frequency. The greatest effect of the delamination was seen at the bending mode node lines, where the bending mode shape was most significantly affected. The effect of delamination was also dependent on the location of the delamination and the composite structure type. The results of this study provided considerations for future research of an active structural health monitoring system of composite structures using dynamic response measurements. The considerations included sensor mass reduction, sensor placement at constraints and bond areas and the presence of damping material.

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Masango, Thubalakhe Patrick. "Condition monitoring of a wing structure for an unmanned aerial vehicle (UAV)". Thesis, Cape Peninsula University of Technology, 2015. http://hdl.handle.net/20.500.11838/2384.

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Thesis (MTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2015.
Currently non-destructive testing techniques for composite aircraft structures are disadvantaged when compared to online Structural Health Monitoring (SHM) systems that monitor the structure while in-service and give real time data. The present research work looks at developing a protocol for online structural health monitoring of a UAV wing structure using PVDF film sensors, especially including the monitoring of structural changes caused by defects. Different types of SHM techniques were studied in relation to carbon fibre composites. Laminate composite make-up and manufacturing process was investigated and vacuum infusion process was used to manufacture the samples that resemble the Guardian II wing structure, then the three-point bending test was used to determine the material properties. Digital Shearography was employed as a stationery non-destructive technique to determine the sensor to structure attachment, type and position of defects that affect the state of performance. Finite Element Analysis (FEA) was done using ANSYS Workbench which served as a modelling tool using a drawing imported from Solid-works. Experimental investigation was done using PVDF sensor embedded on the surface of the sample in a cantilever setup and a vertical Vernier scale to measure the deflection due to impact and vibration loading. A Fluke-View oscilloscope was used as a data logger when the measurement of the output voltage and the natural frequency were recorded. The techniques of using FEA and experimental investigation were then compared. The findings of this study showed that the PVDF sensor is suitable for condition monitoring of a UAV wing structure.

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Norouzi, Mehdi. "Tracking Long-Term Changes in Bridges using Multivariate Correlational Data Analysis". University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1416570591.

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20

Facciotto, Nicolò. "Source differentiation and identification of acoustic emission signals by time-frequency analysis". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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In the context of Structural Health Monitoring, the Acoustic Emission Technique may be efficiently used to detect damage on aerospace structures. This study focuses on the development of a source identification algorithm to distinguish different acoustic emission events in aluminium sheets, which have been collected during experimental tests. The future goal will be the design of a Holistic Structural Health Monitoring System which will make the complete aircraft an intelligent structure able to diagnose its own structural damage based on the condition of the structure while maintaining safety.

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21

O'Malley, Curtis John. "Experimental testing, analysis, and strengthening of reinforced concrete pier caps by exterior post tensioning". Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41076.

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Condition assessment of existing concrete bridge pier caps using the general shear provisions of the AASHTO LRFD Bridge Design Specification has caused the Georgia Department of Transportation (GDOT) to post a large number of bridges in the State of Georgia. Posting of bridges disrupts the free flow of goods within the region served by the bridge and has a negative economic impact. To prevent structural deterioration, diagonal cracking or failure of concrete pier caps in shear, the GDOT employs an in-situ strengthening technique that utilizes an external vertical post-tensioning system. However, the fundamental mechanics of this system and its effectiveness under service load have not been examined previously. This research examines the behavior of reinforced concrete pier caps that utilize the above strengthening system in a combined analytical and experimental program. In the experimental part of the study, two groups of full-scale reinforced concrete deep beam specimens were tested. The first group consisted of six deep beams with shear span/depth ratios of approximately 1.0, which is typical of bridge pier caps; of these six, two included the external post-tensioning system. In the second group, nine deep beam specimens that included a segment of the column representing the pier were tested; four of those tests included the external post-tensioning system. The tests revealed that the shear capacity computed using the AASHTO LRFD Bridge Design Specifications provided a conservative estimate of the specimen capacity in all but one case when compared to the experimental results. However, the AASHTO strut and tie provisions were found to provide a much closer assessment of the load carrying mechanism in the pier cap than the general shear provisions, in that they were able to predict the load at which yielding of the tension reinforcement occurred as well as the angle of the compression strut. The presence of the column segment in the second group had a significant impact on the failure mechanism developed in the specimen near ultimate load. The stress concentration at the reentrant corner between the pier cap and column interface served as an attractor for the formation of diagonal shear cracks, a mechanism not observed in previous deep beam tests in shear. The research has led to recommendations for improving the design of pier caps and the external post-tensioning system, where required, based on mechanics which are consistent with the results of the experimental program.

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Sharma, Siddharth. "Application of Support Vector Machines for Damage Detection in Structures". Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/8.

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Support vector machines (SVMs) are a set of supervised learning methods that have recently been applied for structural damage detection due to their ability to form an accurate boundary from a small amount of training data. During training, they require data from the undamaged and damaged structure. The unavailability of data from the damaged structure is a major challenge in such methods due to the irreversibility of damage. Recent methods create data for the damaged structure from finite element models. In this thesis we propose a new method to derive the dataset representing the damage structure from the dataset measured on the undamaged structure without using a detailed structural finite element model. The basic idea is to reduce the values of a copy of the data from the undamaged structure to create the data representing the damaged structure. The performance of the method in the presence of measurement noise, ambient base excitation, wind loading is investigated. We find that SVMs can be used to detect small amounts of damage in the structure in the presence of noise. The ability of the method to detect damage at different locations in a structure and the effect of measurement location on the sensitivity of the method has been investigated. An online structural health monitoring method has also been proposed to use the SVM boundary, trained on data measured from the damaged structure, as an indicator of the structural health condition.

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Wang, Naiyu. "Reliability-based condition assessment of existing highway bridges". Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34835.

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Condition assessment and safety verification of existing bridges and decisions as to whether bridge posting is required are addressed through analysis, load testing, or a combination of methods. Bridge rating through structural analysis is by far the most common procedure for rating existing bridges. The American Association of State Highway and Transportation Officials (AASHTO) Manual for Bridge Evaluation (MBE), First Edition permits bridge capacity ratings to be determined through allowable stress rating (ASR), load factor rating (LFR) or load and resistance factor rating (LRFR); the latter method is keyed to the AASHTO LRFD Bridge Design Specifications, which is reliability-based and has been required for the design of new bridges built with federal findings since October, 2007. A survey of current bridge rating practices in the United States has revealed that these three methods may lead to different ratings and posting limits for the same bridge, a situation that carries serious implications with regard to the safety of the public and the economic well-being of communities that may be affected by bridge postings or closures. To address this issue, a research program has been conducted with the overall objective of providing recommendations for improving the process by which the condition of existing bridge structures is assessed. This research required a coordinated program of load testing and finite element analysis of selected bridges in the State of Georgia to gain perspectives on the behavior of older bridges under various load conditions. Structural system reliability assessments of these bridges were conducted and bridge fragilities were developed for purposes of comparison with component reliability benchmarks for new bridges. A reliability-based bridge rating framework was developed, along with a series of recommended improvements to the current bridge rating methods, which facilitate the incorporation of various in situ conditions of existing bridges into the bridge rating process at both component and system levels. This framework permits bridge ratings to be conducted at three levels of increasing complexity to achieve the performance objectives, expressed in the terms of reliability, that are embedded in the LRFR option of the AASHTO Manual of Bridge Evaluation. This research was sponsored by the Georgia Department of Transportation, and has led to a set of Recommended Guidelines for Condition Assessment and Evaluation of Existing Bridges in Georgia.

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German, Stephanie Ann. "Automated damage assessment of reinforced concrete columns for post-earthquake evaluations". Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47686.

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An automated method in damage state assessment of reinforced concrete columns for the purpose of establishing a rapid and quantitative post-earthquake safety and structural evaluation procedure is proposed. Several techniques from the fields of computer vision and image processing are employed in order to develop a set of methods capable of automatically detecting spalled regions on the surface of reinforced concrete columns as well as the properties of cracks and spalled regions on these surfaces. The resulting properties of the observed visible damage on the reinforced concrete column surfaces are then utilized to automatically estimate the existing condition and safety of the column. The damage state is quantified according to the maximum drift capacity of the column. The methods proposed in this research were implemented in a Microsoft Visual Studio .NET environment, and tested on real images of damaged columns. The test results indicated that the methods could automatically detect spalled regions and retrieve the properties of spalling and cracks on reinforced concrete column surfaces in images or video frames, and further, that this retrieved information could be accurately translate to a meaningful assessment of the column's existing damage state in the form of the maximum drift capacity.

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Veta, Jacob E. "Analysis and Development of a Lower Extremity Osteological Monitoring Tool Based on Vibration Data". Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595879294258019.

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Levine, Ross M. "Ultrasonic guided wave imaging via sparse reconstruction". Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51829.

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Structural health monitoring (SHM) is concerned with the continuous, long-term assessment of structural integrity. One commonly investigated SHM technique uses guided ultrasonic waves, which travel through the structure and interact with damage. Measured signals are then analyzed in software for detection, estimation, and characterization of damage. One common configuration for such a system uses a spatially-distributed array of fixed piezoelectric transducers, which is inexpensive and can cover large areas. Typically, one or more sets of prerecorded baseline signals are measured when the structure is in a known state, with imaging methods operating on differences between follow-up measurements and these baselines. Presented here is a new class of SHM spatially-distributed array algorithms that rely on sparse reconstruction. For this problem, damage over a region of interest (ROI) is considered to be sparse. Two different techniques are demonstrated here. The first, which relies on sparse reconstruction, uses an a priori assumption of scattering behavior to generate a redundant dictionary where each column corresponds to a pixel in the ROI. The second method extends this concept by using multidimensional models for each pixel, with each pixel corresponding to a "block" in the dictionary matrix; this method does not require advance knowledge of scattering behavior. Analysis and experimental results presented demonstrate the validity of the sparsity assumption. Experiments show that images generated with sparse methods are superior to those created with delay-and-sum methods; the techniques here are shown to be tolerant of propagation model mismatch. The block-sparse method described here also allows the extraction of scattering patterns, which can be used for damage characterization.

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Brooker, Caden B. "Field Experimentation and Finite Element Analysis of Prominent Drive-by Bridge Inspection Techniques". Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1617056113435238.

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Brigman, Nicholas (Nicholas Allen). "Structural health monitoring in commercial aviation". Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/73846.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 87-90).
The number of aging commercial aircraft in service is steadily increasing as airlines continue to extend the life of their aircraft. Aging aircraft are more susceptible to fatigue and corrosion and require more frequent and intensive inspections and maintenance, which is a financial drain on operators. One way to improve the economics and safety of commercial aircraft is through implementation of a structural health monitoring (SHM) system. An ideal SHM would be able to give be capable of indicating damage type, location, severity, and estimate the remaining life of the structure while the structure is in use. This paper is an overview of how SHM can be applied in commercial aviation including discussion of requirements, implementation, challenges, and introducing several possible SHM systems. The SHM systems introduced in this paper are: vibration based monitoring, fiber optic sensors, and high frequency wave propagation techniques including acoustic emission, ultrasonic, Lamb waves, piezoelectric and MEMS actuator/sensors. The limitations and challenges inhibiting introduction of SHM to industry and recommendations for the future are also discussed.
by Nicholas Brigman.
M.Eng.

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29

Kolli, Phaneendra K. "Wireless Sensor Network for Structural Health Monitoring". Youngstown State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1274304285.

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30

Jesus, André H. "Modular Bayesian uncertainty assessment for structural health monitoring". Thesis, University of Warwick, 2018. http://wrap.warwick.ac.uk/109522/.

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Civil infrastructure are critical elements to a society’s welfare and economic thriving. Understanding their behaviour and monitoring their serviceability are relevant challenges of Structural Health Monitoring (SHM). Despite the impressive improvement of miniaturisation, standardisation and diversity of monitoring systems, the ability to interpret data has registered a much slower progression across years. The underlying causes for such disparity are the overall complexity of the proposed challenge, and the inherent errors and lack of information associated with it. Overall, it is necessary to appropriately quantify the uncertainties which undermine the SHM concept. This thesis proposes an enhanced modular Bayesian framework (MBA) for structural identification (st-id) and measurement system design (MSD). The framework is hybrid, in the sense that it uses a physics-based model, and Gaussian processes (mrGp) which are trained against data, for uncertainty quantification. The mrGp act as emulators of the model response surface and its model discrepancy, also quantifying observation error, parametric and interpolation uncertainty. Finally, this framework has been enhanced with the Metropolis–Hastings for multiple parameters st-id. In contrast to other probabilistic frameworks, the MBA allows to estimate structural parameters (which reflect a performance of interest) consistently with their physical interpretation, while highlighting patterns of a model’s discrepancy. The MBA performance can be substantially improved by considering multiple responses which are sensitive to the structural parameters. An extension of the MBA for MSD has been validated on a reduced-scale aluminium bridge subject to thermal expansion (supported at one end with springs and instrumented with strain gauges and thermocouples). A finite element (FE) model of the structure was used to obtain a semi-optimal sensor configuration for stid. Results indicate that 1) measuring responses which are sensitive to the structural parameters and are more directly related to model discrepancy, provide the best results for st-id; 2) prior knowledge of the model discrepancy is essential to capture the latter type of responses. Subsequently, an extension of the MBA for st-id was also applied for identification of the springs stiffness, and results indicate relative errors five times less than other state of the art Bayesian/deterministic methodologies. Finally, a first application to field data was performed, to calibrate a detailed FE model of the Tamar suspension bridge using long-term monitored data. Measurements of temperature, traffic, mid-span displacement and natural frequencies of the bridge, were used to identify the bridge’s main/stay cables initial strain and friction of its bearings. Validation of results suggests that the identified parameters agree more closely with the true structural behaviour of the bridge, with an error that is several orders of magnitude smaller than other probabilistic st-id approaches. Additionally, the MBA allowed to predicted model discrepancy functions to assess the predictive ability of the Tamar bridge FE model. It was found, that the model predicts more accurately the bridge mid-span displacements than its natural frequencies, and that the adopted traffic model is less able to simulate the bridge behaviour during periods of traffic jams. Future developments of the MBA framework include its extension and application for damage detection and MSD with multiple parameter identification.

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31

Storozhev, Dmitry Leonidovich. "Smart Rotating Machines for Structural Health Monitoring". Cleveland State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=csu1262724991.

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32

Cury, Alexandre. "Techniques d'anormalité appliquées à la surveillance de santé structurale". Phd thesis, Université Paris-Est, 2010. http://tel.archives-ouvertes.fr/tel-00581772.

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Le paradigme de la surveillance de santé structurale repose sur l'introduction d'indicateurs fiables et robustes permettant de détecter, localiser, quantifier et prédire un endommagement de manière précoce. En effet, la détection d'une modification structurale susceptible de devenir critique peut éviter l'occurrence de dysfonctionnements majeurs associés à des conséquences sociales, économiques et environnementales très importantes.Ces dernières années, de nombreuses recherches se fait de l'évaluation dynamique un élément de diagnostic. La plupart des méthodes reposent sur une analyse temporelle ou fréquentielle des signaux pour en extraire une information compressée au travers de quelques caractéristiques modales ou d'indicateurs évolués construits sur ces caractéristiques. Ces indicateurs ont montré leur efficacité, mais le problème de leur sensibilité, de la nécessité de disposer d'un état de référence, et de leur fiabilité en terme de la probabilité de détection et de fausses alarmes, reste entier. De plus, le fait d'utiliser des mesures dynamiques (particulièrement si plusieurs voies de mesures sont considérées) mène au stockage de grands volumes de données.Dans ce contexte, il est important d'employer des techniques permettant d'utiliser autant des données brutes que les propriétés modales de manière pratique et pertinente. Pour cela, des représentations adaptées ont été développées pour améliorer la manipulation et le stockage des données. Ces représentations sont connues sous le nom de og données symboliques fg . Elles permettent de caractériser la variabilité et l'incertitude qui entachent chacune des variables. Le développement de nouvelles méthodes d'analyse adéquates pour traiter ces données est le but de l'Analyse de Données Symboliques (ADS).L'objectif de cette thèse est double : le premier consiste à utiliser différentes méthodes couplées à l'ADS pour détecter un endommagement structural. L'idée est d'appliquer des procédures de classification non supervisée (e.g. divisions hiérarchiques, agglomérations hiérarchiques et nuées dynamiques) et supervisée (e.g., arbres de décision Bayésiens, réseaux de neurones et machines à vecteurs supports) afin de discriminer les différents états de santé d'une structure. Dans le cadre de cette thèse, l'ADS est appliquée aux mesures dynamiques acquises emph{in situ} (accélérations) et aux paramètres modaux identifiés. Le deuxième objectif est la compréhension de l'impact des effets environnementaux, notamment de ceux liés à la variation thermique, sur les paramètres modaux. Pour cela, des techniques de régression des données sont proposées.Afin d'évaluer la pertinence des démarches proposées, des études de sensibilité sont menées sur des exemples numériques et des investigations expérimentales. Il est montré que le couplage de l'ADS aux méthodes de classification de données permet de discriminer des états structuraux avec un taux de réussite élevé. Par ailleurs, la démarche proposée permet de vérifier l'importance d'utiliser des techniques permettant de corriger les propriétés modales identifiées des effets thermiques, afin de produire un processus de détection d'endommagements efficace

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33

Sazak, Hasan. "STRUCTURAL HEALTH MONITORING OF A STADIUM FOR EVALUATING HUMAN COMFORT AND STRUCTURAL PERFORMANCE". Master's thesis, University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4473.

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Light and rapid constructions as well as considerations such as improved line of sight and increased capacity for modern stadium structures make them vulnerable for vibration serviceability problems. These problems are also observed at convention centers, large shopping malls, concert halls and ballrooms. Especially when the individuals in a crowd are involved in some sort of coordinated motion, this type of loading creates the most potential for high levels of vibration. In order to understand the causes of vibration, vibration levels, service and safety levels, Structural Health Monitoring (SHM) can be implemented to track and evaluate performance of a structure during events such as games at football stadia. SHM becomes a critical need especially when decisions such as repair and retrofit are to be made for the structure. The main objectives of this study are a) to determine the impact of vibration to human comfort levels; b) to identify dynamic loading for the coordinated motion; c) to determine the structural performance by means of a detailed model validated using experimental data. In order to achieve these objectives, a football stadium was monitored for three years to establish the vibration levels during different games and different events in each game such as goals, interceptions, playing a particular song. It is seen that certain events and long periods of playing particular songs induced vibration levels that are at the threshold of human comfort based on the design codes. To simulate the crowd motion due to this song, a laboratory study was designed and conducted to experimentally determine the forcing functions due to jumping with the rhythm of the song. The spectral analysis of the stadium data and the song also revealed that the first mode frequency of the stadium and the dominant frequency of the music are very close, creating resonance conditions. Further investigative studies were conducted by developing a finite element (FE) model of the stadium, which was validated using the results of the modal analysis from the ambient vibration data. Subsequently, the FE model was employed to simulate forcing functions obtained from the laboratory studies to explore the vibration levels, dynamic response as well as the response of the structure when it is retrofitted by additional elements. In addition, different aspects of model development, with respect to the physical model of the stadium were outlined in terms of design considerations, instrumentation, finite element modeling, and simulating dynamic effect of spectators. Finally, the effectiveness of the retrofit by adding elements to the steel structure of the stadium was explored by simulating the crowd motion with the FE model.
M.S.
Department of Civil, Environmental, and Construction Engineering;
Engineering and Computer Science
Civil, Environmental, and Construction Engineering

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34

Erazo, Kalil. "Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring". ScholarWorks @ UVM, 2015. http://scholarworks.uvm.edu/graddis/513.

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During strong earthquakes structural systems exhibit nonlinear behavior due to low-cycle fatigue, cracking, yielding and/or fracture of constituent elements. After a seismic event it is essential to assess the state of damage of structures and determine if they can safely resist aftershocks or future strong motions. The current practice in post-earthquake damage assessment relies mainly on visual inspections and local testing. These approaches are limited to the ability of inspectors to reach all potentially damaged locations, and are typically intended to detect damage near the outer surfaces of the structure leaving the possibility of hidden undetected damage. Some structures in seismic prone-regions are instrumented with an array of sensors that measure their acceleration at different locations. We operate under the premise that acceleration response measurements contain information about the state of damage of structures, and it is of interest to extract this information and use it in post-earthquake damage assessment and decision making strategies. The objective of this dissertation is to show that Bayesian filters can be successfully employed to estimate the nonlinear dynamic response of instrumented structural systems. The estimated response is subsequently used for structural damage diagnosis. Bayesian filters combine dynamic response measurements at limited spatial locations with a nonlinear dynamic model to estimate the response of stochastic dynamical systems at the model degrees-of-freedom. The application of five filters is investigated: the extended, unscented and ensemble Kalman filters, the particle filter and the model-based observer. The main contributions of this dissertation are summarized as follows: i) Development of a filtering-based mechanistic damage assessment framework; ii) Experimental validation of Bayesian filters in small and large-scale structures; iii) Uncertainty quantification and propagation of response and damage estimates computed using Bayesian filters.

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35

Kuok, Sin Chi. "Ambient effects on structural health monitoring of buildings". Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2099636.

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36

Engelbrecht, André. "Structural integrity monitoring using vibration measurements". Pretoria : [s.n.], 2006. http://upetd.up.ac.za/thesis/available/etd-07032006-122342/.

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37

Shiryayev, Oleg V. "Improved Structural Health Monitoring Using Random Decrement Signatures". Wright State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1214234132.

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38

Meehan, Rachael E. (Rachael Elizabeth). "Technology and application of structural health monitoring in bridges". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66841.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, June 2011.
"June 2011." Cataloged from PDF version of thesis.
Includes bibliographical references (p. 51-53).
Structural Health Monitoring (SHM) has become a useful tool for detecting when the characteristics of a structure have changed to indicate damage such that well-timed and effective maintenance may be planned and the remaining performance capacity may be assessed. SHM has also lead to a better understanding of the loads and the response within a structure in order to optimize future design. In this paper, research is compiled on the current practice of SHM with coverage of sensors used, system configurations, data management, analysis and a discussion of current issues. Recommendations on the current state and future of SHM are made and case studies investigate recent applications. A proposed procedure for the design and implementation of a SHM system is examined and then applied to the design project for the Master of Engineering program in High Performance Structures at MIT. Conclusions include a suggestion on the most effective way to design a SHM system, what the industry needs to mature and predictions of the future of the industry.
by Rachael E. Meehan.
M.Eng.

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39

Wang, Wennie. "Towards structural health monitoring in carbon nanotube reinforced composites". Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/80904.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2013.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 51-56).
An experimental investigation was conducted to understand the non-destructive evaluation (NDE) capabilities of carbon nanotubes (CNTs) of several network architectures towards structural health monitoring (SHM). As heterogeneous composite structures become increasingly common in industry, detecting mechanical damage and damage accumulation becomes increasingly difficult as many modes of failure occur below the external surface. Traditional SHM techniques may be time consuming and costly; however, CNTs are a unique material that shows promise as a strain or damage sensor. Three different laminate samples types with various CNT network architectures were tested in open-hole tension. Samples tested were quasiisotropic carbon fiber, carbon fiber prepreg with unidirectional knocked-down CNT surface patch, and fuzzy fiber reinforced plastic (FFRP) samples, which consist of radially grown CNTs on a woven ceramic fiber substrate. Mechanical load and electrical resistance were simulataneously measured using three different probes configurations with respect to the tensile direction that measured either surface or through thickness resistance changes. Measurements were taken near and away from the stress concentration. Results indicated that different CNT network architectures influenced the consistency and efficacy of indicating damage acculumation. Changes in electrical resistance correlated strongly with sample mechanical damage accumulation for unidirectional knocked-down CNTs, but had more consistent values and readings for the FFRP samples, indicating that CNT network architecture beyond the inherent piezoresistivity of the CNT heavily influences the NDE capabilities of using CNTs as strain or damage sensors. Results also suggest that CNT network architecture must be further optimized to achieve reliable NDE and SHM, and may depend on the desired application.
by Wennie Wang.
S.B.

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40

Pentaris, Fragkiskos. "Digital signal processing for structural health monitoring of buildings". Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/10560.

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Structural health monitoring (SHM) systems is a relatively new discipline, studying the structural condition of buildings and other constructions. Current SHM systems are either wired or wireless, with a relatively high cost and low accuracy. This thesis exploits a blend of digital signal processing methodologies, for structural health monitoring (SHM) and develops a wireless SHM system in order to provide a low cost implementation yet reliable and robust. Existing technologies of wired and wireless sensor network platforms with high sensitivity accelerometers are combined, in order to create a system for monitoring the structural characteristics of buildings very economically and functionally, so that it can be easily implemented at low cost in buildings. Well-known and established statistical time series methods are applied to SHM data collected from real concrete structures subjected to earthquake excitation and their strong and weak points are investigated. The necessity to combine parametric and non-parametric approaches is justified and to this direction novel and improved digital signal processing techniques and indexes are applied to vibration data recordings, in order to eliminate noise and reveal structural properties and characteristics of the buildings under study, that deteriorate due to environmental, seismic or anthropogenic impact. A characteristic and potential harming specific case study is presented, where consequences to structures due to a strong earthquake of magnitude 6.4 M are investigated. Furthermore, is introduced a seismic influence profile of the buildings under study related to the seismic sources that exist in the broad region of study.

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41

Mullapudi, Sai Lalitya. "New Techniques in Structural Health Monitoring using Continuous Sensors". University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1299179416.

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42

Li, Xinming. "Piezoelectric-based structural health monitoring of flexible beam connection damage". Thesis, University of Ottawa (Canada), 2003. http://hdl.handle.net/10393/26511.

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Structural health monitoring is an emerging technology addressing major concerns in the operation of in-service structures, i.e. the reliability of the structures and the cost associated with maintaining reliability. In this thesis, the motivation of structural health monitoring has been discussed within the framework of non-destructive evaluation. To be a common failure mode, connection damage or lap joint damage is chosen as damage signature in a structure, consisting of a flexible aluminum beam jointed on a frame by bolts. To simulate connection damage, the stress relaxing on the bolt is achieved by the action of bolt looseness quantified by rotation angle. The dynamic response of flexible beam system is monitored with a piezoelectric transducer. To produce exciting signal, an electro-mechanical system processes the voltage signal. Response interpretation is carried out on PC or on an embedded DSP chip in real time. The two analysis methods, frequency response method and wavelet analysis method, were explored to identify early "changes" of beam connection so as to reach the goal of structural health monitoring.

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43

He, Jiaze. "Time-reversal Based Array Damage Imaging in Structural Health Monitoring". Thesis, North Carolina State University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10110540.

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Composite materials are receiving increasing attention and broadly used in aerospace industry due to their superior strength-to-weight ratio, corrosion resistance and design flexibility. The need for rapid nondestructive evaluation (NDE) techniques for composites is growing rapidly as the complexity and dimensions of the structures are increasing significantly. Structural health monitoring (SHM) has been attracting much attention as a means of providing in-service and in-situ monitoring of various critical structures. Due to their capability of long-range and through-the-thickness interrogation of the structures for small defects, guided waves have been studied extensively in damage detection for plate-like structures.

However, a few challenges exist when Lamb wave-based SHM/NDE techniques are employed. For example, the dispersion effect decreases the accuracy of many damage imaging algorithms; damage severity quantification is always a difficult problem. To provide possible solutions to above challenges, two damage imaging algorithms were developed and utilized for Lamb-wave based damage imaging.

The first algorithm is reverse-time migration (RTM), which was first used in geophysics to provide proper solutions to complex wave phenomena. The traditional imaging condition utilized in SHM is called excitation-time imaging condition, which used ray tracing and group velocity corresponding to the center frequency of the input signal. Due to the dispersion effect, the time-of-flight (ToF) estimation cannot always be accurate, especially for the situations that the Lamb waves propagate for a long distance. In this thesis, new imaging conditions are proposed to form enhanced zero-lag cross-correlation reverse-time migration (E-CCRTM) techniques. The proposed damage imaging technique takes into account the amplitude, phase, and all the frequency content of the Lamb waves propagating in the plate; thus, the severity of multiple sites of damage can be non-biasedly imaged regardless of the damage locations in comparison with using existing imaging conditions. The other imaging algorithm is called ‘DORT-MUSIC’. A Lamb wave-based, subwavelength imaging algorithm is developed for damage imaging in large-scale, plate-like structures based on a decomposition of the time-reversal operator (DORT) method combined with the multiple signal classification (MUSIC) algorithm in the space-frequency domain. The physics of wave propagation, reflection, and scattering that underlies the response matrix in the DORT method is mathematically formulated in the context of guided waves. Singular value decomposition (SVD) is then employed to decompose the experimentally measured response matrix into three matrices, detailing the incident wave propagation from the linear actuator array, reflection from the damage, and followed by scattering waves toward the linear sensing array for each small damage. The SVD and MUSIC-based imaging condition enable quantifying the damage severity by a ‘reflectivity’ parameter and super-resolution imaging.

The two algorithms were also integrated with a hybrid system mainly comprised piezoelectric actuators mounted onto the structure and a laser Doppler vibrometer (LDV) for reception. The flexibility of the proposed system was used for inspection of various plate-like structures. The experimental results show that the 2-D E-CCRTM has robust performance to image and quantify multiple sites of damage in large area of the plate using a single PZT actuator with a nearby areal scan using LDV, and the DORT-MUSIC (TR-MUSIC) imaging technique can provide rapid, highly accurate imaging results as well as damage quantification with unknown material properties.

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Yan, Linjun. "Sensor data analysis and information extraction for structural health monitoring". Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3226288.

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Thesis (Ph. D.)--University of California, San Diego, 2006.
Title from first page of PDF file (viewed October 11, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.

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45

Fekrmandi, Hadi. "Development of New Structural Health Monitoring Techniques". FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=2923&context=etd.

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During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

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46

Sarti, Matteo. "Preliminary study for the assessment of discontinuity’s size through Machine Learning algorithms". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22874/.

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During the last two decades there has been a huge breakthrough in the Structural Health Monitoring field, especially in the study of Acoustic Emissions (AE), to get qualitative and quantitative damage-related information. This thesis attempts to focus on the possibility of obtaining an automatic estimate of small discontinuity’s length in an aluminium plate, by analysing some impinging signals when they interfere with the defect itself. The novel aspect about this analysis is that it was conducted through “trained” classification and regression algorithms that have been able, up to some extent, to automatically classify and predict the desired responses. This means that Artificial Intelligence, in particular Machine Learning techniques, were employed and played an important role within either the identification and the predictive part of this study. Due to the SARS-CoV-2 global pandemic, and the consequent closure of the US embassies, it was not possible to obtain the Visa and go to Clarkson University to perform the experimental campaign there. Therefore, in order to collect the raw signals for the subsequent analysis, a comparison between Abaqus CAE and OnScale software was firstly enforced, and eventually the latter was chosen to perform the whole set of numerical simulations exploiting a pitch-catch configuration.

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47

Gaddam, Sathvik Reddy. "Structural health monitoring system| Filtering techniques, damage localization, and system design". Thesis, California State University, Long Beach, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10144825.

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Material testing is a major concern in many manufacturing and aeronautical industries, where structures require periodic inspection using equipment and manpower. Environmental Noise (EN) is the major concern when localizing the damage in real time. Inspecting underlying components involves destructive approaches. These factors can be alleviated using Non Destructive Testing (NDT) and a cost effective embedded sensor system.

This project involves NDT implementation of Structural Health Monitoring (SHM) with filtering techniques in real time. A spectrogram and a scalogram are used to analyze lamb response from an embedded array of Piezo Transducers (PZT). This project gives insights on implementing a real time SHM system with a sensor placement strategy and addresses two main problems, namely filtering and damage localization. An Adaptive Correlated Noise Filter (ACNF) removes EN from the lamb response of a structure. A damage map is developed using Short Time Fourier Transform (STFT), and Continuous Wavelet Analysis (CWA).

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Kirikera, Goutham Raghavendra. "A Structural Neural System for Health Monitoring of Structures". University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1155149869.

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49

Pawar, Prashant M. "Structural Health Monitoring Of Composite Helicopter Rotor Blades". Thesis, Indian Institute of Science, 2006. http://hdl.handle.net/2005/273.

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Helicopter rotor system operates in a highly dynamic and unsteady aerodynamic environment leading to severe vibratory loads on the rotor system. Repeated exposure to these severe loading conditions can induce damage in the composite rotor blade which may lead to a catastrophic failure. Therefore, an interest in the structural health monitoring (SHM) of the composite rotor blades has grown markedly in recent years. Two important issues are addressed in this thesis; (1) structural modeling and aeroelastic analysis of the damaged rotor blade and (2) development of a model based rotor health monitoring system. The effect of matrix cracking, the first failure mode in composites, is studied in detail for a circular section beam, box-beam and two-cell airfoil section beam. Later, the effects of further progressive damages such as debonding/delamination and fiber breakage are considered for a two-cell airfoil section beam representing a stiff-inplane helicopter rotor blade. It is found that the stiffness decreases rapidly in the initial phase of matrix cracking but becomes almost constant later as matrix crack saturation is reached. Due to matrix cracking, the bending and torsion stiffness losses at the point of matrix crack saturation are about 6-12 percent and about 25-30 percent, respectively. Due to debonding/delamination, the bending and torsion stiffness losses are about 6-8 percent and about 40-45 percent after matrix crack saturation, respectively. The stiffness loss due to fiber breakage is very rapid and leads to the final failure of the blade. An aeroelastic analysis is performed for the damaged composite rotor in forward flight and the numerically simulated results are used to develop an online health monitoring system. For fault detection, the variations in rotating frequencies, tip bending and torsion response, blade root loads and strains along the blade due to damage are investigated. It is found that peak-to-peak values of blade response and loads provide a good global damage indicator and result in considerable data reduction. Also, the shear strain is a useful indicator to predict local damage. The structural health monitoring system is developed using the physics based models to detect and locate damage from simulated noisy rotor system data. A genetic fuzzy system (GFS) developed for solving the inverse problem of detecting damage from noise contaminated measurements by hybridizing the best features of fuzzy logic and genetic algorithms. Using the changes in structural measurements between the damaged and undamaged blade, a fuzzy system is generated and the rule-base and membership functions optimized by genetic algorithm. The GFS is demonstrated using frequency and mode shape based measurements for various beam type structures such as uniform cantilever beam, tapered beam and non-rotating helicopter blade. The GFS is further demonstrated for predicting the internal state of the composite structures using an example of a composite hollow circular beam with matrix cracking damage mode. Finally, the GFS is applied for online SHM of a rotor in forward flight. It is found that the GFS shows excellent robustness with noisy data, missing measurements and degrades gradually in the presence of faulty sensors/measurements. Furthermore, the GFS can be developed in an automated manner resulting in an optimal solution to the inverse problem of SHM. Finally, the stiffness degradation of the composite rotor blade is correlated to the life consumption of the rotor blade and issues related to damage prognosis are addressed.

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50

Zheng, Shijie. "Photonic Crystal Fiber Based Chemical Sensors for Civil Structural Health Monitoring". Thesis, Northwestern University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3563914.

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Abstract (sommario):

A photonic crystal fiber (PCF) long-period grating (LPG) humidity sensor has been developed with high sensitivity and selectivity for nondestructive detection of moisture ingression into structures that can potentially lead to corrosion. We have proposed two types of nanofilms to be coated on the surface of air channels in the grating region of the fiber using electrostatic self-assembly deposition processing. The primary nanofilm does not affect LPG properties such as resonance wavelength or transmission intensity which can impact sensing characteristics; however it increases the sensitivity by changing the refractive index of the surrounding material. The secondary nanofilm is used for selectively adsorbing analyte molecules of interest. The experimental results reveal that, compared to the conventional fiber LPGs and exterior nanofilm-coated PCF-LPG, the interior nanofilm-coated PCF-LPG humidity sensors have higher resonance intensity change of 0.00022%/10^-3dBm at relative humidity (RH) of 38% and average wavelength shift of 0.0007%/pm in range of 22% to 29%. The proposed sensor shows excellent thermal stability as well.

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Tesi sul tema "Structural analysis (Engineering) Structural health monitoring"

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