This thesis presents a research work on the development of new methodology for near-real-time detection and localisation of pipe bursts in a Water Distribution System (WDS) at the District Meters Area (DMA) level. The methodology makes use of online hydraulic model coupled with a demand forecasting methodology and several statistical techniques to process the hydraulic meters data (i.e., flows and pressures) coming from the field at regular time intervals (i.e. every 15 minutes). Once the detection part of the methodology identifies a potential burst occurrence in a system it raises an alarm. This is followed by the application of the burst localisation methodology to approximately locate the event within the District Metered Area (DMA). The online hydraulic model is based on data assimilation methodology coupled with a short-term Water Demand Forecasting Model (WDFM) based on Multi-Linear Regression. Three data assimilation methods were tested in the thesis, namely the iterative Kalman Filter method, the Ensemble Kalman Filter method and the Particle Filter method. The iterative Kalman Filter (i-KF) method was eventually chosen for the online hydraulic model based on the best overall trade-off between water system state prediction accuracy and computational efficiency. The online hydraulic model created this way was coupled with the Statistical Process Control (SPC) technique and a newly developed burst detection metric based on the moving average residuals between the predicted and observed hydraulic states (flows/pressures). Two new SPC-based charts with associated generic set of control rules for analysing burst detection metric values over consecutive time steps were introduced to raise burst alarms in a reliable and timely fashion. The SPC rules and relevant thresholds were determined offline by performing appropriate statistical analysis of residuals. The above was followed by the development of the new methodology for online burst localisation. The methodology integrates the information on burst detection metric values obtained during the detection stage with the new sensitivity matrix developed offline and hydraulic model runs used to simulate potential bursts to identify the most likely burst location in the pipe network. A new data algorithm for estimating the ‘normal’ DMA demand and burst flow during the burst period is developed and used for localisation. A new data algorithm for statistical analysis of flow and pressure data was also developed and used to determine the approximate burst area by producing a list of top ten suspected burst location nodes. The above novel methodologies for burst detection and localisation were applied to two real-life District Metred Areas in the United Kingdom (UK) with artificially generated flow and pressure observations and assumed bursts. The results obtained this way show that the developed methodology detects pipe bursts in a reliable and timely fashion, provides good estimate of a burst flow and accurately approximately locates the burst within a DMA. In addition, the results obtained show the potential of the methodology described here for online burst detection and localisation in assisting Water Companies (WCs) to conserve water, save energy and money. It can also enhance the UK WCs’ profile customer satisfaction, improve operational efficiency and improve the OFWAT’s Service Incentive Mechanism (SIM) scores.

La déformation des signaux au long de leur trajet de propagation est un des plus importants facteurs qui doivent être considérés à la réception. Ces effets sont dus à des phénomènes comme l’atténuation, la réflexion, la dispersion et le bruit. Alors que les premiers deux phénomènes sont assez facile à surveiller, parce qu’elles affectent l’amplitude, respectivement le retard des signaux, les deux derniers phénomènes sont plus difficiles à contrôler, parce qu’elles changent les paramètres du signal (amplitude, fréquence et phase) de manière totalement dépendante de l’environnement.Dans cette thèse, l’objectif principal est de contribuer à l’analyse des signaux liés aux différents phénomènes physiques, en visant une meilleure compréhension de ces phénomènes, ainsi que l’estimation de leurs paramètres qui sont intéressants de point de vue applicatif. Plusieurs contextes applicatifs ont été investigués dans deux configurations de : active et passive.Pour la configuration active, le premier contexte applicatif consiste en l’étude du phénomène de cavitation dans le domaine de la surveillance de systèmes hydrauliques. La deuxième application de la configuration active est la détection et le suivi des objets immergés sans synchronisation entre les capteurs d’émission et de réception.Pour la configuration passive, nous nous concentrons sur l’analyse des transitoires de pression dans les conduites d’eau en utilisant une méthode non-intrusive ainsi que sur la surveillance des réseaux d’énergie électrique en présence des phénomènes transitoires comme les arcs électriques.Malgré les différences entre les considérations physiques spécifiques à ces applications, nous proposons un modèle mathématique unique pour les signaux issus des deux types de configurations. Le modèle est basé sur l’analyse des récurrences. Avec ce concept, nous proposons une nouvelle approche pour les ondes basées sur l’espace des phases. Cette technique de construction des formes d’ondes présente l’intérêt de conduire à des méthodes de d’investigation active à haut cadence, très utiles pour la surveillance des phénomènes dynamiques.En plus, nous proposons des approches nouvelles pour l’investigation des caractéristiques des signaux. La première est la mesure TDR* (Time Distributed Recurrences) qui quantifie la matrice des récurrences/ distances et qui est utilisée pour la détection des signaux transitoires. La deuxième approche est l’analyse des phases à plusieurs retards et elle est utilisée pour la discrimination entre des signaux avec des paramètres très proches. Finalement, la quantification des lignes diagonales de la matrice des récurrences est proposée comme alternative pour l’analyse des signaux modulés en fréquence.Les travaux présentent les résultats expérimentaux en utilisant les méthodes théorétiques proposées dans cette thèse. Les résultats sont comparés avec des techniques classiques.Des perspectives de ces travaux, tant dans les domaines théorique et qu’applicatif, sont discutés à la fin du mémoire. / Signals’ deformation along their propagation path is among the most important aspect which has to be taken into account at reception. These effects are caused by phenomena like attenuation, reflection, dispersion and noise. Whereas the first two are rather easy to monitor, because they affect the amplitude, respectively the delay, the latter two are more difficult to control, because they change signals’ parameters (amplitude, frequency and phase) in an environment-dependent manner.In this thesis, the main objective is to contribute to the analysis of signals related to different physical phenomena, aiming to better understand them as well as to estimate their parameters that are interesting from application point of view. Different applicative contexts have been investigated in active and passive sensing configurations. For the active part, we mention the monitoring of cavitation phenomena and its characterization for hydraulic system surveillance. The second application of the active sensing is the underwater object detection and tracking without synchronization between sensors. For the passive configuration, we focus on the pressure transient analysis in water pipes investigation with a non-intrusive method and on the surveillance of electrical power systems in the presence of transient phenomena such as electrical arcs.Despite the differences between the physical considerations, we propose a unique mathematical model of the signals issued from the active/passive sensing system used to analyze the considered phenomena. This model is based on the Recurrence Plot Analysis (RPA) method. With this concept, we propose the phase-space based waveform design. This waveform design technique presents the interest to conduct to a high speed sensing methods, very useful to monitor dynamic phenomena.Moreover, we propose new tools for the investigation of the signals characteristics. The first one is the TDR* measure (Time Distributed Recurrences) that quantifies the recurrence/ distance matrix and it is used for the detection of transient signals. The second one is the multi-lag phase analysis using multiple lags and it is successfully used to discriminate between signals with close parameters. Finally, the diagonal lines quantification of RPA matrix is proposed as an alternative for the analysis of modulated signals.Our work presents the experimental results using the proposed theoretical methods introduced by this thesis. The results are compared with classical techniques.The perspectives of this thesis are presented at the end of this paper.