Monitoring the integrity of civil engineering structures is an imperative aspect of public safety, since structural failures can pose serious threats to life and property. Periodic inspection performed throughout the life span of these structures is also vital for a nation’s economy. Substantial sums of money may be saved upon detecting structural deterioration in a timely manner. Nondestructive damage evaluation (NDE) offers effective and economically feasible solutions to perform such tasks. Better predictions can be made regarding the current state of structures, and structurally deficient regions that need immediate attention may successfully be narrowed down by utilizing NDE. For these reasons, a considerable amount of research has been conducted in the field of NDE over the past few decades. As a result, many different methodologies are now available, and many new ones continue to emerge as the need for better evaluation techniques prevails. Upon reviewing the NDE methodologies proposed to date, it may be concluded that theories based on the fundamental equations of mechanics and mathematics in conjunction with justifiable assumptions provided the best results compared to the algorithms developed pragmatically. The goal of this study is to provide NDE methodologies that simultaneously identify the location, the extent, and the severity of damage in general beams. By general beams, we mean beyond Euler-Bernoulli beams (i.e. slender beams) to deep beams and stubby beams whose response may be based on the Timoshenko beam theory, and the Theory of Elasticity. After presenting the governing equations of equilibrium and stress-displacement relations of the fundamental beam theories including the Euler-Bernoulli Beam theory, the Timoshenko beam theory, and the beam theory based on linear Elasticity Theory, mathematical expressions which relate physical properties (e.g. stiffness) of the undamaged and damaged structure to measurable response quantities (e.g. displacement, strains, etc.) are developed. We believe that these algorithms will lead to earlier and more accurate prediction of damage in critical structures. The findings of this work will also lead to a better understanding of the limitations of the currently proposed NDE techniques. In addition, it is anticipated that by incorporating the methodologies proposed in this study to the continuous health monitoring of structural systems could reduce the cost of maintenance and offer safer infrastructure networks.

The objective of this research is to develop a theoretical Structural Impairment Detection System (SIDS) for timber railway bridges. Due to fatigue, the timber stringers in timber railway bridges develop shear cracks. These shear cracks lead to higher bridge deflections, higher stresses in the stringers and rail, and shorter fatigue life of the system. A SIDS is proposed which links wheel path accelerations obtained from traversing freight cars to the condition of the bridge. In order to develop the SIDS, two models of timber railway bridges with various levels of structural impairment were developed. The first model was a quasi-static model developed from classical beam theory and implemented in MATLAB. The second model was a dynamic, finite element model created in LS-DYNA. Traversing axle loads were imposed on the models. The results obtained from the model were the wheel paths the axles take as they traverse the bridge. The paths were expressed as vertical displacements as a function of position on the bridge. Wheel path accelerations were obtained by numerically differentiating the vertical displacements. The accelerations were then used to train neural networks to have an input of an acceleration vector and an output of a bridge condition vector. The neural networks were trained on results from both models under three train speeds: 40 mph, 30 mph, and 20 mph. The networks were able to determine the correct bridge condition 90% of the time when the train speed was 40 mph and 70% of the time when the train speed was 30 mph. The networks were not successful in determining bridge condition when the train speed was 20 mph.

As the UH-1 aircraft continue to age, there is growing concern for their structural integrity. With corrosion damage becoming a bigger part of the sustainment picture with increasing maintenance burden and cost, it is becoming increasingly important for corrosion management to be updated with more advanced techniques. The current find-and-fix technique for handling corrosion has many shortfalls, spurring the recent interest in early detection through structural health monitoring. This condition based technique is becoming more prevalent and is recognized for the potential to greatly reduce maintenance cost. Through corrosion monitoring, structural and environmental conditions can be closely observed, preventing excessive maintenance action and saving cost. Searches for corrosion monitoring system designs revealed several commercial companies with prototype systems installed on commercial aircraft, however, details on system design and data analysis were scarce. This study attempted to bridge the gap in literature by providing insight into the development of a corrosion damage prediction model and the design of a corrosion monitoring system. This study attempted to use aircraft maintenance data to make prediction models for determining what corrosion damage an aircraft can expect, given varying operating conditions. Although a reliable prediction model could not be created, trends observed in the data were still valuable for identifying problematic areas of the aircraft. In order to create reliable models, more accurate corrosion data is needed. This can be accomplished through the implementation of a corrosion monitoring system. A custom corrosion monitoring system was designed for the UH-1 aircraft. Commercial off-the-shelf products were fit to the design and a benefits-to-cost analysis was performed for the monitoring system, evaluating the system based on criteria developed from user requirements. The system proved to meet and exceed expectation, making it an ideal choice for the UH-1 aircraft.

Highway bridges are vital links in any transportation network. Identifying the possible safety problems in the approximately 600,000 bridges across the U.S. is generally accomplished through labor-intensive, visual inspections. Wireless monitoring technology seeks to improve current practices by supplementing the visual inspections with real-time evaluation of bridges. To be economically feasible, wireless sensor networks should be able to (a) operate independent of the power grid, and (b) achieve a service life of at least ten years. Novel energy harvesting approaches have been investigated to fulfill these two criteria. In particular, the feasibility of a vibration energy harvester as a long-term power source was assessed. The goal of the research was to process measured acceleration data and analyze the vibrational response of typical highway bridges under truck loads. The effects of ambient temperature, truck traffic patterns, and harvester position on the power content of the vibrations were explored, as well as the effects of linear and nonlinear harvesters. This thesis presents the results of evaluating the response of five steel bridges in Texas and Oregon for energy harvesting applications. / text

Ageing mechanical, civil, aerospace, marine and offshore structures require continuous and accurate assessment on their integrity to avoid potentially hazardous failures. To further facilitate this crucial demand, a new technical terminology, generally referred to as structural health monitoring (SHM) has been coined in three past decades. SHM involves deployment of a sensory network on such structures in order to gather useful data, such that processing and interpreting the data through specific algorithms would enable one to detect defects and anomalies within the structures. This dissertation presents the results of a series of efforts expended towards the refinement and enhancement of a vibration-based SHM technique, which was originated within our research group. In the adopted damage detection scheme, vibration data are gathered from structures via piezoelectric sensors. Data are processed by a robust signal processing approach, known as the empirical mode decomposition (EMD) in order to establish energy-based damage indices (EMD_EDIs). Interpretation of the damage indices enables detection of onset, location and advancement of defects within structures. A series of adjustments and modifications were devised and implemented to the application of the originally developed methodology, such that, besides increasing the methodology’s robustness and accuracy, they also facilitate a remote vibration-based SHM targeting onshore and offshore pipelines. The integrity of the method in detection of bolt-loosening in a bolted flange joint of a full-scale pipeline was verified through numerical simulations and experimental investigations. The source of a significant inconsistency reported in the previous trials was identified and resolved. Also, for the first time, the remote application of the technique was facilitated by incorporating an advanced wireless data acquisition system. Moreover, the application of the methodology was extended to detection of cracks in girth-welds of offshore pipelines. In this regard, a comprehensive discussion is first provided, which identifies the role of parameters that influence the accuracy of numerical modeling of the dynamic response of submerged structures. The experimental and numerical investigation following the aforementioned modeling efforts presents encouraging results in detection of an advancing notch in the girth-weld of a submerged pipe. The use of a piezoelectric-based excitation technique, incorporated for the first time in the application of the methodology would evidence the enhanced practicality and robustness of the approach. The study concludes with a successful detection of a real-life sharp propagating crack in a beam due to cyclic loadings.

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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.

Composite materials are supplanting conventional metals in aerospace, automotive, civil and marine industries in recent times. This is mainly due to their high strength and light weight characteristics. But with all the advantages they have, they are prone to delamination or matrix cracking. These types of damage are often invisible and if undetected, could lead to appalling failures of structures. Although there are systems to detect such damage, the criticality assessment and prognosis of the damage is often more difficult to achieve. The research study conducted here primarily deals with the structural health monitoring of composite materials by analysing vibration signatures acquired from a laser vibrometer. The primary aim of the project is to develop a vibration based structural health monitoring (SHM) method for detecting flaws such as delamination within the composite beams. Secondly, the project emphasises on the method's ability to recognise the locatio n and severity of the damage within the structure. The system proposed relies on the examination of the displacement mode shapes acquired from the composite beams using the laser vibrometer and later processing them to curvature mode shapes for damage identification and characterization. Other identification techniques such as a C-scan has been applied to validate the location and size of the defects with the structures tested. The output from these plots enabled the successful identification of both the location and extent of damage within the structure with an accuracy of 96.5%. In addition to this, this project also introduces a method to experimentally compute the critical stress intensity factor, KIC for the composite beam. Based on this, a technique for extending the defect has been proposed and validated using concepts of fatigue and fracture mechanics. A composite specimen with a 40 mm wide delamination embedded within was loaded under fatigue conditions and extension of the defect by 4mm on either s ide of the specimen's loading axis was achieved satisfactorily. The experimental procedure to extend the defect using fatigue was validated using the SLV system. Displacement and Curvature mode shapes were acquired post-fatigue crack extension. Upon analysing and comparing the displacement and curvature mode shapes before and after crack extension, the extended delamination was identified satisfactorily.

Composite materials are supplanting conventional metals in aerospace, automotive, civil and marine industries in recent times. This is mainly due to their high strength and light weight characteristics. But with all the advantages they have, they are prone to delamination or matrix cracking. These types of damage are often invisible and if undetected, could lead to appalling failures of structures. Although there are systems to detect such damage, the criticality assessment and prognosis of the damage is often more difficult to achieve. The research study conducted here primarily deals with the structural health monitoring of composite materials by analysing vibration signatures acquired from a laser vibrometer. The primary aim of the project is to develop a vibration based structural health monitoring (SHM) method for detecting flaws such as delamination within the composite beams. Secondly, the project emphasises on the method's ability to recognise the locatio n and severity of the damage within the structure. The system proposed relies on the examination of the displacement mode shapes acquired from the composite beams using the laser vibrometer and later processing them to curvature mode shapes for damage identification and characterization. Other identification techniques such as a C-scan has been applied to validate the location and size of the defects with the structures tested. The output from these plots enabled the successful identification of both the location and extent of damage within the structure with an accuracy of 96.5%. In addition to this, this project also introduces a method to experimentally compute the critical stress intensity factor, KIC for the composite beam. Based on this, a technique for extending the defect has been proposed and validated using concepts of fatigue and fracture mechanics. A composite specimen with a 40 mm wide delamination embedded within was loaded under fatigue conditions and extension of the defect by 4mm on either s ide of the specimen's loading axis was achieved satisfactorily. The experimental procedure to extend the defect using fatigue was validated using the SLV system. Displacement and Curvature mode shapes were acquired post-fatigue crack extension. Upon analysing and comparing the displacement and curvature mode shapes before and after crack extension, the extended delamination was identified satisfactorily.

In recent years, the use of composite structures in engineering application has increased. This is mainly due to their special advantages such as high structural performance, high corrosion resistance, tolerance of temperature; extreme fatigue resistance and high strength/weight ratio. However, some disorders like fibre breakage, matrix cracking and delaminations could be caused by operational loading, aging, chemical attack, mechanical vibration, changing of ambient conditions and shock etc. during the service. Although these disorders are hardly visible, they can severely reduce the mechanical properties and the load carrying capability of the composite structure. The aim of this research project is to develop a Vibration-based Structural Health Monitoring (SHM) method for carbon/epoxy composite beam specimens with the embedded artificial delaminations. The Laser Vibrometer Machine was used to excite the beams and gather the responses of the structure to the excitations. The physical properties such as frequency, velocity, mode shapes, and damping of the defective beams were measured. By using a C-SCAN machine, the accuracy of the positions of the delaminations was verified to be about 95% is accurate. Curvature mode shapes as a scalable damage detection parameter is calculated using an analytical model based on the Heaviside step function and the Central Difference Approximation (CDA) technique. The vibration-based damage detection method is then obtained using the difference between curvature mode shapes of the intact and damaged carbon/epoxy beams. An accurate prediction of 90% was attained. These results are proposed and discussed in detail in this study. Finally, the Fatigue Crack Propagation Test was applied on Samples with embedded delamination to extend the crack. The ASTM E399-90 standard is used for the experiment and a careful fatigue crack growth routine was designed and implemented to advance the delamination in a controlled manner. The total extension of 17 mm was observed with Microscope. The total propagation as determined by the curvature mode plots was 17.84 mm.