Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

Adaptive edge analytics for distributed networked control of water systems

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.

Algorithme non intrusif de localisation et de correction de distorsions dans les signaux sonores compressés à bas débits

Des sites de visionnement de contenu audio-vidéo en temps-réel comme YouTube sont devenus très populaires. Le téléchargement des fichiers audio/vidéo consomme une quantité importante de bande passante des réseaux Internet. L’utilisation de codecs à bas débit permet de compresser la taille des fichiers transmis afin de consommer moins de bande passante. La conséquence est une diminution de la qualité de ce qui est transmis. Une diminution de qualité mène à l’apparition de défauts perceptibles dans les fichiers. Ces défauts sont appelés des artifices de compression. L’utilisation d’un algorithme de post-traitement sur les fichiers sonores pourrait augmenter la qualité perçue de la musique transmise en corrigeant certains artifices à la réception, sans toutefois consommer davantage de bande passante. Pour rehausser la qualité subjective des fichiers sonores, il est d’abord nécessaire de déterminer quelles caractéristiques dégradent la qualité perceptuelle. Le présent projet a donc pour objectif le développement d’un algorithme capable de localiser et de corriger de façon non intrusive, un artifice provoqué par des discontinuités et des incohérences au niveau des harmoniques qui dégrade la qualité objective dans les signaux sonores compressés à bas débits (8 – 12 kilobits par seconde).

Tracing the Cambro-Ordovician ferrosilicic to calc-alkaline magmatic

U–Pb geochronological study of zircons from nodular granites and Qtz-diorites comprising part of Variscan high- grade metamorphic complexes in Gredos massif (Spanish Central System batholith) points out the significant presence of Cambro-Ordovician protoliths among the Variscan migmatitic rocks that host the Late Carboniferous intrusive granitoids. Indeed, the studied zone was affected by two contrasted tectono-magmatic episodes, Car- boniferous (Variscan) and Cambro-Ordovician. Three main characteristics denote a close relation between the Cambro-Ordovician protholiths of the Prado de las Pozas high-grade metamorphic complex, strongly reworked during the Variscan Orogeny, and other Cambro-Ordovician igneous domains in the Central Iberian Zone of the Iberian Massif: (1) geochemical features show the ferrosilicic signature of nodular granites. They plot very close to the average analysis of themetavolcanic rocks of the Ollo de Sapo formation (Iberia). Qtz-diorites present typical calc-alkaline signatures and are geochemically similar to intermediate cordilleran granitoids. (2) Both Qtz-diorite and nodular granite samples yield a significant population of Cambro-Ordovician ages, ranging between 483 and 473 Ma and between 487 and 457 Ma, respectively. Besides, (3) the abundance of zircon inher- itance observed on nodular granites matches the significant component of inheritance reported on Cambro- Ordovician metagranites and metavolcanic rocks of central and NW Iberia. The spatial and temporal coincidence of both peraluminous and intermediate granitoids, and specifically in nodular granites and Qtz-diorite enclaves of the Prado de las Pozas high-grade complex, is conducive to a common petrogenetic context for the formation of both magmatic types. Tectonic and geochemical characteristics describe the activity of a Cambro-Ordovician arc-back-arc tectonic set- ting associated with the subduction of the Iapetus–Tornquist Ocean and the birth of the Rheic Ocean. The exten- sional setting is favorable for the generation, emplacement, and fast rise of subduction-related cold diapirs, supported by the presence of typical calc-alkaline cordilleran granitoids contemporary with ferrosilicic volcanism.

Deposition of thin films by a non-equilibrium atmospheric pressure Plasma Jet: a poly-diagnostic study

The use of atmospheric pressure plasmas for thin film deposition on thermo-sensitive materials is currently one of the main challenges of the plasma scientific community. Despite the growing interest in this field, the existing knowledge gap between gas-phase reaction mechanisms and thin film properties is still one of the most important barriers to overcome for a complete understanding of the process. In this work, thin films surface characterization techniques, combined with passive and active gas-phase diagnostic methods, were used to provide a comprehensive study of the Ar/TEOS deposition process assisted by an atmospheric pressure plasma jet. SiO2-based thin films exhibiting a well-defined chemistry, a good morphological structure and high uniformity were studied in detail by FTIR, XPS, AFM and SEM analysis. Furthermore, non-intrusive spectroscopy techniques (OES, filter imaging) and laser spectroscopic methods (Rayleigh scattering, LIF and TALIF) were employed to shed light on the complexity of gas-phase mechanisms involved in the deposition process and discuss the influence of TEOS admixture on gas temperature, electron density and spatial-temporal behaviours of active species. The poly-diagnostic approach proposed in this work opens interesting perspectives both in terms of process control and optimization of thin film performances.

Mitigating non-Lambertian surfaces issues in Stereo Matching with Neural Radiance Fields

Depth estimation from images has long been regarded as a preferable alternative compared to expensive and intrusive active sensors, such as LiDAR and ToF. The topic has attracted the attention of an increasingly wide audience thanks to the great amount of application domains, such as autonomous driving, robotic navigation and 3D reconstruction. Among the various techniques employed for depth estimation, stereo matching is one of the most widespread, owing to its robustness, speed and simplicity in setup. Recent developments has been aided by the abundance of annotated stereo images, which granted to deep learning the opportunity to thrive in a research area where deep networks can reach state-of-the-art sub-pixel precision in most cases. Despite the recent findings, stereo matching still begets many open challenges, two among them being finding pixel correspondences in presence of objects that exhibits a non-Lambertian behaviour and processing high-resolution images. Recently, a novel dataset named Booster, which contains high-resolution stereo pairs featuring a large collection of labeled non-Lambertian objects, has been released. The work shown that training state-of-the-art deep neural network on such data improves the generalization capabilities of these networks also in presence of non-Lambertian surfaces. Regardless being a further step to tackle the aforementioned challenge, Booster includes a rather small number of annotated images, and thus cannot satisfy the intensive training requirements of deep learning. This thesis work aims to investigate novel view synthesis techniques to augment the Booster dataset, with ultimate goal of improving stereo matching reliability in presence of high-resolution images that displays non-Lambertian surfaces.