Doctor of Philosophy, The Ohio State University, 2022, Civil Engineering

There are three main research conducted in this paper, including using deep learning methods with vision-based technologies on Structural Damage Detection (SDD), Structural Health Monitoring (SHM) and progressive collapse study. During the learning and improvement process, many goals of automation in SDD and SHM have been achieved, although there will be a large room for further improvement and development on these studies. In progressive collapse study, remote sensing technologies and data fusion are applied on a field experiment of a real building at the Central Campus of the Ohio State University. The major contributions of this paper are shown as follows: A few comprehensive experimental studies for automated SDD in extreme events using deep learning methods for processing 2D images. In the first study, a 152-layer Residual Network (ResNet) is utilized to identify multiple classes in eight SDD tasks, which include identification of scene levels, damage levels, material types, etc. The proposed ResNet achieved high accuracy for each task while the positions of the damage are not identifiable. In the second study, the existing ResNet and a segmentation network (U-Net) are combined into a new pipeline, cascaded networks, for categorizing and locating structural damage. The results show that the accuracy of damage detection is significantly improved compared to only using a segmentation network. In the third and fourth studies, end-to-end networks are developed and tested as a new solution to directly detect cracks and spalling in the image collections of recent large earthquakes. One of the proposed networks can achieve an accuracy above $67.6\%$ for all tested images at various scales and resolutions, and shows its robustness for these human-free detection tasks. Studies are conducted with a pipeline to automatically track and measure displacements and vibrations of structures or structural components in laboratory and field experiments. This novel framework (open full item for complete abstract)

Committee: Halil Sezen Dr. (Advisor); Farhang Pourboghrat Dr. (Committee Member); Rongjun Qin Dr. (Committee Member); Alper Yilmaz Dr. (Advisor) Subjects: Civil Engineering; Computer Science; Mechanics

Master of Science, University of Akron, 2006, Civil Engineering

The main objective of this study is to show the specific capabilities of the Scanning Laser Vibrometer (SLV) for global damage detection using a recent defect energy parameter technique proposed by Saleeb and coworkers. The experimental technique used for extraction of signature is the first and most important part in any damage detection technique. Signatures considered here are full-field SLV measurements for modal shapes and associated frequencies of plated structures. The damage feature extraction capability was studied extensively by analyzing various simulation and experimental results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The signal – noise ratio of experiment shows the capability of the same experiment to be used for damage detection purpose. Various experiments were performed to verify a significant signal – noise ratio for a successful detection. Very high number of scanning points, for optical experimental measurement, for any civil structure can be impractical and uneconomical. So, a pragmatic direction for the development of new experimental measurement tools was studied where different number of scanning points and different types of statically loaded simulations were performed to verify the specific capabilities of the defect energy parameter technique. It was further observed that powerful graphic user interface should also be an integral part in any present in the damage detection scheme for successful and more accurate detection. Furthermore, some potential use of SLV techniques in detection are provided, both for dynamic and static applications.

Committee: Atef Saleeb (Advisor) Subjects:

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2009, College of Science

A large number of genetic diseases and genetic disorders are simply caused by base alterations in the genome. Therefore, developing efficient and cost effective techniques for routine detection of these alterations is of great importance. Different methods involving gel electrophoresis and Polymerase Chain Reaction have been widely employed, but majority of these methods are costly, time consuming, and lack throughput, creating a fundamental gap between the current state-of-the-art and desired characteristics of low-cost, high-speed, simplicity, versatility, and potential for miniaturization. In this study, we attempt to bridge this gap by developing new sensing platforms to detect DNA base mismatches and DNA damage with higher throughput, better ease-of-use, and with the potential to be miniaturized for greater portability. Two electrochemical mismatch detection sensing platforms were developed. One uses the electrochemical reduction of trans-4-cinnamic acid diazonium tetrafluoroborate. The other takes advantage of the natural ability of MutS protein for single base mismatch recognition. Also, two DNA damage detection assays were developed and the first approach uses Atomic Force Microscopy to monitor minor DNA damage by labeling damaged sites with a biomarker. This site-specific biolabeling was achieved through well-established biotin-streptavidin chemistry. In the second approach, a new layer-by-layer biomolecular immobilization method was introduced and used to detect DNA chemical damage using electrochemical techniques.

Committee: Mekki Bayachou PhD (Committee Chair); Lily Ng PhD (Committee Member); Robert Wei PhD (Committee Member); John Masnovi PhD (Committee Member); Crystal Weyman PhD (Committee Member) Subjects: Analytical Chemistry

MS, University of Cincinnati, 2024, Engineering and Applied Science: Mechanical Engineering

Vibration based methods for Structural Health Monitoring (SHM) have become increasingly popular over the last few decades. In this field, non-contact measurement techniques have garnered a lot of attention due to its capacity to provide spatially dense full-field measurements. One such method is photogrammetry, which works on the technique of tracking an object or feature on the surface of a structure. This study proposes a fully non-contact method for estimating the Operational Deflection Shape (ODS) of a plate-like structure based on detecting and tracking a laser projected feature which can provide a dense measurement grid and has no permanent effect on the surface of the structure being measured. It has been long established that any local damage to a structure defined by a loss of stiffness causes local anomalies in the structure's ODS, which can be localized by taking the second derivative of the ODS, commonly known as its curvature. In this study, a damage index is formulated for plate-like structures using higher order derivatives, namely the second, fourth and sixth derivatives, with different orders of accuracy and is shown to successfully identify damage with no knowledge of the structure's undamaged state. The derivatives are computed using the central finite difference scheme. Both experimental and numerical studies are conducted to test the robustness and efficacy of the proposed index. In the numerical investigations, a Finite Element Model (FEM) is used to simulate and extract the natural frequencies and mode shapes of a plate-like structure under free-free boundary conditions. The robustness of the proposed damage index is studied for varying levels of measurement errors, simulated by adding white Gaussian noise. The effects of different parameters like the location and size of the damage are also studied. In the experimental investigation, a damaged steel plate is acoustically excited using an electric speaker at a frequency very close to o (open full item for complete abstract)

Committee: Yongfeng Xu Ph.D. (Committee Chair); Allyn Phillips Ph.D. (Committee Member); Jay Kim Ph.D. (Committee Member) Subjects: Mechanical Engineering

MS, University of Cincinnati, 2021, Engineering and Applied Science: Mechanical Engineering

The presence of damage can significantly decrease the performance of a structure and lead to potential repairs, downtimes, and failures. Therefore, it is important and desirable to identify the damage at an early stage. This work proposes a baseline-free damage identification method using an acoustic beamforming approach. This approach excites a plate-like structure using an active acoustic source and measures sound radiation of the structure in the form of sound pressure using a microphone array. The measured sound pressure is processed using a delay and sum beamforming (DASB) algorithm to identify the existence and spatial location of the damage. In the algorithm, the damage is considered as a dominant point sound source, assuming the sound pressure from the damage has a much higher magnitude than that from intact areas of the structure. The existence of damage is identified based on an acoustic damage index, and its location is identified as the centroid of a non-zero area of clustered auxiliary binary damage index. Numerical and experimental studies were conducted to investigate the effectiveness and robustness of the proposed method. In the numerical study, a vibro-acoustic finite element model is constructed: a metal box is modeled with damage in the form of a through-thickness hole on its front plate and an active monopole sound source is placed inside the box to generate acoustic excitation. Parametric studies are performed to understand the effects of the damage size and location, microphone array arrangement, excitation frequency, and distance between the box and microphone array, on damage identification results by the proposed method. The robustness of the proposed method is also studied for measurement errors of sound pressure and position estimation errors of a microphone array and scan points on the structure. In the experimental study, a vibro-acoustic test setup was established in a hemi-anechoic chamber. A metal box with a front plate undergoin (open full item for complete abstract)

Committee: Yongfeng Xu Ph.D. (Committee Chair); David Thompson (Committee Member); Jay Kim Ph.D. (Committee Member) Subjects: Mechanical Engineering

MS, University of Cincinnati, 2021, Engineering and Applied Science: Mechanical Engineering

Vibration-based damage detection methods have been extensively used in structural health monitoring as these are response-based techniques and can be applied to experimental/operational data. The conventional methods of obtaining full-field vibration measurements are limited due to the location and number of sensors. Advancements in imaging technology have enabled the use of the digital image correlation (DIC) technique to measure the full-field deformation of a vibrating structure. In this study, the DIC technique was used to obtain vibration measurements from an impact test of a cantilever beam for damage identification. The application of curvature mode shapes (CMSs) developed from the mode shapes (MSs) of the beam is studied to detect and locate the damage. The CMSs of the undamaged state of the beam are determined only from the damaged state of the beam, without prior information about the associated undamaged beam, provided the beam is geometrically smooth. It is shown that the polynomial fit of the appropriate order of measured MS is equivalent to the associated MS of the undamaged beam. The objective of this study was to investigate the use of DIC technique and CMSs to locate and detect damage in the form of a machined area with reduced thickness in a cantilever beam. The modal parameter estimation (MPE) was done using X-Modal software, based on the unified matrix polynomial approach (UMPA), to obtain mode shapes and natural frequencies from the vibration measurements. It is shown that the proposed method can successfully detect and locate damage in the beam, for the data obtained from a single-input impact test. The work focuses on understanding how the parameters used in the DIC technique and MPE influence the damage detection. The influences of parameters such as subset size and step size used in the DIC technique are studied. The influences of parameters such as type of MPE algorithm, frequency band selection and model order during MPE are studied. (open full item for complete abstract)

Committee: Yongfeng Xu Ph.D. (Committee Chair); Randall Allemang Ph.D. (Committee Member); Allyn Phillips Ph.D. (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2020, Civil Engineering

Vibration-based structural health monitoring (SHM) has become increasingly popular in recent years as a general and global method to detect possible damage scenarios. With the increase in the number of infrastructures that are in service beyond their initial design service age, more and more owners are relying on SHM to evaluate the integrity of their structures. As a result, SHM approaches that are applicable to a variety of structures with minimal service interruption and lower cost are of high importance. There are many research on SHM processes using a network of sensors placed on over a target structure. Although these approaches may result in more accurate results due to redundancy of the system, they are mostly cost prohibitive for currently in-service structures and are suitable for newly constructed projects with embedded sensors. This dissertation presents a feature-based SHM process using a new signal processing and feature extraction methodology and presents its application on a real-life vibration monitoring project completed of an energized substation structure. The new signal processing and feature extraction methodology uses specific filtering and optimization schemes which improved the performance in extracting features specifically when using a contaminated response signal. Next, the extracted features are used in a structural model updating to identify and localize the damage through an optimization process. Finally, a vortex-induced vibration analysis process is presented and applied to the real-life monitored structure. Currently there are no power utility industry standard methodology for the analysis and design of structures against wind-induced vibrations. The current codes or standards of practice recommend using damping devices such as chain dampers or strakes to mitigate the vibrations, when they are observed. This approach may not be feasible due to the energized in-service structures. In addition, modifications to the installed structure (open full item for complete abstract)

Committee: Abdollah Shafieezadeh (Advisor); Jieun Hur (Committee Member); Halil Sezen (Committee Member) Subjects: Engineering

Master of Science in Engineering, Youngstown State University, 2020, Department of Civil/Environmental and Chemical Engineering

In any civil engineering structure, damage resulted from the construction phase or developed over time affects the structural performance and may result in its failure. Early-stage damage detection is necessary for maintaining structural safety, serviceability, and minimizing the cost throughout the structural operation. Various destructive and conventional non-destructive damage detection techniques employed over the years are either laborious or, uneconomical, and require access to the entire structure. These limitations were addressed by developing the vibration-based methods for regular structural health monitoring. This holistic approach includes analyses of vibration signals and the related modal parameters. The change in these parameters may be used for detection of damage. In this research, modal frequency was used as a parameter to detect damage. The objective is to identify damage using natural frequency. To achieve this objective, several tests were conducted on simply supported steel beams having an open transverse crack with varying depths and locations. The analytical, numerical, and experimental approaches generate frequencies for the first three vibrating modes. The analytical approach considered the beam as the Euler-Bernoulli beam. Analytical frequencies were found from the solution of a partial differential equation by applying the boundary conditions. Vibration signals collected from the portable digital vibrometer (PDV 100) were analyzed using the Fast Fourier Transform (FFT) technique to achieve modal frequencies of the steel beam. In ANSYS (ANSYS, 2017), the finite element models of the beams were calibrated using the experimental results. The frequency from the analytical approach depends on the crack depth. Therefore, this method cannot produce the actual frequency of a beam with varying damage locations and depths. The graphical plots of the normalized frequency with varying damage depth and damage location was used to study the impact o (open full item for complete abstract)

Committee: AKM Anwarul Islam PhD (Advisor); Shakir Husain PhD (Committee Member); Richard Deschenes PhD (Committee Member) Subjects: Civil Engineering; Engineering

Doctor of Philosophy, University of Akron, 2016, Mechanical Engineering

Melt infiltrated (MI) SiC fiber-reinforced SiC ceramic matrix composites (CMCs) are slowly replacing metals in the hot section components of turbine engines. The increasing application of these composites requires structural health monitoring techniques that are sensitive to transverse matrix cracks which form at elevated temperatures and limit the long-term durability of the material. Previous research has demonstrated a large increase in electrical resistance (ER) in response to transverse matrix cracks that formed in MI SiC/SiC during room temperature tensile loading. In this study, the ER response of slurry cast MI SiC/SiC CMCs at elevated temperatures (815°C and 1315°C), was explored under a wide range of applied tensile stresses. The results showed that the ER increased by up to 300% in response to tensile loading at the intermediate temperature of 815°C. Long-term stressed-oxidation tests at 815°C led to in-situ ER increases of more than 90% prior to sample break. The in-situ ER changes also directly correlated with measured crack density. Similarly, post-test inspection of the samples at room temperature showed ER increases greater than 100% for cracked samples after 100 hours. The room temperature inspection ER also correlated directly with the observed crack density. Thus, for all tests at 815°C, the ER was highly sensitive to the formation of matrix cracks. However, for the test temperature of 1315°C, the ER was less sensitive to damage. Resistance changes of the samples were an order of magnitude lower than they were at 815°C and there was no clear correlation between ER and crack density. The difference in results for the two test temperatures was explained by the decreasing sample resistivity at higher temperatures. Since the resistance was measured from the cold grips, the cooler (higher resistivity) regions had more effect on the sample resistance than the hotter (lower resistivity) regions.

Committee: Gregory Morscher Dr. (Advisor); Kwek-Tze Tan Dr. (Committee Member); Wieslaw Binienda Dr. (Committee Member); Erol Sancaktar Dr. (Committee Member); Manigandan Kannan Dr. (Committee Member); Tirumalai Srivatsan Dr. (Other) Subjects: Mechanical Engineering

Master of Science, University of Akron, 2015, Civil Engineering

Understanding and predicting the behavior of structures under specific operating conditions is a fundamental task of structural engineers. Scientific principles are used to model the characteristics of a material's response to these various mechanical loads. Using experimental data, constitutive models can be created that provide a mathematical description of a materials response. However, these constitutive models require numerous parameters to be identified. In order to calculate these parameters, inverse parameter identification algorithms can be used. These constitutive models apply a homogenous distribution of the material parameters across a structural component. However, in reality there is often a heterogeneous distribution of these material parameters across the structure. This can be due to a variety of reasons including the characteristics of the raw material, geometry, manufacturing processes, fatigue and damage. In order to model this heterogeneous distribution, stochastic methods can be deployed. In this research, an inverse parameter identification method known as the Self-Optimizing Inverse Methodology (Self-OPTIM) will be used to create a powerful and easy to use software framework for parameter identification. This software framework includes capabilities to parallelize finite element simulation to reduce the time of optimization. In addition, this framework will include a stochastic methodology that can be used to model heterogeneous distributions of material parameters across a structural component. Using this software, the capabilities of Self-OPTIM will be tested on various constitutive models to demonstrate its ease of use as well as its superiority to other methods using boundary information as its primary input.

Committee: Gunjin Yun Dr. (Advisor); Robert Goldberg Dr. (Committee Member); Weislaw Binienda Dr. (Committee Member) Subjects: Civil Engineering

Doctor of Philosophy, Case Western Reserve University, 2015, Biomedical Engineering

Cartilage tissue engineers have made great inroads on understanding the factors controlling chondrogenesis, however, the biomechanical properties of tissue engineered cartilage (TEC) are chronically inferior to that of native cartilage. The focus of this dissertation was to determine the ability of scaffold-free TEC to withstand frictional-shear stress, and if needed, to improve that ability to a physiologically relevant level. Frictional-shear testing performed at a sub-physiological normal stress of 0.55 MPa demonstrated that constructs exhibited lubrication patterns characteristic of native cartilage lubrication, but severe damage also occurred. Low absolute collagen content, and a low collagen-to-glycosaminoglycan (GAG) ratio were also found in the same constructs. Reduction in damage was attempted by increasing the collagen content of the ECM. Scaffold-free TEC treated with T4 at 25 ng/ml exhibited increased collagen concentration in a statistically significant manner, and the average collagen-to-GAG ratio was also increased although statistical significance was not achieved. Western blotting showed that type II collagen was increased, type X collagen was not detected. COL2A1, and biglycan gene expression were also found to have increased, no statistically significant difference was found for COLX gene expression. When compared to control constructs, T4 treated constructs exhibited a large and statistically significant decrease in the extent of damage incurred by frictional-shear testing. At the 2.8 MPa normal stress, total damage was reduced by 60% in the 2-month constructs. Correlation coefficients calculated between compositional properties and the amount of damage showed that at the 2.8 MPa normal stress collagen concentration and the collagen-to-GAG ratio exhibited the greatest correlation to damage (correlation coefficient of approximately -0.7 with a 95% confidence interval of approximately -0.87 to -0.38 for both). In conclu (open full item for complete abstract)

Committee: James Dennis Ph.D. (Advisor); Joseph Mansour Ph.D. (Advisor); Horst von Recum Ph.D. (Committee Chair); Eben Alsberg Ph.D. (Committee Member) Subjects: Biomechanics; Biomedical Engineering; Biomedical Research; Engineering; Materials Science

Master of Science in Civil Engineering, University of Toledo, 2014, Civil Engineering

The use of Lamb waves to investigate damage in thin metal plates is investigated. This study is necessary to have a thorough understanding of Lamb wave propagation characteristics, its dispersion phenomena, its behavior when scattered from minor flaws, and its ability to detect damages. Nowadays, there is a growing interest to use Lamb waves for damage detection techniques. A literature review of Lamb waves and other types of waves pertinent to their use in damage detection mechanisms is presented. Dispersion curves for aluminum plates are studied for symmetric and anti-symmetric modes. Detailed comparison between the different modes, and the merits and demerits of these wave modes which help to select an appropriate mode for use in damage detection is also explained. Different types of damage have been detected experimentally using a pitch-catch method and are verified by using Waveform Revealer and finite element software, Pzflex. Based on selected fundamental Lamb wave modes, damage inflicted by drilling a through-thickness hole in an aluminum plate has been detected experimentally using a pitch-catch method by applying mode conversion phenomena and is verified by using Waveform Revealer. Moreover, different sizes of through-thickness holes and cracks in an aluminum plate have been detected by running simulations in Pzflex and using changes in time of flight and amplitude of the wave as parameters. Based on the experimental and simulation results, it is concluded in this paper that Lamb waves are sensitive to cracks and holes in thin aluminum plates, and that these types of defects can be detected by techniques using Lamb waves.

Committee: Douglas Nims Dr. (Advisor); Brian Randolph Dr. (Committee Member); Daniel Georgiev Dr. (Committee Member) Subjects: Engineering

MS, University of Cincinnati, 2008, Engineering : Mechanical Engineering

Vibration based damage detection of engineering structures has become an important and difficult issue for the last couple of decades. Research in vibration based structural damage detection has been rapidly expanding from traditional modal parameter estimation based techniques to modern feature based, online monitoring techniques. However, there is still a need for a universal structural damage detection method that does not depend on modal parameter estimation, finite element model or specific structural type. This research outlines and validates a Unified Matrix Polynomial Approach (UMPA) and subspace analysis based structural damage detection method. UMPA presents a theoretical basis and a fundamental mathematical framework for experimental modal parameter estimation algorithms while Singular Value Decomposition (SVD) based subspace analysis provides an mechanism to extract and compare the characteristic features from this mathematical framework to detect structural damage. Simulations were performed on an analytical 15 Degree of Freedom (DOF) mass-spring-damper system and a lightly damped circular plate finite element model to validate and assess the proposed structural damage detection method. The results show that the proposed method successfully identifies structural damage under all test conditions. The proposed method has a significant resistance to measurement uncertainty, has a good consistency with the severity of the damage and is applicable to various structural damage locations.

Committee: Randall J. Allemang PhD (Committee Chair); Teik C. Lim PhD (Committee Member); Allyn W. Phillips PhD (Committee Member) Subjects: Mechanical Engineering

MS, University of Cincinnati, 2006, Engineering : Mechanical Engineering

The United States economy is heavily dependent upon a vast network of pipeline systems to transport and distribute the nation's energy resources. As this network of pipelines continues to age, monitoring and maintaining its structural integrity remains essential to the nation's energy interests. Numerous pipeline accidents over the past several years have resulted in hundreds of fatalities and billions of dollars in property damages. These accidents show that the current monitoring methods are not sufficient and leave a considerable margin for improvement. To avoid such catastrophes, more thorough methods are needed. As a solution, the research of this thesis proposes a structural health monitoring (SHM) system for pipeline networks. By implementing a SHM system with pipelines, their structural integrity can be continuously monitored, reducing the overall risks and costs associated with current methods. The proposed SHM system relies upon the deployment of macro fiber composite (MFC) patches for the sensor array. Because MFC patches are flexible and resilient, they can be permanently mounted to the curved surface of a pipeline's main body. From this location, the MFC patches are used to monitor the structural integrity of the entire pipeline. Two damage detection techniques, guided wave and impedance methods, were implemented as part of the proposed SHM system. However, both techniques utilize the same MFC patches. This dual use of the MFC patches enables the proposed SHM system to require only a single sensor array. The presented Lamb wave methods demonstrated the ability to correctly identify and locate the presence of damage in the main body of the pipeline system, including simulated cracks and actual corrosion damage. The presented impedance methods demonstrated the ability to correctly identify and locate the presence of damage in the flanged joints of the pipeline system, including the loosening of bolts on the flanges. In addition to damage to the actual pip (open full item for complete abstract)

Committee: Dr. Randall Allemang (Advisor) Subjects: Engineering, Mechanical

MS, University of Cincinnati, 2003, Engineering : Mechanical Engineering

Detecting damage in structures that are in service and operating is difficult using conventional non-destructive evaluation techniques. This thesis examines the use of acoustic emission and resulting waves in the structure to determine damage in the structure. In order to detect and measure the waves generated continuous sensors are used. Continuous sensors contain multiple interconnected sensor nodes that form an array of sensors covering the whole structure. A new concept of active fiber composite sensor is added to the continuous sensor. The use of active fiber sensor brings the possibility of unidirectional sensing in continuous sensor. The advantage of this passive health monitoring approach is that the sensors are highly distributed and uses parallel processing allowing large structures to be monitored for damage using a small number of channels of data acquisition. In the thesis, the continuous sensor is modeled and simulated by solving the elastic response of a plate and the coupled piezoelectric constitutive equations. The model and simulation allow the sensor to be optimized for a particular material and plate size. The simulation predicts that acoustic waves representative of damage growth can be detected using continuous sensors. The simulation results show the possibility of unidirectional sensing and give some insight into the sensor response. Based on the simulation results the unidirectional sensor are constructed and tested. To improve the sensitivity of the continuous sensor, unidirectional active fiber composite sensors were built from piezoceramic ribbon preforms. Different designs and sensor configurations are examined and advantages are discussed. The sensor design proposed is manufactured in Smart Structures and Bio-Nanotechnology Laboratory. Step by step manufacturing of the active fiber composite sensors is also discussed in the thesis. The continuous sensors constructed in the lab are evaluated in a realistic test to show their ability to d (open full item for complete abstract)

Committee: Dr. Mark J. Schulz (Advisor) Subjects: Engineering, Mechanical

Doctor of Philosophy, The Ohio State University, 2005, Civil Engineering

A multi-paradigm nonparametric model, dynamic fuzzy wavelet neural network (WNN) model, is developed for structural system identification of three dimensional highrise buildings. The model integrates chaos theory (nonlinear dynamics theory), a signal processing method (wavelets), and two complementary soft computing methods (fuzzy logic and neural network). An adaptive Levenberg-Marquardt-least-squares learning algorithm is developed for adjusting parameters of the dynamic fuzzy WNN model. The methodology is applied to one five-story test frame and two highrise moment-resisting building structures. Results demonstrate that the methodology incorporates the imprecision existing in the sensor data effectively and balances the global and local influences of the training data. It therefore provides more accurate system identifications and nonlinear approximation with a fast training convergence. A nonparametric system identification-based model is developed for damage detection of highrise building structures subjected to seismic excitations using the dynamic fuzzy WNN model. The model does not require complete measurements of the dynamic responses of the whole structure. A damage evaluation method is proposed based on a power density spectrum method. The multiple signal classification method is employed to compute the pseudospectrum from the structural response time series. The methodology is validated using experimental data obtained for a 38-story concrete test model. It is demonstrated that the WNN model together with the pseudospectrum method is effective for damage detection of highrise buildings based on a small amount of sensed data. A nonlinear control model is developed for active control of highrise three dimensional building structures including geometrical and material nonlinearities, coupling action between lateral and torsional motions, and actuator dynamics. A dynamic fuzzy wavelet neuroemulator is developed for predicting the structural response in futur (open full item for complete abstract)

Committee: Hojjat Adeli (Advisor) Subjects: Engineering, Civil

Bachelor of Science in Applied Science, Miami University, 2005, School of Engineering and Applied Science - Manufacturing Engineering

Health monitoring of structures aims to characterize, asses, and predict damage initiation and propagation. Studies in this field are utilized to provide a damage analysis of structures that allows time-consuming inspections to be avoided. The aim of this work is to use experimental and computational tools to identify key parameters that characterize damage initiation and propagation. More specifically, this thesis will focus on experimental and computational modeling of damaged and healthy automotive exhaustive hangers to determine the main mechanical parameters that will serve to identify damage. The results obtained from computer simulations and laboratory experiments are thoroughly compared and analyzed to observe the changes in mechanical properties of the structure. The evolution of damage in the structure will translate in alterations in its mechanical properties. This report starts by providing a brief introduction to the field of health monitoring and a literature review of available methods for damage identification and prediction. The research approach is also described to introduce the reader to the main tools used in this study. Sections on experimental and computational analysis of the results follow which provides the main findings of this work. Finally, the conclusions and future work section of the report provides a summary of the main findings and the potential usage of these in future studies in the field of prognosis.

Committee: Amit Shukla (Advisor) Subjects: Engineering, Mechanical

Master of Science in Mechanical Engineering, Cleveland State University, 2009, Fenn College of Engineering

The objective of this thesis is to explore an innovative approach to the on-line health monitoring of rotating machinery in the presence of structural damage using active magnetic bearings (AMBs). First, the detailed model of the rotor with the breathing transverse crack is developed using finite element method. Next, the experimental data from the rotating magnetically levitated healthy and cracked shafts, under specially designed external excitation force, was collected, analyzed and compared with the computer simulation. The obtained results demonstrate that the presented on-line health monitoring technique is very effective for detection of the structural damage in rotating machinery, and it has a potential to be effectively applied in industry.

Committee: Dr. Jerzy Sawicki PhD (Committee Chair); Dr. John Frater PhD (Committee Member); Dr. Ana Stankovic PhD (Committee Member); Dr. John Lekki PhD (Committee Member) Subjects: Electromagnetism; Engineering; Mechanical Engineering

Master of Science, University of Akron, 2005, Civil Engineering

There is a pressing need to develop effective techniques for structural health monitoring (SHM), so that the safety and integrity of the structures can be improved. The main objective of this study is to evaluate the dynamics-based damage detection techniques for the plate-type structures using smart piezoelectric materials and modern instrumentation like Scanning Laser Vibrometer (SLV). The study comprises of testing an E-glass/epoxy composite plate with an embedded delamination and an aluminum plate with a saw-cut crack using two different actuator-sensor systems: (1) SLV with PZT (lead-zirconate-titanate) actuators (PZT-SLV), and (2) Polyvinylidenefluoride (PVDF) sensors with PZT actuators (PZT-PVDF). The numerical finite element (FE) analysis is also performed to complement the damage detection. Three relatively new damage detection algorithms (i.e., Simplified Gapped Smoothing Method (GSM), Generalized Fractal Dimension (GFD), and Strain Energy Method (SEM)) are employed to analyze the experimental and numerical mode shape data and Uniform Load Surface (ULS). From the damage detection outcomes, it is observed that the PZT-SLV system proves to be more convenient and effective, and it is capable of scanning a large number of points over the entire plate specimens; while the PZT-PVDF system, in which the curvature mode shapes are directly acquired, exhibits good sensitivity to damage. The damage detection algorithms like the GSM, GFD and SEM based on the utilization of three consecutive mode curvatures (modes 3 to 5) and resulting ULS curvature successfully identify the presence and location of delamination in the composite plate; however, they do not show much success in locating the saw-cut crack in the aluminum plate with the same mode curvatures. Using the transverse bending dominated modes (e.g., modes 6 and 12), the above damage detection algorithms are capable of locating the saw-cut crack in the aluminum plate. Due to refined analysis of FE approach, all t (open full item for complete abstract)

Committee: Pizhong Qiao (Advisor) Subjects: