Desenvolvimento de um sistema de SHM sem fio e com compensação automática de temperatura

Pós-graduação em Engenharia Elétrica - FEIS

Avaliação do método da quebra do grafite para estimação da sensibilidade de transdutores piezelétricos utilizados na técnica da Impedância Eletromecânica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Desarrollo de aplicaciones de comunicaciones inalámbricas en sistemas de monitorización estructural desarrollados en aeronáutica.

Los Sistemas de SHM o de monitorización de la integridad estructural surgen ante la necesidad de mejorar los métodos de evaluación y de test no destructivos convencionales. De esta manera, se puede tener controlado todo tipo de estructuras en las cuales su correcto estado o funcionamiento suponga un factor crítico. Un Sistema SHM permite analizar una estructura concreta capturando de manera periódica el estado de la integridad estructural, que en este proyecto se ha aplicado a estructuras aeronáuticas. P.A.M.E.L.A. (Phase Array Monitoring for Enhanced Life Assessment) es la denominación utilizada para definir una serie de equipos electrónicos para Sistemas SHM desarrollados por AERNOVA y los Grupos de Diseño Electrónico de las universidades UPV/EHU y UPM. Los dispositivos P.A.M.E.L.A. originalmente no cuentan con tecnología Wi-Fi, por lo que incorporan un módulo hardware independiente que se encarga de las comunicaciones inalámbricas, a los que se les denomina Nodos. Estos Nodos poseen un Sistema Operativo propio y todo lo necesario para administrar y organizar la red Mallada Wi-Fi. De esta manera se obtiene una red mallada inalámbrica compuesta por Nodos que interconectan los Sistemas SHM y que se encargan de transmitir los datos a los equipos que procesan los resultados adquiridos por P.A.M.E.L.A. Los Nodos son dispositivos empotrados que llevan instalados un firmware basado en una distribución de Linux para Nodos (o Routers), llamado Openwrt. Que para disponer de una red mallada necesitan de un protocolo orientado a este tipo de redes. Entre las opciones de protocolo más destacadas se puede mencionar: DSDV (Destination Sequenced Distance Vector), OLSR (Optimized Link State Routing), B.A.T.M.A.N-Adv (Better Approach To Mobile Adhoc Networking Advance), BMX (una versión de B.A.T.M.A.N-Adv), AODV (Ad hoc On-Demand Distance Vector) y el DSR (Dynamic Source Routing). Además de la existencia de protocolos orientados a las redes malladas, también hay organizaciones que se dedican a desarrollar firmware que los utilizan, como es el caso del firmware llamado Nightwing que utiliza BMX, Freifunk que utiliza OLSR o Potato Mesh que utiliza B.A.T.M.A.N-Adv. La ventaja de estos tres firmwares mencionados es que las agrupaciones que las desarrollan proporcionan las imágenes precompiladas del sistema,listas para cargarlas en distintos modelos de Nodos. En este proyecto se han instalado las imágenes en los Nodos y se han probado los protocolos BMX, OLSR y B.A.T.M.A.N.-Adv. Concluyendo que la red gestionada por B.A.T.M.A.N.-Adv era la que mejor rendimiento obtenía en cuanto a estabilidad y ancho de banda. Después de haber definido el protocolo a usar, se procedió a desarrollar una distribución basada en Openwrt, que utilice B.A.T.M.A.N.-Adv para crear la red mallada, pero que se ajuste mejor a las necesidades del proyecto, ya que Nightwing, Freifunk y Potato Mesh no lo hacían. Además se implementan aplicaciones en lenguaje ANSI C y en LabVIEW para interactuar con los Nodos y los Sistemas SHM. También se procede a hacer alguna modificación en el Hardware de P.A.M.E.L.A. y del Nodo para obtener una mejor integración entre los dos dispositivos. Y por ultimo, se prueba la transferencia de datos de los Nodos en distintos escenarios. ABSTRACT. Structural Health Monitoring (SHM) systems arise from the need of improving assessment methods and conventional nondestructive tests. Critical structures can be monitored using SHM. A SHM system analyzes periodically a specific structure capturing the state of structural integrity. The aim of this project is to contribute in the implementation of Mesh network for SHM system in aircraft structures. P.A.M.E.L.A. (Phase Array Monitoring for Enhanced Life Assessment) is the name for electronic equipment developed by AERNOVA, the Electronic Design Groups of university UPV/EHU and the Instrumentation and Applied Acoustics research group from UPM. P.A.M.E.L.A. devices were not originally equipped with Wi-Fi interface. In this project a separate hardware module that handles wireless communications (nodes) has been added. The nodes include an operating system for manage the Wi-Fi Mesh Network and they form the wireless mesh network to link SHM systems with monitoring equipment. Nodes are embedded devices with an installed firmware based on special Linux distribution used in routers or nodes, called OpenWRT. They need a Mesh Protocol to stablish the network. The most common protocols options are: DSDV (Destination Sequenced Distance Vector), OLSR (Optimized Link State Routing), BATMAN-Adv (Better Approach To Mobile Ad-hoc Networking Advance), BMX (a version of BATMAN-Adv) AODV (Ad hoc on-Demand Distance Vector) and DSR (Dynamic Source Routing). In addition, there are organizations that are dedicated to develope firmware using these Mesh Protocols, for instance: Nightwing uses BMX, Freifunk use OLSR and Potato Mesh uses BATMAN-Adv. The advantage of these three firmwares is that these groups develop pre-compiled images of the system ready to be loaded in several models of Nodes. In this project the images were installed in the nodes. In this way, BMX, OLSR and BATMAN-Adv have been tested. We conclude that the protocol BATMAN-Adv has better performance in terms of stability and bandwidth. After choosing the protocol, the objective was to develop a distribution based on OpenWRT, using BATMAN-Adv to create the mesh network. This distribution is fitted to the requirements of this project. Besides, in this project it has been developed applications in C language and LabVIEW to interact with the Nodes and the SHM systems. The project also address some modifications to the PAMELA hardware and the Node, for better integration between both elements. Finally, data transfer tests among the different nodes in different scenarios has been carried out.

Identification of intermediate debonding damage in FRP-plated RC beams based on multi-objective particle swarm optimization without updated baseline model

Fiber reinforced polymer composites (FRP) have found widespread usage in the repair and strengthening of concrete structures. FRP composites exhibit high strength-to-weight ratio, corrosion resistance, and are convenient to use in repair applications. Externally bonded FRP flexural strengthening of concrete beams is the most extended application of this technique. A common cause of failure in such members is associated with intermediate crack-induced debonding (IC debonding) of the FRP substrate from the concrete in an abrupt manner. Continuous monitoring of the concrete?FRP interface is essential to pre- vent IC debonding. Objective condition assessment and performance evaluation are challenging activities since they require some type of monitoring to track the response over a period of time. In this paper, a multi-objective model updating method integrated in the context of structural health monitoring is demonstrated as promising technology for the safety and reliability of this kind of strengthening technique. The proposed method, solved by a multi-objective extension of the particle swarm optimization method, is based on strain measurements under controlled loading. The use of permanently installed fiber Bragg grating (FBG) sensors embedded into the FRP-concrete interface or bonded onto the FRP strip together with the proposed methodology results in an automated method able to operate in an unsupervised mode.

A simplified spectral approachfor impedance-based damage identification of frp-strengthened rc beams

Hoy en día, el refuerzo y reparación de estructuras de hormigón armado mediante el pegado de bandas de polímeros reforzados con fibras (FRP) se emplea cada vez con más frecuencia a causa de sus numerosas ventajas. Sin embargo, las vigas reforzadas con esta técnica pueden experimentar un modo de fallo frágil a causa del despegue repentino de la banda de FRP a partir de una fisura intermedia. A pesar de su importancia, el número de trabajos que abordan el estudio de este mecanismo de fallo y su monitorización es muy limitado. Por ello, el desarrollo de metodologías capaces de monitorizar a largo plazo la adherencia de este refuerzo a las estructuras de hormigón e identificar cuándo se inicia el despegue de la banda constituyen un importante desafío a abordar. El principal objetivo de esta tesis es la implementación de una metodología fiable y efectiva, capaz de detectar el despegue de una banda de FRP en una viga de hormigón armado a partir de una fisura intermedia. Para alcanzar este objetivo se ha implementado un procedimiento de calibración numérica a partir de ensayos experimentales. Para ello, en primer lugar, se ha desarrollado un modelo numérico unidimensional simple y no costoso representativo del comportamiento de este tipo vigas de hormigón reforzadas con FRP, basado en un modelo de fisura discreta para el hormigón y el método de elementos espectrales. La formación progresiva de fisuras a flexion y el consiguiente despegue en la interface entre el hormigón y el FRP se formulan mediante la introducción de un nuevo elemento capaz de representar ambos fenómenos simultáneamente sin afectar al procedimiento numérico. Además, con el modelo propuesto, se puede obtener de una forma sencilla la respuesta dinámica en altas frecuencias de este tipo de estructuras, lo cual puede hacer muy útil su uso como herramienta de diagnosis y detección del despegue en su fase inicial mediante una monitorización de la variación de las características dinámicas locales de la estructura. Un método de evaluación no destructivo muy prometedor para la monitorización local de las estructuras es el método de la impedancia usando sensores-actuadores piezoeléctricos (PZT). La impedancia eléctrica de los sensores PZT se puede relacionar con la impedancia mecánica de las estructuras donde se encuentran adheridos Ya que la impedancia mecánica de una estructura se verá afectada por su deterioro, se pueden implementar indicadores de daño mediante una comparación del espectro de admitancia (inversa de la impedancia) a lo largo de distintas etapas durante el periodo de servicio de una estructura. Cualquier cambio en el espectro se podría interpretar como una variación en la integridad de la estructura. La impedancia eléctrica se mide a altas frecuencias con lo cual esta metodología debería ser muy sensible a la detección de estados de daño incipiente local, tal como se desea en la aplicación de este trabajo. Se ha implementado un elemento espectral PZT-FRP como extensión del modelo previamente desarrollado, con el objetivo de poder calcular numéricamente la impedancia eléctrica de sensores PZT adheridos a bandas de FRP sobre una viga de hormigón armado. El modelo, combinado con medidas experimentales captadas mediante sensores PZT, se implementa en el marco de una metodología de calibración de modelos para detectar cuantitativamente el despegue en la interfase entre una banda de FRP y una viga de hormigón. El procedimiento de optimización se resuelve empleando el método del enjambre cooperativo con un algoritmo bagging. Los resultados muestran una gran aproximación en la estimación del daño para el problema propuesto. Adicionalmente, se ha desarrollado también un método adaptativo para el mallado de elementos espectrales con el objetivo de localizar las zonas dañadas a partir de los resultados experimentales, el cual contribuye a aumentar la robustez y efectividad del método propuesto a la hora de identificar daños incipientes en su aparición inicial. Finalmente, se ha llevado a cabo un procedimiento de optimización multi-objetivo para detectar el despegue inicial en una viga de hormigón a escala real reforzada con FRP a partir de las impedancias captadas con una red de sensores PZT instrumentada a lo largo de la longitud de la viga. Cada sensor aporta los datos para definir cada una de las funciones objetivo que definen el procedimiento. Combinando el modelo previo de elementos espectrales con un algoritmo PSO multi-objetivo el procedimiento de detección de daño resultante proporciona resultados satisfactorios considerando la escala de la estructura y todas las incertidumbres características ligadas a este proceso. Los resultados obtenidos prueban la viabilidad y capacidad de los métodos antes mencionados y también su potencial en aplicaciones reales. Abstract Nowadays, the external bonding of fibre reinforced polymer (FRP) plates or sheets is increasingly used for the strengthening and retrofitting of reinforced concrete (RC) structures due to its numerous advantages. However, this kind of strengthening often leads to brittle failure modes being the most dominant failure mode the debonding induced by an intermediate crack (IC). In spite of its importance, the number of studies regarding the IC debonding mechanism and bond health monitoring is very limited. Methodologies able to monitor the long-term efficiency of bonding and successfully identify the initiation of FRP debonding constitute a challenge to be met. The main purpose of this thesisis the implementation of a reliable and effective methodology of damage identification able to detect intermediate crack debonding in FRP-strengthened RC beams. To achieve this goal, a model updating procedure based on numerical simulations and experimental tests has been implemented. For it, firstly, a simple and non-expensive one-dimensional model based on the discrete crack approach for concrete and the spectral element method has been developed. The progressive formation of flexural cracks and subsequent concrete-FRP interfacial debonding is formulated by the introduction of a new element able to represent both phenomena simultaneously without perturbing the numerical procedure. Furthermore, with the proposed model, high frequency dynamic response for these kinds of structures can also be obtained in a very simple and non-expensive way, which makes this procedure very useful as a tool for diagnoses and detection of debonding in its initial stage by monitoring the change in local dynamic characteristics. One very promising active non-destructive evaluation method for local monitoring is impedance-based structural health monitoring(SHM)using piezoelectric ceramic (PZT) sensor-actuators. The electrical impedance of the PZT can be directly related to the mechanical impedance of the host structural component where the PZT transducers are attached. Since the structural mechanical impedance will be affected by the presence of structural damage, comparisons of admittance (inverse of impedance) spectra at various times during the service period of the structure can be used as damage indicator. Any change in the spectra might be an indication of a change in the structural integrity. The electrical impedance is measured at high frequencies with which this methodology appears to be very sensitive to incipient damage in structural systems as desired for our application. Abonded-PZT-FRP spectral beam element approach based on an extension of the previous discrete crack approach is implemented in the calculation of the electrical impedance of the PZT transducer bonded to the FRP plates of a RC beam. This approach in conjunction with the experimental measurements of PZT actuator-sensors mounted on the structure is used to present an updating methodology to quantitatively detect interfacial debonding between a FRP strip and the host RC structure. The updating procedure is solved by using an ensemble particle swarm optimization approach with abagging algorithm, and the results demonstrate a big improvement for the performance and accuracy of the damage detection in the proposed problem. Additionally, an adaptive strategy of spectral element mesh has been also developed to detect damage location with experimental results, which shows the robustness and effectiveness of the proposed method to identify initial and incipient damages at its early stage. Lastly, multi-objective optimization has been carried out to detect debonding damage in a real scale FRP-strengthened RC beam by using impedance signatures. A net of PZT sensors is distributed along the beam to construct impedance-based multiple objectives under gradually induced damage scenario. By combining the spectral element model presented previously and an ensemble multi-objective PSO algorithm, the implemented damage detection process yields satisfactory predictions considering the scale and uncertainties of the structure. The obtained results prove the feasibility and capability of the aforementioned methods and also their potentials in real engineering applications.

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Monitorización de estructuras aeronáuticas mediante técnicas de inteligencia artificial

Una de las barreras para la aplicación de las técnicas de monitorización de la integridad estructural (SHM) basadas en ondas elásticas guiadas (GLW) en aeronaves es la influencia perniciosa de las condiciones ambientales y de operación (EOC). En esta tesis se ha estudiado dicha influencia y la compensación de la misma, particularizando en variaciones del estado de carga y temperatura. La compensación de dichos efectos se fundamenta en Redes Neuronales Artificiales (ANN) empleando datos experimentales procesados con la Transformada Chirplet. Los cambios en la geometría y en las propiedades del material respecto al estado inicial de la estructura (lo daños) provocan cambios en la forma de onda de las GLW (lo que denominamos característica sensible al daño o DSF). Mediante técnicas de tratamiento de señal se puede buscar una relación entre dichas variaciones y los daños, esto se conoce como SHM. Sin embargo, las variaciones en las EOC producen también cambios en los datos adquiridos relativos a las GLW (DSF) que provocan errores en los algoritmos de diagnóstico de daño (SHM). Esto sucede porque las firmas de daño y de las EOC en la DSF son del mismo orden. Por lo tanto, es necesario cuantificar y compensar el efecto de las EOC sobre la GLW. Si bien existen diversas metodologías para compensar los efectos de las EOC como por ejemplo “Optimal Baseline Selection” (OBS) o “Baseline Signal Stretching” (BSS), estas, se emplean exclusivamente en la compensación de los efectos térmicos. El método propuesto en esta tesis mezcla análisis de datos experimentales, como en el método OBS, y modelos basados en Redes Neuronales Artificiales (ANN) que reemplazan el modelado físico requerido por el método BSS. El análisis de datos experimentales consiste en aplicar la Transformada Chirplet (CT) para extraer la firma de las EOC sobre la DSF. Con esta información, obtenida bajo diversas EOC, se entrena una ANN. A continuación, la ANN actuará como un interpolador de referencias de la estructura sin daño, generando información de referencia para cualquier EOC. La comparación de las mediciones reales de la DSF con los valores simulados por la ANN, dará como resultado la firma daño en la DSF, lo que permite el diagnóstico de daño. Este esquema se ha aplicado y verificado, en diversas EOC, para una estructura unidimensional con un único camino de daño, y para una estructura representativa de un fuselaje de una aeronave, con curvatura y múltiples elementos rigidizadores, sometida a un estado de cargas complejo, con múltiples caminos de daños. Los efectos de las EOC se han estudiado en detalle en la estructura unidimensional y se han generalizado para el fuselaje, demostrando la independencia del método respecto a la configuración de la estructura y el tipo de sensores utilizados para la adquisición de datos GLW. Por otra parte, esta metodología se puede utilizar para la compensación simultánea de una variedad medible de EOC, que afecten a la adquisición de datos de la onda elástica guiada. El principal resultado entre otros, de esta tesis, es la metodología CT-ANN para la compensación de EOC en técnicas SHM basadas en ondas elásticas guiadas para el diagnóstico de daño. ABSTRACT One of the open problems to implement Structural Health Monitoring techniques based on elastic guided waves in real aircraft structures at operation is the influence of the environmental and operational conditions (EOC) on the damage diagnosis problem. This thesis deals with the compensation of these environmental and operational effects, specifically, the temperature and the external loading, by the use of the Chirplet Transform working with Artificial Neural Networks. It is well known that the guided elastic wave form is affected by the damage appearance (what is known as the damage sensitive feature or DSF). The DSF is modified by the temperature and by the load applied to the structure. The EOC promotes variations in the acquired data (DSF) and cause mistakes in damage diagnosis algorithms. This effect promotes changes on the waveform due to the EOC variations of the same order than the damage occurrence. It is difficult to separate both effects in order to avoid damage diagnosis mistakes. Therefore it is necessary to quantify and compensate the effect of EOC over the GLW forms. There are several approaches to compensate the EOC effects such as Optimal Baseline Selection (OBS) or Baseline Signal Stretching (BSS). Usually, they are used for temperature compensation. The new method proposed here mixes experimental data analysis, as in the OBS method, and Artificial Neural Network (ANN) models to replace the physical modelling which involves the BSS method. The experimental data analysis studied is based on apply the Chirplet Transform (CT) to extract the EOC signature on the DSF. The information obtained varying EOC is employed to train an ANN. Then, the ANN will act as a baselines interpolator of the undamaged structure. The ANN generates reference information at any EOC. By comparing real measurements of the DSF against the ANN simulated values, the damage signature appears clearly in the DSF, enabling an accurate damage diagnosis. This schema has been applied in a range of EOC for a one-dimensional structure containing single damage path and two dimensional real fuselage structure with stiffener elements and multiple damage paths. The EOC effects tested in the one-dimensional structure have been generalized to the fuselage showing its independence from structural arrangement and the type of sensors used for GLW data acquisition. Moreover, it can be used for the simultaneous compensation of a variety of measurable EOC, which affects the guided wave data acquisition. The main result, among others, of this thesis is the CT-ANN methodology for the compensation of EOC in GLW based SHM technique for damage diagnosis.

Subsidence damage assessment of a Gothic church using differential interferometry and field data

The Santas Justa and Rufina Gothic church (fourteenth century) has suffered several physical, mechanical, chemical, and biochemical types of pathologies along its history: rock alveolization, efflorescence, biological activity, and capillary ascent of groundwater. However, during the last two decades, a new phenomenon has seriously affected the church: ground subsidence caused by aquifer overexploitation. Subsidence is a process that affects the whole Vega Baja of the Segura River basin and consists of gradual sinking in the ground surface caused by soil consolidation due to a pore pressure decrease. This phenomenon has been studied by differential synthetic aperture radar interferometry techniques, which illustrate settlements up to 100 mm for the 1993–2009 period for the whole Orihuela city. Although no differential synthetic aperture radar interferometry information is available for the church due to the loss of interferometric coherence, the spatial analysis of nearby deformation combined with fieldwork has advanced the current understanding on the mechanisms that affect the Santas Justa and Rufina church. These results show the potential interest and the limitations of using this remote sensing technique as a complementary tool for the forensic analysis of building structures.

Detection of bridge anomalous behavior and assessment of their impact on structural performance

Peer reviewed

A Delay Vector Variance based marker for an output-only assessment of structural changes in tension leg platforms

Although aspects of power generation of many offshore renewable devices are well understood, their dynamic responses under high wind and wave conditions are still to be investigated to a great detail. Output only statistical markers are important for these offshore devices, since access to the device is limited and information about the exposure conditions and the true behaviour of the devices are generally partial, limited, and vague or even absent. The markers can summarise and characterise the behaviour of these devices from their dynamic response available as time series data. The behaviour may be linear or nonlinear and consequently a marker that can track the changes in structural situations can be quite important. These markers can then be helpful in assessing the current condition of the structure and can indicate possible intervention, monitoring or assessment. This paper considers a Delay Vector Variance based marker for changes in a tension leg platform tested in an ocean wave basin for structural changes brought about by single column dampers. The approach is based on dynamic outputs of the device alone and is based on the estimation of the nonlinearity of the output signal. The advantages of the selected marker and its response with changing structural properties are discussed. The marker is observed to be important for monitoring the as- deployed structural condition and is sensitive to changes in such conditions. Influence of exposure conditions of wave loading is also discussed in this study based only on experimental data.

Field Testing and Development of Novel SHM systems at Queen’s University Belfast

Ageing and deterioration of infrastructure is a challenge facing transport authorities. In
particular, there is a need for increased bridge monitoring in order to provide adequate
maintenance and to guarantee acceptable levels of transport safety. The Intelligent
Infrastructure group at Queens University Belfast (QUB) are working on a number of aspects
of infrastructure monitoring and this paper presents summarised results from three distinct
monitoring projects carried out by this group. Firstly the findings from a project on next
generation Bridge Weight in Motion (B-WIM) are reported, this includes full scale field testing
using fibre optic strain sensors. Secondly, results from early phase testing of a computer
vision system for bridge deflection monitoring are reported on. This research seeks to exploit
recent advances in image processing technology with a view to developing contactless
bridge monitoring approaches. Considering the logistical difficulty of installing sensors on a
‘live’ bridge, contactless monitoring has some inherent advantages over conventional
contact based sensing systems. Finally the last section of the paper presents some recent
findings on drive by bridge monitoring. In practice a drive-by monitoring system will likely
require GPS to allow the response of a given bridge to be identified; this study looks at the
feasibility of using low-cost GPS sensors for this purpose, via field trials. The three topics
outlined above cover a spectrum of SHM approaches namely, wired monitoring, contactless
monitoring and drive by monitoring

Étude paramétrique de la propagation d'ondes ultrasonores guidées dans les structures aéronautiques

La mise en oeuvre de systèmes de détection de défauts à même les structures ou infrastructures en génie est le sujet d’étude du Structural Health Monitoring (SHM). Le SHM est une solution efficace à la réduction des coûts associés à la maintenance de structures. Une stratégie prometteuse parmi les technologies émergentes en SHM est fondée sur l’utilisation d’ondes ultrasonores guidées. Ces méthodes sont basées sur le fait que les structures minces agissent comme guides d’ondes pour les ondes ultrasonores. Puisque les structures aéronautiques sont majoritairement minces, les ondes guidées constituent une stratégie pertinente afin d’inspecter de grandes surfaces. Toutefois, les assemblages aéronautiques sont constitués de plusieurs éléments modifiant et compliquant la propagation des ondes guidées dans celles-ci. En effet, la présence de rivets, de raidisseurs, de joints ainsi que la variation de la nature des matériaux utilisés complexifie la propagation des ondes guidées. Pour envisager la mise en oeuvre de systèmes de détection basés sur les ondes guidées, une compréhension des interactions intervenant dans ces diverses structures est nécessaire. Un tel travail entre dans le cadre du projet de collaboration CRIAQ DPHM 501 dont l’objectif principal est de développer une banque de connaissances quant à la propagation d’ondes guidées dans les structures aéronautiques. Le travail de ce mémoire présente d’abord les résultats d’études paramétriques numériques obtenus dans le cadre de ce projet CRIAQ. Puis, afin de faciliter la caractérisation expérimentale de la propagation des ondes guidées, une seconde partie du travail a porté sur le développement d’un absorbant d’ondes guidées. Cet absorbant permet également d’envisager l’extension des régions observables par les systèmes SHM. Ce deuxième volet contribue donc également au projet CRIAQ par l’atténuation de réflexions non désirées dans l’étude menée sur les maintes structures aéronautiques nourrissant la banque de connaissances. La première partie de ce mémoire relève l’état des connaissances de la littérature sur la propagation d’ondes guidées dans les structures aéronautiques. La deuxième partie présente rapidement le formalisme derrière les ondes de Lamb ainsi que les différentes approches analytiques pour caractériser les interactions entre ondes guidées et discontinuités. Par la suite, les outils utilisés pour effectuer les simulations par éléments finis sont présentés et validés par le biais d’une phase expérimentale. La deuxième partie se termine avec la présentation des différentes structures et discontinuités étudiées dans le cadre du projet CRIAQ. Finalement, la troisième et dernière partie de ce mémoire présente les travaux numériques orientés vers la conception d’un absorbant idéal pour ondes guidées. Afin d’y parvenir, une étude paramétrique quant à la forme, les dimensions et les propriétés mécaniques de l’absorbant est entreprise. Enfin, une étude expérimentale permettant de valider les résultats numériques est présentée.

Development of a Wireless MEMS Multifunction Sensor System and Field Demonstration of Embedded Sensors for Monitoring Concrete Pavements, TR-637, 2016

Pavements tend to deteriorate with time under repeated traffic and/or environmental loading. By detecting pavement distresses and damage early enough, it is possible for transportation agencies to develop more effective pavement maintenance and rehabilitation programs and thereby achieve significant cost and time savings. The structural health monitoring (SHM) concept can be considered as a systematic method for assessing the structural state of pavement infrastructure systems and documenting their condition. Over the past several years, this process has traditionally been accomplished through the use of wired sensors embedded in bridge and highway pavement. However, the use of wired sensors has limitations for long-term SHM and presents other associated cost and safety concerns. Recently, micro-electromechanical sensors and systems (MEMS) and nano-electromechanical systems (NEMS) have emerged as advanced/smart-sensing technologies with potential for cost-effective and long-term SHM. This two-pronged study evaluated the performance of commercial off-the-shelf (COTS) MEMS sensors embedded in concrete pavement (Final Report Volume I) and developed a wireless MEMS multifunctional sensor system for health monitoring of concrete pavement (Final Report Volume II).

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Structural Data Acquisition Using Sensor Network

The development cost of any civil infrastructure is very high; during its life span, the civil structure undergoes a lot of physical loads and environmental effects which damage the structure. Failing to identify this damage at an early stage may result in severe property loss and may become a potential threat to people and the environment. Thus, there is a need to develop effective damage detection techniques to ensure the safety and integrity of the structure. One of the Structural Health Monitoring methods to evaluate a structure is by using statistical analysis. In this study, a civil structure measuring 8 feet in length, 3 feet in diameter, embedded with thermocouple sensors at 4 different levels is analyzed under controlled and variable conditions. With the help of statistical analysis, possible damage to the structure was analyzed. The analysis could detect the structural defects at various levels of the structure.