Calculation Methodology and Fabrication Procedures for Particle Accelerator Strip-Line Kickers: Application to the CTF3 Combiner Ring Extraction Kicker and TL2 Tail Clippers

A particle accelerator is any device that, using electromagnetic fields, is able to communicate energy to charged particles (typically electrons or ionized atoms), accelerating and/or energizing them up to the required level for its purpose. The applications of particle accelerators are countless, beginning in a common TV CRT, passing through medical X-ray devices, and ending in large ion colliders utilized to find the smallest details of the matter. Among the other engineering applications, the ion implantation devices to obtain better semiconductors and materials of amazing properties are included. Materials supporting irradiation for future nuclear fusion plants are also benefited from particle accelerators. There are many devices in a particle accelerator required for its correct operation. The most important are the particle sources, the guiding, focalizing and correcting magnets, the radiofrequency accelerating cavities, the fast deflection devices, the beam diagnostic mechanisms and the particle detectors. Most of the fast particle deflection devices have been built historically by using copper coils and ferrite cores which could effectuate a relatively fast magnetic deflection, but needed large voltages and currents to counteract the high coil inductance in a response in the microseconds range. Various beam stability considerations and the new range of energies and sizes of present time accelerators and their rings require new devices featuring an improved wakefield behaviour and faster response (in the nanoseconds range). This can only be achieved by an electromagnetic deflection device based on a transmission line. The electromagnetic deflection device (strip-line kicker) produces a transverse displacement on the particle beam travelling close to the speed of light, in order to extract the particles to another experiment or to inject them into a different accelerator. The deflection is carried out by the means of two short, opposite phase pulses. The diversion of the particles is exerted by the integrated Lorentz force of the electromagnetic field travelling along the kicker. This Thesis deals with a detailed calculation, manufacturing and test methodology for strip-line kicker devices. The methodology is then applied to two real cases which are fully designed, built, tested and finally installed in the CTF3 accelerator facility at CERN (Geneva). Analytical and numerical calculations, both in 2D and 3D, are detailed starting from the basic specifications in order to obtain a conceptual design. Time domain and frequency domain calculations are developed in the process using different FDM and FEM codes. The following concepts among others are analyzed: scattering parameters, resonating high order modes, the wakefields, etc. Several contributions are presented in the calculation process dealing specifically with strip-line kicker devices fed by electromagnetic pulses. Materials and components typically used for the fabrication of these devices are analyzed in the manufacturing section. Mechanical supports and connexions of electrodes are also detailed, presenting some interesting contributions on these concepts. The electromagnetic and vacuum tests are then analyzed. These tests are required to ensure that the manufactured devices fulfil the specifications. Finally, and only from the analytical point of view, the strip-line kickers are studied together with a pulsed power supply based on solid state power switches (MOSFETs). The solid state technology applied to pulsed power supplies is introduced and several circuit topologies are modelled and simulated to obtain fast and good flat-top pulses.

Técnicas de análisis, caracterización y detección de señales de voz en entornos acústicos adversos

Este trabajo de Tesis ha abordado el objetivo de dar robustez y mejorar la Detección de Actividad de Voz en entornos acústicos adversos con el fin de favorecer el comportamiento de muchas aplicaciones vocales, por ejemplo aplicaciones de telefonía basadas en reconocimiento automático de voz, aplicaciones en sistemas de transcripción automática, aplicaciones en sistemas multicanal, etc. En especial, aunque se han tenido en cuenta todos los tipos de ruido, se muestra especial interés en el estudio de las voces de fondo, principal fuente de error de la mayoría de los Detectores de Actividad en la actualidad. Las tareas llevadas a cabo poseen como punto de partida un Detector de Actividad basado en Modelos Ocultos de Markov, cuyo vector de características contiene dos componentes: la energía normalizada y la variación de la energía. Las aportaciones fundamentales de esta Tesis son las siguientes: 1) ampliación del vector de características de partida dotándole así de información espectral, 2) ajuste de los Modelos Ocultos de Markov al entorno y estudio de diferentes topologías y, finalmente, 3) estudio e inclusión de nuevas características, distintas de las del punto 1, para filtrar los pulsos de pronunciaciones que proceden de las voces de fondo. Los resultados de detección, teniendo en cuenta los tres puntos anteriores, muestran con creces los avances realizados y son significativamente mejores que los resultados obtenidos, bajo las mismas condiciones, con otros detectores de actividad de referencia. This work has been focused on improving the robustness at Voice Activity Detection in adverse acoustic environments in order to enhance the behavior of many vocal applications, for example telephony applications based on automatic speech recognition, automatic transcription applications, multichannel systems applications, and so on. In particular, though all types of noise have taken into account, this research has special interest in the study of pronunciations coming from far-field speakers, the main error source of most activity detectors today. The tasks carried out have, as starting point, a Hidden Markov Models Voice Activity Detector which a feature vector containing two components: normalized energy and delta energy. The key points of this Thesis are the following: 1) feature vector extension providing spectral information, 2) Hidden Markov Models adjustment to environment and study of different Hidden Markov Model topologies and, finally, 3) study and inclusion of new features, different from point 1, to reject the pronunciations coming from far-field speakers. Detection results, taking into account the above three points, show the advantages of using this method and are significantly better than the results obtained under the same conditions by other well-known voice activity detectors.