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<p dir="ltr">The research in this thesis focuses on developing an alert system to detect damage or impact on bridge. It employs Raspberry Pi and accelerometers for real-time health monitoring. The methodology includes bridge model creation, testing under no damage, impact, and structural damage conditions, and data processing for vibration frequency analysis. The aim is to differentiate between normal bridge conditions, collisions, and structural damages, providing timely notifications for necessary investigations or repairs. The study addresses the challenges in bridge safety and aims to improve maintenance efficiency and reliability.</p><p><br></p>

Detecção de dano em estruturas de engenharia de grandes dimensões através da análise de suas características dinâmicas envolve diversos campos de estudo. O primeiro deles trata da identificação dos parâmetros modais da estrutura, uma vez que executar testes de vibração livre em tais estruturas não é uma tarefa simples, necessita-se de um método robusto que seja capaz de identificar os parâmetros modais dessa estrutura a ações ambientais, campo esse chamado de análise modal operacional. Este trabalho trata do problema de detecção de dano em estruturas que possam ser representadas através de modelos em pórticos planos e vigas e que estejam submetidos à ação de vibrações ambientais. A localização do dano é determinada através de um algoritmo de otimização conhecido como Backtracking Search Algorithm (BSA) fazendo uso de uma função objetivo que utiliza as frequências naturais e modos de vibração identificados da estrutura. Simulações e testes são feitos a fim de verificar a concordância da metodologia para ambos os casos. Para as simulações, são utilizados casos mais gerais de carregamentos dinâmicos, e dois níveis de ruído (3% e 5%) são adicionados ao sinal de respostas para que esses ensaios se assemelhem aos ensaios experimentais, onde o ruído é inerente do processo. Já nos ensaios experimentais, apenas testes de vibração livre são executados. Diversos cenários de dano são propostos para as estruturas analisadas a fim de se verificar a robustez da rotina de detecção de dano. Os resultados mostram que a etapa de identificação modal estocástica através do método de identificação estocástica de subespaço (SSI) teve ótimos resultados, possibilitando, assim, a localização da região danificada da estrutura em todos os casos analisados. / Damage detection in large dimensions engineering structures through the analysis of their dynamic characteristics involves several fields. The first one deals with the structure modal identification parameter, since running free vibration tests in such structures is not a simple task, robust methods are needed in order to identify the modal parameters of this structure under ambient vibrations, this field is known as operational modal analysis. This work deals with the problem of damage detection in structures under ambient vibrations that can be represented by FEM using frame and beam elements. The damage location is determined through an optimization algorithm know as Backtracking Search Algorithm (BSA). It uses as objective function the identified natural frequencies and modes of vibration of the structure. Numerical and experimental tests are performed to assess the agreement of the methodology for both cases. For the numerical tests, more general cases of dynamic loads are used, and two noise levels (3% and 5%) are added to the response signal to assessing the robustness of the methodology close to the field conditions, in which noise is inherent of the process. In the experimental tests, only free vibration tests are performed. Several damage scenarios are proposed for the analyzed structures to check the robustness of the damage detection routine. The results show that the stochastic modal identification using the stochastic subspace identification (SSI) method had excellent results, thus allowing the location of the damaged region of the structure in all analyzed cases.

Submitted by Danilo Ecidir Budoya (dbudoya.eng@gmail.com) on 2018-04-25T21:17:47Z No. of bitstreams: 1 Dissertação - Danilo Budoya.pdf: 3474646 bytes, checksum: 301f48ae4a6c065e915f91fe3d764dd8 (MD5) / Approved for entry into archive by Minervina Teixeira Lopes null (vina_lopes@bauru.unesp.br) on 2018-04-26T12:29:49Z (GMT) No. of bitstreams: 1 budoya_de_me_bauru.pdf: 3415870 bytes, checksum: 35422f7801e20a052d2c9a303aa7e2dd (MD5) / Made available in DSpace on 2018-04-26T12:29:49Z (GMT). No. of bitstreams: 1 budoya_de_me_bauru.pdf: 3415870 bytes, checksum: 35422f7801e20a052d2c9a303aa7e2dd (MD5) Previous issue date: 2018-04-20 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Sistemas de monitoramento de integridade estrutural (SHM – Structural Health Monitoring) são científica e economicamente relevantes como métodos de detecção de danos estruturais em diversos tipos de estruturas, aumentando assim a segurança e reduzindo os custos de manutenção. Entre os vários princípios de detecção de danos, o método da impedância eletromecânica (E/M) baseia-se na medição da impedância elétrica do transdutor piezelétrico fixado à estrutura monitorada. Aqui, a exatidão e precisão do sistema de medição são fundamentais para o diagnóstico correto da estrutura. Portanto, essa dissertação apresenta uma análise comparativa de duas técnicas de medição de impedância para detecção de danos que são tipicamente utilizadas em analisadores de impedância comerciais e em outros sistemas de medição alternativos: medições em estado transitório utilizando um sinal de excitação de varredura e medições em estado estacionário utilizando um sinal senoidal puro para cada frequência de excitação. Os testes foram realizados com cargas resistivas e capacitivas de valores nominais 100 Ω e 10 nF, respectivamente, e com um transdutor piezelétrico fixado em uma barra de alumínio que representa uma estrutura monitorada. As duas técnicas foram comparadas com base na exatidão, precisão, sensibilidade à danos e tempo necessário para as medições. Os resultados destacam as características importantes de cada técnica, as quais devem ser consideradas para o desenvolvimento de sistemas de SHM baseados na impedância e o diagnóstico correto das estruturas monitoradas. / Structural health monitoring (SHM) systems are scientifically and economically relevant as methods of detecting structural damage to various types of structures, thus increasing safety and reducing maintenance costs. Among the various principles of damage detection, the electromechanical impedance (EMI) method is based on the electrical impedance measurement of piezoelectric transducers attached to the monitored structure. Here, the accuracy and precision of the measurement system are fundamental for the correct diagnosis of the structure. Therefore, this dissertation presents a comparative analysis of two impedance measurement techniques for damage detection that are typically used in commercial impedance analyzers and other alternative measurement systems: transient-state measurements using a sweep excitation signal and steady-state measurements using a pure sinusoidal signal for each excitation frequency. Tests were performed with resistive and capacitive loads with nominal values of 100 Ω e 10 nF, respectively, and a piezoelectric transducer fixed to an aluminum bar representing a monitored structure. The two techniques were compared based on the accuracy, precision, sensibility to damage and time required for the measurements. The results highlight the important features of each technique, which should be considered for the development of impedance-based SHM systems and the correct diagnosis of monitored structures. / 2015/23272-1

Detecção de dano em estruturas de engenharia de grandes dimensões através da análise de suas características dinâmicas envolve diversos campos de estudo. O primeiro deles trata da identificação dos parâmetros modais da estrutura, uma vez que executar testes de vibração livre em tais estruturas não é uma tarefa simples, necessita-se de um método robusto que seja capaz de identificar os parâmetros modais dessa estrutura a ações ambientais, campo esse chamado de análise modal operacional. Este trabalho trata do problema de detecção de dano em estruturas que possam ser representadas através de modelos em pórticos planos e vigas e que estejam submetidos à ação de vibrações ambientais. A localização do dano é determinada através de um algoritmo de otimização conhecido como Backtracking Search Algorithm (BSA) fazendo uso de uma função objetivo que utiliza as frequências naturais e modos de vibração identificados da estrutura. Simulações e testes são feitos a fim de verificar a concordância da metodologia para ambos os casos. Para as simulações, são utilizados casos mais gerais de carregamentos dinâmicos, e dois níveis de ruído (3% e 5%) são adicionados ao sinal de respostas para que esses ensaios se assemelhem aos ensaios experimentais, onde o ruído é inerente do processo. Já nos ensaios experimentais, apenas testes de vibração livre são executados. Diversos cenários de dano são propostos para as estruturas analisadas a fim de se verificar a robustez da rotina de detecção de dano. Os resultados mostram que a etapa de identificação modal estocástica através do método de identificação estocástica de subespaço (SSI) teve ótimos resultados, possibilitando, assim, a localização da região danificada da estrutura em todos os casos analisados. / Damage detection in large dimensions engineering structures through the analysis of their dynamic characteristics involves several fields. The first one deals with the structure modal identification parameter, since running free vibration tests in such structures is not a simple task, robust methods are needed in order to identify the modal parameters of this structure under ambient vibrations, this field is known as operational modal analysis. This work deals with the problem of damage detection in structures under ambient vibrations that can be represented by FEM using frame and beam elements. The damage location is determined through an optimization algorithm know as Backtracking Search Algorithm (BSA). It uses as objective function the identified natural frequencies and modes of vibration of the structure. Numerical and experimental tests are performed to assess the agreement of the methodology for both cases. For the numerical tests, more general cases of dynamic loads are used, and two noise levels (3% and 5%) are added to the response signal to assessing the robustness of the methodology close to the field conditions, in which noise is inherent of the process. In the experimental tests, only free vibration tests are performed. Several damage scenarios are proposed for the analyzed structures to check the robustness of the damage detection routine. The results show that the stochastic modal identification using the stochastic subspace identification (SSI) method had excellent results, thus allowing the location of the damaged region of the structure in all analyzed cases.

Detecção de dano em estruturas de engenharia de grandes dimensões através da análise de suas características dinâmicas envolve diversos campos de estudo. O primeiro deles trata da identificação dos parâmetros modais da estrutura, uma vez que executar testes de vibração livre em tais estruturas não é uma tarefa simples, necessita-se de um método robusto que seja capaz de identificar os parâmetros modais dessa estrutura a ações ambientais, campo esse chamado de análise modal operacional. Este trabalho trata do problema de detecção de dano em estruturas que possam ser representadas através de modelos em pórticos planos e vigas e que estejam submetidos à ação de vibrações ambientais. A localização do dano é determinada através de um algoritmo de otimização conhecido como Backtracking Search Algorithm (BSA) fazendo uso de uma função objetivo que utiliza as frequências naturais e modos de vibração identificados da estrutura. Simulações e testes são feitos a fim de verificar a concordância da metodologia para ambos os casos. Para as simulações, são utilizados casos mais gerais de carregamentos dinâmicos, e dois níveis de ruído (3% e 5%) são adicionados ao sinal de respostas para que esses ensaios se assemelhem aos ensaios experimentais, onde o ruído é inerente do processo. Já nos ensaios experimentais, apenas testes de vibração livre são executados. Diversos cenários de dano são propostos para as estruturas analisadas a fim de se verificar a robustez da rotina de detecção de dano. Os resultados mostram que a etapa de identificação modal estocástica através do método de identificação estocástica de subespaço (SSI) teve ótimos resultados, possibilitando, assim, a localização da região danificada da estrutura em todos os casos analisados. / Damage detection in large dimensions engineering structures through the analysis of their dynamic characteristics involves several fields. The first one deals with the structure modal identification parameter, since running free vibration tests in such structures is not a simple task, robust methods are needed in order to identify the modal parameters of this structure under ambient vibrations, this field is known as operational modal analysis. This work deals with the problem of damage detection in structures under ambient vibrations that can be represented by FEM using frame and beam elements. The damage location is determined through an optimization algorithm know as Backtracking Search Algorithm (BSA). It uses as objective function the identified natural frequencies and modes of vibration of the structure. Numerical and experimental tests are performed to assess the agreement of the methodology for both cases. For the numerical tests, more general cases of dynamic loads are used, and two noise levels (3% and 5%) are added to the response signal to assessing the robustness of the methodology close to the field conditions, in which noise is inherent of the process. In the experimental tests, only free vibration tests are performed. Several damage scenarios are proposed for the analyzed structures to check the robustness of the damage detection routine. The results show that the stochastic modal identification using the stochastic subspace identification (SSI) method had excellent results, thus allowing the location of the damaged region of the structure in all analyzed cases.

<div>This dissertation broadly focuses on autonomous condition assessment of civil infrastructures using vision-based methods, which present a plausible alternative to existing manual techniques. A region-based convolutional neural network (Faster R-CNN) is exploited for the detection of various earthquake-induced damages in reinforced concrete buildings. Four different damage categories are considered such as surface crack, spalling, spalling with exposed rebars, and severely buckled rebars. The performance of the model is evaluated on image data collected from buildings damaged under several past earthquakes taking place in different parts of the world. The proposed algorithm can be integrated with inspection drones or mobile robotic platforms for quick assessment of damaged buildings leading to expeditious planning of retrofit operations, minimization of damage cost, and timely restoration of essential services. </div><div><br></div><div> </div><div> Besides, a computer vision-based approach is presented to track the evolution of a damage over time by analysing historical visual inspection data. Once a defect is detected in a recent inspection data set, its spatial correspondences in the data collected during previous rounds of inspection are identified leveraging popular computer vision-based techniques. A single reconstructed view is then generated for each inspection round by synthesizing the candidate corresponding images. The chronology of damage thus established facilitates time-based quantification and lucid visual interpretation. This study is likely to enhance the efficiency structural inspection by introducing the time dimension into the autonomous condition assessment pipeline.</div><div><br></div><div> </div><div> Additionally, this dissertation incorporates depth fusion into a CNN-based semantic segmentation model. A 3D animation and visual effect software is exploited to generate a synthetic database of spatially aligned RGB and depth image pairs representing various damage categories which are commonly observed in reinforced concrete buildings. A number of encoding techniques are explored for representing the depth data. Besides, various schemes for fusion of RGB and depth data are investigated to identify the best fusion strategy. It was observed that depth fusion enhances the performance of deep learning-based damage segmentation algorithms significantly. Furthermore, strategies are proposed to manufacture depth information from corresponding RGB frame, which eliminates the need of depth sensing at the time of deployment without compromising on segmentation performance. Overall, the scientific research presented in this dissertation will be a stepping stone towards realizing a fully autonomous structural condition assessment pipeline.</div>

Dans le domaine de la construction, la détection automatisée et à distance de l’endommagementdes structures en béton est d’une importance capitale. En effet, lescontraintes économiques actuelles imposent une réduction des coûts de maintenancetandis que les impératifs en termes de sécurité et de qualité sont de plus en plus stricts.Dans le cadre de cette thèse, des transducteurs piézoélectriques intégrés sont utilisésafin de suivre en temps réel le comportement du béton. Ces transducteurs sont faitsde PZT, une céramique piézoélectrique particulièrement adaptée au suivi à l’aide d’ultrasonsde par ses faibles dimensions, son faible coût et la large bande de fréquenced’utilisation. Un système de monitoring ultrasonore à faible voltage et ultra rapide a étéentièrement conçu dans le cadre de cette thèse. Le système est basé sur des mesuresultrasonores bilatérales entre un émetteur et un récepteur. Le système d’acquisitiondes données développé permet d’atteindre jusqu’à 150 mesures par seconde et decalculer en temps réel un indice d’endommagement sur base des mesures effectuées.L’indice d’endommagement est basé sur la première partie de l’onde transmise (ondedirecte) plutôt que sur l’onde tardive. Le système a démontré qu’il est capable de détecterl’apparition de fissures dans le béton avant qu’elles ne soient visuellement apparenteset qu’il permet de suivre de suivre l’initiation de l’endommagement jusqu’à la rupturepour des mécanismes de fissuration très rapides, voire fragiles. Le fait d’intégrer lestransducteurs à l’intérieur de la structure permet potentiellement d’améliorer l’efficacitédes transducteurs ultrasonores à condition que les couches d’enrobage de l’élémentpiézoélectrique soient adéquatement choisis. Une partie importante du travail réaliséa été consacrée au développement d’une méthode innovante et fiable pour concevoirde nouveaux designs de transducteurs optimisés à la fois dans du béton frais ou durci.Nous avons choisi de tirer avantage du mode radial de vibration de disques piézoélectriquepeu coûteux au mode de vibration selon l’épaisseur. Ce dernier requiert en effetdes éléments plus épais ou des matériaux piézoélectriques composites plus coûteuxet dès lors peu appropriés à être intégré définitivement dans une structure en béton.Nous démontrons par ailleurs que les matériaux piézoélectriques composites à base dematériaux cimentaires qui sont abondamment étudiés semblent en réalité peu adaptés àêtre utilisés comme transducteurs ultrasonores, contrairement à des composites plusclassiques. Une attention particulière a été portée à comparer le fonctionnement destransducteurs externes et intégrés. Nous montrons par exemple que si les performancesdes transducteurs externes peuvent être améliorées sur base de la théorie d’adaptationde l’impédance acoustique, il en va tout autrement pour les transducteurs intégrés / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Bridges are vital components of the U.S. transportation network. However, every year, the transportation agencies report a large number of aging bridges that are structurally damaged. Also, evolving traffic and particularly the overloaded traversing traffic can threaten the bridges' integrity and safety further. Bridge weight-in-motion (BWIM) is a system that takes the instrumented bridges as a scale and uses the structure response to compute the trucks' weights with no interruption in the traffic. In a particular type of BWIM, called nothing-on-road BWIM (NOR-BWIM), only a few weighing sensors should be installed under the bridge top slab. Since nothing will be installed on the road surface, NOR-BWIM addresses some of the main challenges of pavement-based WIM and traditional BWIM systems. These include lane closure, interruption to the traveling traffic, and sensitivity to daily tire impacts and harsh weather conditions. It also provides a portable solution with a less labor-intense installation process. Additionally, previous studies have shown that BWIM systems are versatile candidates for overcoming the critical challenges of structural health monitoring (SHM) across various types of bridges. The integration of the two systems is more cost-effective with improved performance; thus, it is more attractive to practitioners. However, the current BWIMs have serious shortcomings that make the integrated SHM-BWIM systems impractical in real-world long-span bridges. In the first two phases of this study, these shortcomings are addressed and a novel BWIM system is proposed. Then, the novel BWIM system is used for SHM in the third phase of the study. These shortcomings are explained as follows. Most studies are performed on short/medium-span T-beam and slab-on-girder bridges. However, longer span lengths, construction methods, different slab properties (e.g., stiffness), etc., can affect the efficacy of the NOR-BWIM. Thus, there is a need to further evaluate this technique on other bridges, such as concrete-box-girder bridges with longer spans, in an effort to ascertain whether or not NOR-BWIM systems would still work effectively on such bridges. Thus, the first phase presents an experimental investigation conducted for a long-span concrete-box-girder bridge (144 m span) called the Smart Road bridge. A total of 18 experimental tests were performed on the bridge. Moreover, a cost-effective sensor placement was developed. It was found that the number of axles is detectable with an accuracy of 100%. Moreover, the estimated mean-absolute-error for axle spacing, vehicle speed, and gross vehicle weight were 4.6%, 2.6%, and 4.6%, respectively. Lastly, it was also demonstrated that the developed cost-effective NOR-BWIM system is capable of lane identification and truck position detection. The second main issue with the existing BWIM approaches is their limited suitability for simultaneous multiple-vehicle cases on multiple-lane bridges. To address this limitation, in the second phase of this study, a novel BWIM approach is proposed. The approach is built around the removal of the non-localized portion of the strain response. Keeping the localized portion of the strain response, which is not sensitive to nearby loads, allowing for enhanced detection. The superiority of this approach stems from its capability to handle multiple-vehicle cases. These may present with an arbitrary number of trucks and light-weight vehicles, simultaneously passing the bridge in any arbitrary pattern or configuration. To show the applicability of the approach, a finite element (FE) model of a long-span concrete-box-girder bridge was simulated. The model was validated against the experimental data collected under known large events. The FE model was then used to consider single-truck events (for proof-of-concept) as well as complex multiple-truck traffic cases. These included in-one-row trucks, zigzag patterns, side-by-side trucks, and a combination of several trucks with several light-weight vehicles present. The results demonstrated that the proposed BWIM approach is capable of detecting the axle weights and gross vehicle weight (GVW) of the traversing trucks. Based on all complex multiple-truck cases, the overall mean absolute errors for GVW and axle weight estimations were 4.5% and 11.3%, respectively. In the last phase, a multiple-presence dual-purpose (MPDP) SHM approach was proposed to monitor the integrity of bridges using the BWIM system existing sensors. This approach centers on the influence line (IL) change and uses a developed multiple-presence IL (MP-IL) technique (in the second phase) for SHM application. This can effectively handle the multiple presence issue of the current integrated SHM-BWIM systems to make them more practical. Also, unlike many SHM-BWIM studies, noise and transverse position change (defined as false damage indicators) were included in the proposed procedure to provide a more realistic bridge health monitoring approach. To show the applicability of the approach, a similar FE model simulated in the second phase was used. The model was then used to evaluate the MPDP approach under single and multiple truck events. Eleven damage scenarios were simulated, and three SHM trucks (a 3-axle, a 4-axle, and a 5-axle) were used to improve the SHM accuracy. Also, an updated sensor placement was proposed to effectively work for both BWIM and SHM applications in both single and multiple-truck events. According to the results, the MPDP SHM procedure coupled with the novel MP-IL and the proposed sensor placement could effectively detect the damage scenarios in both single and multiple-truck events. Also, it was shown that using several independent SHM trucks can make the monitoring process more effective. / Doctor of Philosophy / Every year, the transportation agencies report a large number of aging bridges that are structurally damaged. Also, evolving traffic and particularly overloaded traffic can threaten the bridges' integrity and safety further. Bridge weight-in-motion (BWIM) is a traffic system that takes the instrumented bridges as a scale and uses the structure response to compute the trucks' weights with no interruption in the traffic. In a particular type of BWIM, called nothing-on-road BWIM (NOR-BWIM), only a few weighing sensors should be installed under the road surface. Since nothing will be installed on the road surface, NOR-BWIM addresses some of the main challenges of pavement-based WIM and traditional BWIM systems. These include lane closure, interruption to the traveling traffic, and sensitivity to daily tire impacts and harsh weather conditions. It also provides a portable solution with a less labor-intense installation process. Additionally, previous studies have shown that BWIM systems are versatile candidates for overcoming the critical challenges of structural health monitoring (SHM) across various types of bridges. The integration of the two systems is more attractive to practitioners because it brings improved performance at a lower cost. However, the current BWIMs have serious shortcomings that make the integrated SHM-BWIM systems impractical in real-world long-span bridges. In the first two phases of this study, these shortcomings are addressed and a novel BWIM system is proposed. Then, the novel BWIM system is used for SHM in the third phase of the study. These shortcomings are explained as follows. Most studies are performed on short/medium-span bridges with particular types of structures. However, longer span lengths, construction methods, different bridge components' properties, etc., can affect the efficacy of the NOR-BWIM. Thus, there is a need to further evaluate this technique on other bridges with longer spans and different structural systems to ascertain whether or not NOR-BWIM systems would still work effectively on such bridges. Thus, the first phase presents an experimental investigation conducted for a long-span concrete-box-girder bridge (a different structural system than the literature) with 144-m spans. A total of 18 experimental tests were performed on the bridge. Moreover, a cost-effective sensor placement was developed. It was found that the number of axles is detectable with no error. Moreover, the estimated error for axle spacing, vehicle speed, and gross vehicle weight were all low. Lastly, it was also demonstrated that the developed cost-effective NOR-BWIM system is capable of lane identification and truck position detection. The second main issue with the existing BWIM approaches is their limited suitability for simultaneous multiple vehicles on multiple-lane bridges. To address this limitation, in the second phase of this study, a novel BWIM approach is proposed. The superiority of this approach stems from its capability to handle multiple-vehicle cases. These may present with an arbitrary number of trucks and light-weight vehicles, simultaneously passing the bridge in any arbitrary pattern or configuration. To show the applicability of the approach, a model of the long-span bridge was simulated. The model was validated against the experimental data collected under known traffic events. The model was then used to consider single-truck events and complex multiple-truck traffic cases. The results demonstrated that the proposed BWIM approach can detect the axle weights and gross vehicle weight (GVW) of the traversing trucks. Based on all complex multiple-truck cases, the overall errors for GVW and axle weight estimations were 4.5% and 11.3%, respectively. In the last phase, a novel SHM approach was proposed to monitor the integrity of bridges using the existing sensors for BWIM. This approach uses the proposed BWIM system for SHM application. This can effectively handle the multiple presence issue of the current integrated SHM-BWIM systems to make them more practical. Also, unlike many SHM-BWIM studies, noise and transverse position change were included in the proposed procedure to provide a more realistic bridge health monitoring approach. A similar model simulated in the second phase was used to show the applicability of the approach. The model was then used to evaluate the MPDP approach under single and multiple truck events. Eleven damage scenarios were simulated. Also, an updated sensor placement was proposed to work effectively for both BWIM and SHM applications in single and multiple-truck events. According to the results, the proposed SHM procedure coupled with the novel BWIM and the proposed sensor placement could effectively detect the damage scenarios in both single and multiple-truck events.

Structural Health Monitoring (SHM) of automobile tires has been an active area of research in the last few years. Within this area, the monitoring of strain on tires using wireless devices and networks is gaining prominence because these techniques do not require any wired connections. Various tire manufacturers are looking into SHM of automobile tires due to the Transportation Recall Enhancement, Accountability and Documentation (TREAD) act which demands installation of tire pressure monitoring devices within the tire. Besides measuring tire pressures, tire manufactures are also examining ways to measure strain and temperature as well to enhance overall safety of an automobile. A sensor system that can measure the overall strain of a tire is known as a centralized strain sensing system. However, a centralized strain sensing system cannot find the location and severity of the damage on the tire, which is a basic requirement. Various sensors such as acceleration and optical sensors have also been proposed to be used together to get more local damage information on the tire. In this thesis we have developed a strain sensing system that performs local strain measurements on the tire and transmits them to a console inside the vehicle wirelessly. Our sensing system utilizes a new sensing material called Metal RubberTM which is shown to be conductive like metal, and flexible as rubber. Also, we have also developed a reliable and an energy efficient geographic routing protocol for transporting strain data wirelessly from a tire surface to the driver of the automobile. / Master of Science