Real-time monitoring of fracture critical steel bridges can potentially enhance inspection practices by tracking the behavior of the bridge. Significant advances have occurred in recent years on the development of robust hardware for field monitoring applications. These systems can monitor, process, and store data from a variety of sensors (e.g. strain gages, crack propagation gages etc.) to track the behavior of the bridge. The research outlined in this dissertation is part of a large study focused on the development of a wireless system for use in long-term monitoring of bridges. The wireless monitoring system had a target maintenance-free life of ten years, and independent from the power grid. Thus, the feasibility to harvest energy for the monitoring system is an important step in the development of the system. In addition, the reliability of the sensors in the bridge is very important upon the success of the system. The focus of this dissertation is on two primary aspects of the wireless monitoring system. First, the feasibility to harvest energy from vehicular-induced vibrations is evaluated through analytical models of highway bridges under truck loads. Acceleration results from simple line-element models and detailed finite element models of five steel bridges in Texas and Oregon are compared with actual field data from the same bridges. Second, the dissertation also highlights studies on the identification of strain gages and installation procedures that result in long lives. In addition, the effect of temperature fluctuations and other environmental factors on the sensor drift and noise is also considered. In long-term monitoring applications, slight sensor drift and noise can build up over time to produce misleading results. This dissertation presents the results of transient dynamic analyses of bridges under moving truck loading and laboratory tests on gage durability that were conducted as part of a research project sponsored by the National Institute of Standards and Technology (NIST). / text

As the demands to monitor the health status of structures increase, researchers around the world have proposed several concepts to solve this issue. This research first examines the existing technologies and then works toward a novel structural health monitoring solution. A comprehensive discussion includes major topics from sensor selection and installation to sensing data display. A cyber-physical system combining embedded system, wireless communication, and the Java platform was developed for structural health monitoring. The focus of this system is to continuously monitor structural response and broadcast the information to users worldwide via the Internet. A wireless sensor node is designed to connect up to eight sensor channels. Various sensors have been tested on the sensor node. A data acquisition and repository system was also developed. The use of the Java language makes this system capable of running in virtually any existing computer platform. Distributed design concept expands its functionalities and capabilities. Its graphical user interface offers users a friendly and ease-of-use environment to monitor real-time and historical data in both graphical and numerical ways. Every component of the system has been validated to verify its functionality. Additionally, the whole system has been implemented on a steel pedestrian bridge to observe its performance.

The use of IGBT power modules in the automotive industry is becoming increasingly common as manufacturers develop more hybrid and all electric vehicles. In an industry such as this, the reliability of a component is critical and vehicle manufacturers have conducted much research into diagnostic and prognostic systems for internal combustion engines that run in real time on the vehicle to determine when components will fail. Power electronic components do not have similar prognostics available. The traditional use of power electronic modules has been in applications where their life or duty cycle is well defined, and accelerated life tests are carried out to determine a mean time to failure. This type of prognostics is not appropriate for the automotive industry because the operating cycle of the vehicle varies greatly, both in driving style, duty cycle and environment. A new type of prognostics is therefore required which will calculate the life remaining in the power module in real time as the device is being used.Because of the high robustness of IGBT power modules, testing for time to failure can be a very lengthy process. A novel procedure and test rig based on Peltier effect thermoelectric coolers was developed, which can automatically temperature cycle IGBT power modules in a very short time and determine their life expectancy, all within their operating specifications. This was tested using several power modules. The failure modes of IGBT power modules are also investigated with a view to developing a failure prediction algorithm. The causes of failure are analysed and a prognostics algorithm is proposed. This prognostics algorithm uses thermal cycle history as a means to predict the life consumed for the power module. The data obtained by the accelerated life tests is used to calculate the coefficients for the prognostic algorithm. A simulation of a vehicle drive cycle is used to show how the prognostics algorithm can be used, and a value indicating the extent to which the IGBT power module has aged is calculated. It is also proved that by intelligently controlling the heat flowing from the heat sink on which the power module is mounted, the life of the IGBT power module can be increased by approximately three times.Hardware and software were developed to implement the health monitoring algorithm. Measurement and control circuits were designed, built and tested together with software that processes the input data, records the thermal cycle history of the IGBT power modules and calculates a value of age for the IGBT power modules in real time. This was tested on several modules to prove the validity of the algorithm.The new algorithms and methodology developed could enable vehicle manufacturers to predict the failure of power modules in hybrid and all electric vehicles. This technology could also benefit other industries such as the renewables (eg wind turbines) and aerospace, where the industry is moving towards all electric aircraft.

This thesis examines the value of using dispersed conductive fillers as a stress/strain sensing material. The effect of the intrinsic conductivity of the filler on the ability to be effective and the influence of filler concentration on the conductivity are also examined. To meet these objectives, nanocomposites of polyvinylidene fluoride (PVDF) with carbon nanofibers (CNFs) and carbon nanotubes (CNTs) were prepared by melt-blending using a twin screw extruder. Since PVDF has a potential to be piezoresistive based on the type of crystalline phase, the effect of CNFs on PVDF crystallinity, crystalline phase, quasi static and dynamic mechanical property was studied concurrently with piezoresponse. Three time dependencies were examined for PVDF/CNTs nanocomposites: quasi-static, transient and cyclic fatigue. The transient response of the strain with time showed viscoelastic behavior and was modeled by the 4-element Burger model. Under quasi-static loading the resistance showed negative pressure coefficient below yield but changed to a positive pressure coefficient after yield. Under cyclic load, the stress-time and resistance-time were synchronous but the resistance peak value decreased with increasing cycles, which was attributed to charge storage in the nanocomposite. The outcomes of this thesis indicate that a new piezoresponsive system based on filled polymers is a viable technology for structural health monitoring.

Bisphenol A (BPA), an endocrine disruptor, requires monitoring in water for health safety. Glutamate, H2O2, and glucose are vital biomarkers for various diseases. However, lab-based methods are expensive, time-consuming, and require skilled personnel, making them unsuitable for point-of-care (POC) devices. The electrochemical sensor enables POC device development. However, it suffers from low sensitivity and selectivity. This thesis focuses on the use of nanomaterials to enhance the sensitivity and selectivity of electrochemical sensors to monitor BPA in water, along with glutamate, H2O2, and glucose in bio-fluids. A BPA sensor was developed using chemically modified MWCNTs with βCD on a screen-printed carbon electrode (SPCE). The MWCNTs-βCD/SPCE exhibited high sensitivity, attributed to the catalytic activity of MWCNTs and the host-guest interaction ability of βCD. It provided a linear range (LR) of 125 nM −30 µM, with a limit of detection (LOD) of 13.76 nM (SNR = 3). We improved the performance by curing the MWCNTs-βCD/SPCE with CTAB. The sensor demonstrated a dynamic range of 500 fM to 10 μM, with a LOD of 96.5 fM, surpassing the Canada-assigned PNEC of BPA in water (0.77 nM). We fabricated a nonenzymatic glutamate sensor using CuO nanostructures and MWCNTs on SPCE. The sensor showed irreversible oxidation of glutamate involving one electron and one proton, and an LR of 20 μM−200 μM with LOD of 17.5 μM and sensitivity of 8500 μAmM−1cm−2. The sensor is promising to detect glutamate in blood. We developed a nonenzymatic glucose sensor using green synthesized gold nanoparticles and CuO-modified SPCE. The LR offered by the sensor (2 µM to 397 µM) is suitable for quantifying saliva glucose. We also created nonenzymatic H2O2 sensor by green synthesized silver nanoparticles modified SPCE which offers LR of 0.5- 161.8 µM with LOD 0.3 µM which is capable of H2O2 monitoring in urine. / Thesis / Doctor of Philosophy (PhD) / Bisphenol A (BPA) is a plastic pollutant and an endocrine-disrupting chemical that causes reproductive and neurodevelopmental disorders, and many diseases including obesity, diabetes, and cardiovascular disease. In addition, glutamate, hydrogen peroxide (H2O2), and glucose are vital biomarkers for various acute and chronic diseases. These diseases impose significant burdens on individuals, healthcare systems, and the economy. Therefore, they must be monitored. In this thesis, we developed a BPA sensor using chemically modified multiwall carbon nanotubes (MWCNTs) with β-cyclodextrin (βCD) and cetrimonium bromide (CTAB) which can detect BPA at very low concentration beyond Canada-assigned predicted-no-effect-concentrations (PNEC) of BPA. We also developed a glutamate sensor using MWCNTs and wet chemically synthesized copper oxide (CuxO) nanostructure which offers a linear range related to blood glutamate level. Moreover, we fabricated nonenzymatic H2O2 and glucose sensors using green synthesized gold (AuNPs) and silver (AgNPs) nanoparticles (using orange peel extraction as a reducing and stabilizing agent) which are useful to quantify urine H2O2 and saliva glucose respectively.

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With increasing applications of composite materials, their health monitoring is of growing importance in engineering practice. Damage development in composite materials is more complex than for metallic materials, because in composite materials (a) multiple damage modes are simultaneously in play, and (b) individual 'damage events' that occur throughout a component's service life may neither noticeably affect its performance, nor suggest future failure. Therefore, informed health monitoring of composite components must include monitoring and analysis of their health state throughout their service life. A crucial aspect of the health monitoring process of composites is the development of tools to help with this goal of understanding the health state of composites throughout their life. This knowledge can lead to timely anticipation of future failure in composite components, and advance the state of current technology. One, timely maintenance can be planned in advance. Two, each component's service life can be determined based on its individual health information, rather than empirical statistics of previously failed components. This dissertation develops such tools and methods. Composite specimens of multiple ply-layups are subjected to tensile loading schemes until failure. Pencil Lead Breaks (PLBs) are used to simulate Acoustic Emission sources and generate acoustic waves that are acquired by installed piezoelectric sensors. A numerical method to estimate the arrival of wave modes from ultrasonic signals is presented. Methods are also presented that utilize PLB signals to indicate approaching failure of specimens under monotonic as well as cyclic loading. These processes have been developed prioritizing simplicity and ease-of-execution, to be adapted for practical deployment. / Ph. D.

Fiber reinforced polymers (FRP) are an efficient and inexpensive method of repairing deteriorating infrastructure. FRP sheets can be applied to spalling bridge sections and columns to prevent further deterioration and increase stiffness. However, the effect of the environment on the long-term durability of FRP and how the various damage mechanisms initiate and develop are not known. Systems for structural health monitoring are being sought as a means of managing important components in transportation systems as assets in light of modern life cycle cost concepts. This study characterizes a fiber optic sensor for use in detecting acoustic emissions (AE) in FRP. The results of AE analysis (signal amplitude, frequency spectra, MARSE, and in-plane displacement) caused by simulated fiber fracture experiments and other types of mechanical loading in FRP test coupons are reported. The applications to the development of FRP structural health monitoring systems are also discussed. / Master of Science

Vibration structural health monitoring (VHM) uses the vibration properties to evaluate many civil structures during the design steps, building steps and service life.The whole function, expressed by stiffness and frequencies of tensegrity structures are primarily related to the level of pre-stress. The present work investigates the possibilities to use this relation in designing, constructing and evaluating the tensegrity structures.One of the aims of the thesis was to improve the current models for resonance frequency simulation of tensegrities. This has been achieved by introducing the bending behaviour of all components, and by a one-way coupling between the axial force and the stiffness.The environmental temperature effects on vibration properties of tensegrity structures have been also  investigated. Changes in dynamic characteristics due to temperature variations were compared with the changes due to decreasing pre-tension in one of the cables. In general, it is shown that the change in structural frequencies coming from temperature changes could of several magnitude as those from damage.Coinciding natural frequencies and low stiffness are known issues of tensegrity structures. The former can be an obstacle in VHM, while the later normally limits their uses in real engineering applications. It has been shown that the optimum self-stress vector of tensegrity structures can be chosen such that their lowest natural frequency is high, and separated from others.The environmental temperature effects on vibration properties of tensegrity structures were revisited to find a solution such that the natural frequencies of the tensegrity structures are not strongly affected by the changes in the environmental temperature. An asymmetric self-stress vector can be chosen so that the criterion is fulfilled as well as possible. The level of pre-stress can also be regulated to achieve the solution. The last part of this thesis, services as a summary of the work. / <p>QC 20160429</p>