Work described in this thesis is concerned with localisation techniques, for determining the position, of wireless sensors whilst these are immersed in confined industrial processes, such as those occurring in the chemical, pharmaceutical and food processing industries. Two different approaches to localisation were investigated. The first approach employed an existing hardware system that used ultra wide band (UWB) signals whist the second approach used a network localisation method based on information from narrow-band received signals. A prototype UWB-based localisation algorithm processed experimental received UWB pulses to detect their leading edges (LE) that were used to derive Time Difference of Arrival (TDoA) data. In turn TDoA data were converted into distances and used to compute the locations of the sensor nodes. Nevertheless, the process of detecting the LEs caused significant errors in the localisation process. To deal with this problem new automated adaptive LE detection methods were derived that succeeded in reducing localisation errors by half, compared to the prototype method, reaching accuracies of ±2cm. Thorough analysis of TDoA profiles revealed that these follow specific trends depending on the positions of the sensor nodes. A number of properties of TDoA profiles are proved mathematically and incorporated into seven localisation algorithms. These algorithms were examined using experimental TDoA data and shown to achieve average localisation errors up to 3cm. Network-based localisation was examined at a later stage of this research since complexities of large scale measurements and difficulties with equipment, delayed acquiring experimental data. The deployed network consisted of a number of nodes whose positions were known (anchors) that were used to estimate the positions of sensor nodes whose positions where considered to be unknown. Localisation was based on received signal strength (RSS) data, at every node to be localised, in anticipation that RSS could provide distance information that could be used in the localisation procedure. Nevertheless, fluctuations in RSS only allowed using localisation algorithms that associated RSS to the positions of anchors. The average localisation error in the network-based localisation algorithms was between 30cm to 100cm.

Various nondestructive testing (NDT) technologies for construction and performance monitoring have been studied for decades. Recently, the rapid evolution of wireless sensor network (WSN) technologies has enabled the development of sensors that can be embedded in concrete to monitor the structural health of infrastructure. Such sensors can be buried inside concrete and they can collect and report valuable volumetric data related to the health of a structure during and/or after construction. Wireless embedded sensors monitoring system is also a promising solution for decreasing the high installation and maintenance cost of the conventional wire based monitoring systems. Wireless monitoring sensors need to operate for long time. However, sensor batteries have finite life-time. Therefore, in order to enable long operational life of wireless sensors, novel wireless powering methods, which can charge the sensors’ rechargeable batteries wirelessly, need to be developed. The optimization of RF wireless powering of sensors embedded in concrete is studied here. First, our analytical results focus on calculating the transmission loss and propagation loss of electromagnetic waves penetrating into plain concrete at different humidity conditions for various frequencies. This analysis specifically leads to the identification of an optimum frequency range within 20-80 MHz that is validated through full-wave electromagnetic simulations. Second, the effects of various reinforced bar configurations on the efficiency of wireless powering are investigated. Specifically, effects of the following factors are studied: rebar types, rebar period, rebar radius, depth inside concrete, and offset placement. This analysis leads to the identification of the 902-928 MHz ISM band as the optimum power transmission frequency range for sensors embedded in reinforced concrete, since antennas working in this band are less sensitive to the effects of varying humidity as well as rebar configurations. Finally, optimized rectennas are designed for receiving and/or harvesting power in order to charge the rechargeable batteries of the embedded sensors. Such optimized wireless powering systems exhibit significantly larger efficiencies than the efficiencies of conventional RF wireless powering systems for sensors embedded in plain or reinforced concrete.

Les réseaux de capteurs sans-fil sont une nouvelle technologie qui permet de déployer des capteurs hétérogènes et de les faire communiquer sans fil et de façon autonome. Cette capacité nouvelle à surveiller ou instrumenter le monde qui nous entoure ouvre la voie à de nouvelles applications innovantes ou à une évolution majeure d’applications déjà existantes.D’une dizaine de nœuds à plusieurs milliers, les réseaux de capteurs sans fil commencent à conquérir le monde industriel et notre vie quotidienne. Leurs besoins en communications, gestion, génération et stockage de l’énergie, miniaturisation et réduction des coûts ne nécessitent pas seulement de perfectionner les technologies actuelles mais bien d’en inventer de nouvelles. Parmi toutes les applications révolutionnaires des réseaux de capteurs sans fil comme dans la santé, l’environnement, l’industrie et le militaire, l’une des applications les plus transformatrices est la surveillance de structure. La surveillance de structure est l’art de surveiller tout ce qui peut s’abimer, s’user ou tomber en panne. Elle est particulièrement importante dans les domaines des transports et du bâtiment, étant donné que la sécurité des personnes est en jeu. En plaçant aux endroits stratégiques des capteurs sans-fil, il sera possible de prévoir et de prévenir la défaillance d’un pont, l’usure d’un avion ou d’un train ou la déformation d’un bâtiment. La surveillance de structure permet de prévenir les pannes et les défaillances, de réduire les coûts de maintenance et d’améliorer les performances. C’est un processus complexe qui implique plusieurs technologies : des capteurs, la transmission de l’information et l’analyse des données. La nature (accéléromètre, gyroscope, jauge de contrainte, température, pression, fuite, givre, etc. . .), la position ainsi que le nombre de capteurs sont dictés et dépendants des besoins de l’analyse de la structure qui doit être effectuée. De ce fait, les contraintes imposées au système de transmission de données sans fil, afin d’offrir une couverture suffisante de la structure de l’appareil avec plusieurs centaines voire plusieurs milliers de capteurs que leur localisation rendra difficile d’accès, nécessitent des nouvelles innovations en matière d’efficacité énergétique et de performance de communication. Ce travail s’intéresse à la conception et l’implémentation d’un système de transmission de données dans un réseau de capteurs sans-fil. Après une présentation des exigences du système de surveillance de structure aéronautique, l’architecture générale du système de surveillance est décrite. Une couche physique spécifique à haute efficacité énergétique basée sur l’Impulse-Radio UltraWide Band a été conçue. Les designs complets de l’émetteur et du récepteur IR-UWB sont présentés ainsi que l'optimisation du codage canal par rapport à la consommation énergétique. Une couche MAC spécifique permettant un nombre important de nœuds et une efficacité énergétique élevée basée sur du TDMA reconfigurable a été conçue. Plusieurs prototypes ont été implémentés pour valider la conception et démontrer les performances. Ces implémentation utilise des techniques avancées d’optimisation de la consommation énergétique et de reconfigurabilité afin de répondre aux exigences des réseaux de capteurs sans-fil. Des simulations ASIC permettent également de prévoir que ce système permettra de supporter des débits applicatifs de plusieurs centaines de mégabits par seconde, tout en permettant à plusieurs dizaines de nœuds de communiquer. Les performances énergétiques de ce système de communication sont aujourd’hui à l’état de l’art. Enfin, cette technologie de communication sans-fil a été intégrée dans un système complet de deux nœuds capteurs et d’un routeur dans un démonstrateur FPGA / Wireless Sensor Networks (WSN) is an emerging technology which allows deploying wireless communicating autonomous heterogenous sensors. This monitoring capability paves the way for new innovative applications or breakthrough evolution of existing ones. WSN have started to change the industry and our daily lives. Their communication, energy, miniaturization and cost requirements cannot be met by evolutions of current technologies but will require new innovations.Among health, environment, industrial and military applications for WSN, one of the most revolutionary is Structural Health Monitoring (SHM). SHM is the art of monitoring anything which can wear, break down or be damaged. It is of utmost importance in safety sensitive domains such as the transport and construction industries.By placing sensors in carefully chosen locations, SHM will allow failure prediction, cost reduction and improved performance of bridges, planes, building or engines.The tens to thousands of sensors and the huge amount of data generated places a strong burden on the wireless communication of the nodes, which cannot be satisfied with today’s technology. This work presents the design and implementation works such a wireless communication system.Following a presentation of the context and requirement of this work, a general description of the SHM system is given. A specific highly energy efficient physical layer based on Impulse-Radio UltraWide Band (IR-UWB) has been designed.The complete IR-UWB transmitter and receiver are detailed, including the energy efficiency optimized channel coding. A specific Medium Access Control (MAC) layer allowing a large number of communicating nodes based on reconfigurableTime Division Multiple Access (TDMA) was designed. Several prototypes of this system have been implemented to prove feasibility and performance. These implementations employ advanced energy consumption reduction and reconfigurability techniques to answer WSN communication challenges. An ASIC implementation simulation has demonstrated hundreds of megabits per second data rate at state of the art energy efficiency

McMaster University in conjunction with an industrial partner has been designing wireless vibrational condition monitoring sensors for implementation on a vibrating screening machine used in mining applications. A limitation with the current sensor design is their dependency on battery power. In order for the sensors to provide real-time continuous streaming of acceleration data, an alternate power supply was required outside of traditional sources such as batteries or wired power. This thesis outlines the research and development of a power system that harvests the kinetic vibrational energy of a mining screen and converts it into electrical energy for use by a wireless sensor node. During development, multiple prototypes were built and evaluated under laboratory conditions. The core concept of the system is an eccentric pendulum mass excited by the external vibrations of the screening machine used to drive a stepper motor generator. The major design obstacle of the project was how to get the system to self initiate. Both a mechanical and an electrical solution were developed to solve this concern. The final prototype design is fully autonomous, able to react to the start up or shut-down of a screening machine, while also providing a continuous power supply to a wireless vibrational analysis sensor as tested in the lab. With minor optimization, this prototype can be turned into a commercial product for industrial implementation and sale. / Thesis / Master of Applied Science (MASc)

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Recent years have seen increasing research interest in structural health monitoring (SHM). Among the many advances in SHM research, “smart” wireless sensors capable of embedded computing and wireless communication have been highly attractive. Wireless communication in SHM systems was originally proposed to significantly reduce the monetary and time cost for installing lengthy cables in an SHM system. Besides wireless sensing, the next revolution in sensor networks has been predicted to be mobile sensor networks that implant mobility into traditional wireless sensor networks. This research explores decentralized structural model updating and damage detection using mobile and wireless sensors. In the first stage of this research, mobile sensing nodes (MSNs) are developed for SHM purposes. The MSNs can maneuver upon structures built with ferromagnetic/steel materials, conduct measurement, and communicate with pears or remote servers wirelessly. The performance of the MSNs is validated through laboratory and field experiments. To further investigate the mobile sensing strategy, a decentralized structural damage detection procedure is proposed herein for the MSNs using transmissibility functions. Laboratory experiments are conducted on a steel portal frame where various structure damage scenarios are emulated. Besides experiments with MSNs, this study also investigates the nature of transmissibility functions for damage detection in an analytical manner based on a general multi-DOF spring-mass-damper system. Finally, this research also explores substructure model updating through minimization of modal dynamic residuals, which can best benefit from dense mobile or wireless sensor data concentrated in one area. Craig-Bampton transform is adopted to condense the structural model, and minimization of the modal dynamic residuals is determined as the optimization objective. An iterative linearization procedure is adopted for efficiently solving the optimization problem. The presented substructure updating method is validated through a few numerical examples. For comparison, a conventional approach minimizing modal property differences is also applied, and shows worse updating accuracy than the proposed approach. The performance of the proposed substructure model updating approach is further investigated on the effects of substructure location and size.

In partnership with iMonSys - an emerging company in the passive care field - a new system, 'Verity', is being developed to fulfil the role of a passive behaviour monitoring and alert detection device, providing an unobtrusive level of care and assessing an individual's changing behaviour and health status whilst still allowing for independence of its elderly user. In this research, a Hidden Markov Model incorporating Fuzzy Logic-based sensor fusion is created for the behaviour detection within Verity, with a method of Fuzzy-Rule induction designed for the system's adaptation to a user during operation. A dimension reduction and classification scheme utilising Curvilinear Distance Analysis is further developed to deal with the recognition task presented by increasingly nonlinear and high dimension sensor readings, and anomaly detection methods situated within the Hidden Markov Model provide possible solutions to identification of health concerns arising from independent living. Real-time implementation is proposed through development of an Instance Based Learning approach in combination with a Bloom Filter, speeding up the classification operation and reducing the storage requirements for the considerable amount of observation data obtained during operation. Finally, evaluation of all algorithms is completed using a simulation of the Verity system with which the behaviour monitoring task is to be achieved.