Modulador óptico cuasiestático en la banda del infrarrojo basado en la ritf

Esta tesis doctoral contribuye a la búsqueda de alternativas para la sustitución de la técnica clásica demodulación de la radiación infrarroja, basada en unarueda "chopper". Esta técnica de modulación óptica, seutiliza en los sistemas de espectrofotometría e introducepartes móviles en estos equipos. Las partes móviles generan instrumentos voluminosos y de difícil transporte, puesto que los elementos mecánicos se pueden desajustar fácilmente. Trabajos recientes han conseguido eliminarlas partes móviles presentes en el sensor (tambores defiltros ópticos), pero todavía no se ha conseguido eliminar las partes móviles situadas en la fuente deinfrarrojos.De entre las diferentes alternativas planteadas, se hapropuesto profundizar en el estudio de una de ellas. Enconcreto, se profundiza en el estudio de un moduladoróptico cuasiestático basado en la Reflexión Interna TotalFrustrada, RITF. El fenómeno es ampliamente conocido,pero se ha detectado una falta de contribuciones en suaplicación a la modulación de radiación infrarroja, quetrata de resolverse abordandola en este trabajo.Uno de los puntos de estudio tratados es elfuncionamiento mecánico del modulador. Los resultadosobtenidos son vitales para realizar el control delsistema. El estudio realizado sobre la forma de laradiación de salida del modulador, es fundamental si sepretende introducir el modulador en un equipo deespectrofotometría. El último de los puntos en los quecentra su atención esta tesis doctoral, es en laobtención de algoritmos de control del modulador parapoder garantizar un funcionamiento estable del mism

Espectrometría infrarroja con array de fotodetectores

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Arc fault protections for aeronautic applications: a review identifying the effects, detection methods, current progress, limitations, future challenges, and research needs

©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Arc faults are serious discharges, damaging insulation systems and triggering electrical fires. This is a transversal topic, affecting from residential to aeronautic applications. Current commercial aircrafts are being progressively equipped with arc fault protections. With the development of more electric aircrafts (MEA), future airliners will require more electrical power to enhance fuel economy, save weight and reduce emissions. The ultimate goal of MEAs is electrical propulsion, where fault management devices will have a leading role, because aircraft safety is of utmost importance. Therefore, current fault management devices must evolve to fulfill the safety requirements of electrical propelled aircrafts. To deal with the increased electrical power generation, the distribution voltage must be raised, thus leading to new electrical fault types, in particular arc tracking and series arcing, which are further promoted by the harsh environments typical of aircraft systems, i.e., low pressure, extreme humidity and a wide range of temperatures. Therefore, the development of specific electrical protections which are able to protect against these fault types is a must. This paper reviews the state-of-the-art of electrical protections for aeronautic applications, identifying the current status and progress, their drawbacks and limitations, the future challenges and research needs to fulfill the future requirements of MEAs, with a special emphasis on series arc faults due to arc tracking, because of difficulty in detecting such low-energy faults in the early stage and the importance and harmful effects of tracking activity in cabling insulation systems. This technological and scientific review is based on a deep analysis of research and conference papers, official reports, white papers and international regulations.This research was partially funded by the Ministerio de Ciencia e Innovación de España, grant number PID2020-114240RB-I00 and by the Generalitat de Catalunya, grant number 2017 SGR 967.Peer ReviewedPostprint (author's final draft

Multiple-fault detection methodology based on vibration and current analysis applied to bearings in induction motors and gearboxes on the kinematic chain

© 2016 Juan Jose Saucedo-Dorantes et al. Gearboxes and induction motors are important components in industrial applications and their monitoring condition is critical in the industrial sector so as to reduce costs and maintenance downtimes. There are several techniques associated with the fault diagnosis in rotating machinery; however, vibration and stator currents analysis are commonly used due to their proven reliability. Indeed, vibration and current analysis provide fault condition information by means of the fault-related spectral component identification. This work presents a methodology based on vibration and current analysis for the diagnosis of wear in a gearbox and the detection of bearing defect in an induction motor both linked to the same kinematic chain; besides, the location of the fault-related components for analysis is supported by the corresponding theoretical models. The theoretical models are based on calculation of characteristic gearbox and bearings fault frequencies, in order to locate the spectral components of the faults. In this work, the influence of vibrations over the system is observed by performing motor current signal analysis to detect the presence of faults. The obtained results show the feasibility of detecting multiple faults in a kinematic chain, making the proposed methodology suitable to be used in the application of industrial machinery diagnosis.Postprint (published version

Industrial process monitoring by means of recurrent neural networks and Self Organizing Maps

Industrial manufacturing plants often suffer from reliability problems during their day-to-day operations which have the potential for causing a great impact on the effectiveness and performance of the overall process and the sub-processes involved. Time-series forecasting of critical industrial signals presents itself as a way to reduce this impact by extracting knowledge regarding the internal dynamics of the process and advice any process deviations before it affects the productive process. In this paper, a novel industrial condition monitoring approach based on the combination of Self Organizing Maps for operating point codification and Recurrent Neural Networks for critical signal modeling is proposed. The combination of both methods presents a strong synergy, the information of the operating condition given by the interpretation of the maps helps the model to improve generalization, one of the drawbacks of recurrent networks, while assuring high accuracy and precision rates. Finally, the complete methodology, in terms of performance and effectiveness is validated experimentally with real data from a copper rod industrial plant.Postprint (published version

Bearing fault diagnosis by EXIN CCA

EXIN CCA is an extension of the Curvilinear Component Analysis (CCA), which solves for the noninvariant CCA projection and allows representing data drawn under different operating conditions. It can be applied to data visualization, interpretation (as a kind of sensor of the underlying physical phenomenon) and classification for real time industrial applications. Here an example is given for bearing fault diagnostics in an electromechanical device.Peer ReviewedPostprint (published version

80C537 Microcontroller remote lab for e-learning teaching

A remote microcontroller lab based on an 80C537 mock-up is presented. This paper presents a new way to interact with these kinds of systems via the Internet, giving the possibility for complete interaction. The Citrix Application Server is the platform which manages the debugging microcontroller software, and National Instruments LabVIEW 8 is used to develop the applications which allow the interaction between the system and the remote user. By means of LabVIEW web server, full remote interaction has been achieved. Our results suggest a new way to practise in laboratories without being present, yet retaining the feel of an actual laboratory environment.Postprint (published version

Multimodal forecasting methodology applied to industrial process monitoring

IEEE Industrial process modelling represents a key factor to allow the future generation of industrial manufacturing plants. In this regard, accurate models of critical signals need to be designed in order to forecast process deviations. In this work a novel multimodal forecasting methodology based on adaptive dynamics packaging and codification of the process operation is proposed. First, a target signal is decomposed by means of the Empirical Mode Decomposition in order to identify the characteristics intrinsic mode functions. Second, such dynamics are packaged depending on their significance and modelling complexity. Third, the operating condition of the considered process, reflected by available auxiliary signals, is codified by means of a Self-Organizing Map and presented to the modelling structure. The forecasting structure is supported by a set of ensemble ANFIS based models, each one focused on a different set of signal dynamics. The performance and effectiveness of the proposed method is validated experimentally with industrial data from a copper rod manufacturing plant and performance comparison with classical approaches. The proposed method improves performance and generalization versus classical single model approaches.Peer ReviewedPostprint (author's final draft

Enhanced Industrial Machinery Condition Monitoring Methodology based on Novelty Detection and Multi-Modal Analysis

This paper presents a condition-based monitoring methodology based on novelty detection applied to industrial machinery. The proposed approach includes both, the classical classification of multiple a priori known scenarios, and the innovative detection capability of new operating modes not previously available. The development of condition-based monitoring methodologies considering the isolation capabilities of unexpected scenarios represents, nowadays, a trending topic able to answer the demanding requirements of the future industrial processes monitoring systems. First, the method is based on the temporal segmentation of the available physical magnitudes, and the estimation of a set of time-based statistical features. Then, a double feature reduction stage based on Principal Component Analysis and Linear Discriminant Analysis is applied in order to optimize the classification and novelty detection performances. The posterior combination of a Feed-forward Neural Network and One-Class Support Vector Machine allows the proper interpretation of known and unknown operating conditions. The effectiveness of this novel condition monitoring scheme has been verified by experimental results obtained from an automotive industry machine.Postprint (published version

Eines d’autor: avaluació de noves eines orientades al desenvolupament de competències genèriques per la millora del procés d’aprenentatge autònom dels estudiants

Els cursos on-line massius (Massive Open On-line Courses) estan emergent i suposarà un gran repte en l’educació universitària en els propers anys. Universitats com Standford i MIT han començat aquest any cursos en obert amb una matriculació de centenars de milers d’estudiants en les seves assignatures pilots. Aquests cursos es basen en deixar material docent en servidors, on els estudiants poden seguir en qualsevol moment, i des de qualsevol lloc el curs. Per generar aquest cursos, es necessari tenir bones eines que permetin generar bon material, i que el docent no necessiti concentrar-se en el programari, i si en els mètodes que desitgi aplicar. Dintre d’aquest objectiu, ja des de fa uns anys han aparegut unes eines anomenades “rapid eLearning Tools” que prometen generar materials didàctics de qualitat amb gran facilitat. Entenem per “eines ràpides”, aquelles que, amb uns coneixements a nivell d’usuari d’informàtica, les eines permeten obtenir productes multimèdia de bona qualitat, sense la necessitat de invertir un temps excessiu en la seva generació. Existeixen moltes eines ràpides d’autor a l’actualitat, amb una gran varietat de prestacions. Un dels objectius necessaris és conèixer les ofertes actuals en el mercat dels programaris i tenir una avaluació seguint uns criteris objectius. Aquests s’han definit amb criteris d’us del docent i impacte en el material obtingut.Peer Reviewe