On the identifiability, parameter identification and fault diagnosis of induction machines

PhD ThesisDue to their reliability and low cost, induction machines have been widely utilized in a large variety of industrial applications. Although these machines are rugged and reliable, they are subjected to various stresses that might result in some unavoidable parameter changes and modes of failures. A common practice in induction machine parameter identification and fault diagnosis techniques is to employ a machine model and use the external measurements of voltage, current, speed, and/or torque in model solution. With this approach, it might be possible to get an infinite number of mathematical solutions representing the machine parameters, depending on the employed machine model. It is therefore crucial to investigate such possibility of obtaining incorrect parameter sets, i.e. to test the identifiability of the model before being used for parameter identification and fault diagnosis purposes. This project focuses on the identifiability of induction machine models and their use in parameter identification and fault diagnosis. Two commonly used steady-states induction machine models namely T-model and inverse Γ- model have been considered in this thesis. The classical transfer function and bond graph identifiability analysis approaches, which have been previously employed for the T-model, are applied in this thesis to investigate the identifiability of the inverse Γ-model. A novel algorithm, the Alternating Conditional Expectation, is employed here for the first time to study the identifiability of both the T- and inverse Γ-models of the induction machine. The results obtained from the proposed algorithm show that the parameters of the commonly utilised Tmodel are non-identifiable while those of the inverse Γ-model are uniquely identifiable when using external measurements. The identifiability analysis results are experimentally verified by the particle swarm optimization and Levenberg-Marquardt model-based parameter identification approaches developed in this thesis. To overcome the non-identifiability problem of the T-model, a new technique for induction machine parameter estimation from external measurements based on a combination of the induction machine’s T- and inverse Γ-models is proposed. Results for both supply-fed and inverter-fed operations show the success of the technique in identifying the parameters of the machine using only readily available measurements of steady-state machine current, voltage and speed, without the need for extra hardware. ii A diagnosis scheme to detect stator winding faults in induction machines is also proposed in this thesis. The scheme uses time domain features derived from 3-phase stator currents in conjunction with particle swarm optimization algorithm to check characteristic parameters of the machine and detect the fault accordingly. The validity and effectiveness of the proposed technique has been evaluated for different common faults including interturn short-circuit, stator winding asymmetry (increased resistance in one or more stator phases) and combined faults, i.e. a mixture of stator winding asymmetry and interturn short-circuit. Results show the accuracy of the proposed technique and it is ability to detect the presence of the fault and provide information about its type and location. Extensive simulations using Matlab/SIMULINK and experimental tests have been carried out to verify the identifiability analysis and show the effectiveness of the proposed parameter identification and fault diagnoses schemes. The constructed test rig includes a 1.1 kW threephase test induction machine coupled to a dynamometer loading unit and driven by a variable frequency inverter that allows operation at different speeds. All the experiment analyses provided in the thesis are based on terminal voltages, stator currents and rotor speed that are usually measured and used in machine control.Libya, through the Engineering Faculty of Misurata- Misurata Universit

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Active Backscattering Positioning System Using Innovative Harmonic Oscillator Tags for Future Internet of Things: Theory and Experiments

RÉSUMÉ D'ici 2020, l'Internet des objets (IoT) permettra probablement de créer 25 milliards d'objets connectés, 44 ZB de données et de débloquer 11 000 milliards de dollars d’opportunités commerciales. Par conséquent, ce sujet a suscité d’énormes intérêts de recherche dans le monde académique entier. L'une des technologies clés pour l'IoT concerne le positionnement physique intérieur précis. Le principal objectif dans ce domaine est le développement d'un système de positionnement intérieur avec une grande précision, une haute résolution, un fonctionnement à plusieurs cibles, un faible coût, un faible encombrement et une faible consommation d'énergie. Le système de positionnement intérieur conventionnel basé sur les technologies de Wi-Fi ou d'identification par radiofréquence (RFID) ne peut répondre à ces exigences. Principalement parce que leur appareil et leur signal ne sont pas conçus spécialement pour atteindre les objectifs visés. Les chercheurs ont découvert qu'en mettant en oeuvre de différents types de modulation sur les étiquettes, le radar à onde continue (CW) et ses dérivés deviennent des solutions prometteuses. Les activités de recherche présentées dans cette thèse sont menées dans le but de développer des systèmes de positionnement en intérieur bidimensionnel (2-D) à plusieurs cibles basées sur des étiquettes actives à rétrodiffusion harmonique avec une technique à onde continue modulée en fréquence (FMCW). Les contributions de cette thèse peuvent être résumées comme suit: Tout d'abord, la conception d'un circuit actif harmonique, plus spécifiquement une classe d'oscillateurs harmoniques innovants utilisée comme composant central des étiquettes actives dans notre système, implique une méthodologie de conception de signal de grande taille et des installations de caractérisation. L’analyseur de réseau à grand signal (LSNA) est un instrument émergent basé sur les fondements théoriques du cadre de distorsion polyharmonique (PHD). Bien qu'ils soient disponibles dans le commerce depuis 2008, des organismes de normalisation et de recherche tels que l’Institut national des normes et de la technologie (NIST) des États-Unis travaillent toujours à la mise au point d'un standard largement reconnu permettant d'évaluer et de comparer leurs performances. Dans ce travail, un artefact de génération multi-harmonique pour la vérification LSNA est développé. C'est un dispositif actif capable de générer les 5 premières harmoniques d'un signal d'entrée avec une réponse ultra-stables en amplitude et en phase, quelle que soit la variation de l'impédance de la charge.----------ABSTRACT By 2020, the internet of things (IoT) will probably enable 25 billion connected objects, create 44 ZB data and unlock 11 trillion US dollar business opportunities. Therefore, this topic has been attracting tremendous research interests in the entire academic world. One of the key enabling technologies for IoT is concerned with accurate indoor physical positioning. The development of such an indoor positioning system with high accuracy, high resolution, multitarget operation, low cost, small footprint, and low power consumption is the major objective in this area. The conventional indoor positioning system based on WiFi or radiofrequency identification (RFID) technology cannot fulfill these requirements mainly because their device and signal are not purposely designed for achieving the targeted goals. Researchers have found that by implementing different types of modulation on the tags, continuous-wave (CW) radar and its derivatives become promising solutions. The research activities presented in this Ph.D. thesis are carried out towards the goal of developing multitarget two-dimensional (2-D) indoor positioning systems based on harmonic backscattering active tags together with a frequency-modulated continuous-wave (FMCW) technique. Research contributions of this thesis can be summarized as follows: First of all, the design of a harmonic active circuit, more specifically, a class of innovative harmonic oscillators used as the core component of active tags in our system, involves a large signal design methodology and characterization facilities. The large signal network analyzer (LSNA) is an emerging instrument based on the theoretical foundation for the Poly-Harmonic Distortion (PHD) framework. Although they have been commercially available since 2008, standard and research organizations such as the National Institute of Standards and Technology (NIST) of the US are still working towards a widely-recognized standard to evaluate and cross-reference their performances. In this work, a multi-harmonic generation artifact for LSNA verification is developed. It is an active device that can generate the first 5 harmonics of an input signal with ultra-stable amplitude and phase response regardless of the load impedance variation

Aeronautical engineering: A cumulative index to a continuing bibliography

This bibliography is a cumulative index to the abstracts contained in NASA SP-7037(210) through NASA SP-7037(221) of Aeronautical Engineering: A Continuing Bibliography. NASA SP-7037 and its supplements have been compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). This cumulative index includes subject, personal author, corporate source, foreign technology, contract number, report number, and accession number indexes

Reports to the President

A compilation of annual reports including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans