Integración con Cymdist de las redes de media tensión y subtransmisión del sistema de la Centrosur

El presente trabajo tiene un enfoque práctico e innovador de la explotación del software de simulación Cymdist, que persigue la integración de los sistemas de media tensión y subtransmisión de la E.E.R.C.S que actualmente se modelan en plataformas distintas como son Cymdist y DIgSILENT respectivamente. El enfoque de Cymdist para modelar redes de distribución frente a DIgSILENT con un enfoque a nivel de control y operación de SEP, concluyen en ventajas como es principalmente: la modelación detallada de subestaciones y redes secundarias con la posibilidad de referenciarles geográficamente, la implementación de algoritmos como son el método de caída de tensión en la resolución de flujos de carga y la distribución de carga. El gran potencial que ofrece Cymdist permitió que se modele los sistemas de media tensión y subtransmisión por separado, evaluando el sistema de forma tradicional, y a la hora de realizar la integración el sistema de subtransmisión creado se configuró de tal manera que la integración se realice en pocos segundos, con los alimentadores conectándose automáticamente a sus respectivas subestaciones. Finalmente se presenta en una sola plataforma las redes de media tensión y subtransmisión, eliminando así los equivalentes de red que actualmente se tienen en el sistema de media tensión, este sistema integrado permitirá un análisis de: planificación, diseño y funcionamiento del sistema de la CENTROSUR, ayudando a la toma de decisiones rápidas y efectivas en la parte operativa de las redes eléctricas.This paper has an approach practical and innovative of the exploitation of software of simulation Cymdist, which fallow the integration of the systems the half voltage and subtransmisión of E.E.R.C.S that currently the model in platforms different that are Cymdist and DIgSILENT respectively. The approach of Cymdist to model networks of distribution front of DIgSILENT with an approach a level of control and operation of SEP, conclude in advantages that is the first: the model details of substations and networks seconds with the possibility of references geographically, the implementation of algorithms that are the method of voltage drop in the resolution of the power flow and the load distribution. The great potential that gives Cymdist allowed is modeled half voltage systems and subtransmisión separately; evaluating the traditional system, system was configured so that the integration is performed in few seconds, with feeders automatically connecting to their respective substations. Finally we present on a single platform the networks of half voltage and subtransmisión, deleting that the networks equivalents currently have in the half voltage system, this integrated system will allow analysis of: planning, design and operation of the system of the CENTROSUR, helping to take decisions quick and effectives in the part operational of the electrics networks.Ingeniero EléctricoCuenc

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

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

Modelo de creacion de valor

136 p.Este trabajo se enmarco dentro del área de política de negocios, específicamente en el uso de una herramienta para la implementación estratégica. Esta herramienta la denominamos "GVA" (Gestión por Valor Agregado), las firmas de consultaría financiera usan distintos nombres pero a fin de cuentas están midiendo lo mismo, la creación o destrucción de valor. Este índice se uso para medir si las decisiones tomadas en la empresa crearan valor para los accionistas, trabajadores y sociedad. Consistió básicamente en descubrir cuales son las palancas claves o las actividades que se desarrollan en la empresa y que ayudan a crear valor, medido a través del GVA, que consiste en que: a los flujos de caja descontados, restarles el costo del capital que se utilizo para generar esos flujos de caja. La metodología utilizada consistió en contactar una empresa de la industria del vino, conocerla a fondo, obtener datos generales, financieros y proyecciones a futuro, luego calcular la creación o destrucción de valor de cinco anos a la fecha, construir la malla de actividades y descubrir sus palancas claves a través de un análisis de sensibilidad y de maximización. Se encontraron 11 palancas claves o actividades que al sufrir una pequeña variación incrementaban el valor de la empresa en un 24% y que el 60% de estas palancas se encuentran en la parte operacional que es donde se tiene el mayor control de las variables. Términos Claves: Creación de Valor, Gestión por Valor Agregado, Palancas Claves, R.O.N.I., Capital Invertido, ROIC, WACC, Modelo de Creación de Valor

INTERACCIÓN ENTRE GENÉTICA Y ESTILO DE VIDA EN EL DESARROLLO DE LA DIABETES MELLITUS TIPO 2: EL ESTUDIO EN LOS INDIOS PIMA/ GENETIC-LIFE STYLE INTERACTIONS IN TYPE 2 DIABETES MELLITUS DEVELOPMENT: THE PIMA INDIANS STUDY

La creciente prevalencia de diabetes mellitus tipo 2 (DT2) representa un problema complejo de salud pública a nivel mundial y particularmente en países en desarrollo, incluyendo México. La DT2 es resultado de una interacción entre la predisposición genética y los cambios drásticos en el estilo de vida. El objetivo de este trabajo de revisión es explorar la interacción entre la genética y el estilo de vida sobre el desarrollo de la DT2, comparando dos grupos genéticamente relacionados, Pimas mexicanos y Pimas de Estados Unidos de América (EUA), así como dos grupos no relacionados genéticamente, pero viviendo en ambientes similares, Pimas mexicanos y no-Pimas (Blancos) de Maycoba, México. En comparación con los Pimas de EUA, los Indios Pima Mexicanos presentaron menor prevalencia de DT2 y obesidad. Asimismo, los Indios Pima Mexicanos presentaron menor consumo de grasa y fibra dietaria, y mayor nivel de actividad física. El estudio de los indios Pima nos indica que aún en poblaciones genéticamente predispuestas a estas condiciones, su desarrollo puede estar determinado principalmente por circunstancias relacionadas con el estilo de vida. ABSTRACT Globally, the increase in Type 2 Diabetes (T2D) prevalence represents a complex public health problem, particularly in developing countries, including Mexico. Type 2 diabetes results from an interaction between genetic predisposition and drastic changes in lifestyle. The aim of this review is to explore these interactions on T2D development, using the Mexican and US Pima Indians comparative study as a model; two genetic related groups, living in different environments, and Mexican Pimas and non-Pimas (Blancos) sharing a similar environment, but not the genetics. Study results showed a lower T2D and obesity prevalence in Mexican Pimas when compared with US Pimas. Likewise, Mexican Pimas had lower fat consumption, higher dietary fiber and higher physical activity than their counterparts in the US. The Pima Indians study showed that even in genetically predisposed populations, T2D development could be mainly determined by lifestyle related factors

Vibration-based adaptive novelty detection method for monitoring faults in a kinematic chain

Postprint (published version

Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods

"(c) 2018 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"[EN] Induction motors are used in a variety of industrial applications where frequent startup cycles are required. In those cases, it is necessary to apply sophisticated signal processing analysis methods in order to reliably follow the time evolution of fault-related harmonics in the signal. In this paper, the zero-sequence current (ZSC) is analyzed using the high-resolution spectral method of multiple signal classification. The analysis of the ZSC signal has proved to have several advantages over the analysis of a single-phase current waveform. The method is validated through simulation and experimental results. The simulations are carried out for a 1.1-MW and a 4-kW induction motors under finite element analysis. Experimentation is performed on a healthy motor, a motor with one broken rotor bar, and a motor with two broken rotor bars. The analysis results are satisfactory since the proposed methodology reliably detects the broken rotor bar fault and its severity, both during transient and steady-state operation of the induction motor.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and in part by the FEDER program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P.Morinigo-Sotelo, D.; Romero-Troncoso, R.; Panagiotou, P.; Antonino-Daviu, J.; Gyftakis, KN. (2018). Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods. IEEE Transactions on Industry Applications. 54(2):1224-1234. https://doi.org/10.1109/TIA.2017.2764846S1224123454

Magnetic Flux Analysis for the Condition Monitoring of Electric Machines: A Review

[EN] Magnetic flux analysis is a condition monitoring technique that is drawing the interest of many researchers and motor manufacturers. The great enhancements and reduction in the costs and dimensions of the required sensors, the development of advanced signal processing techniques that are suitable for flux data analysis, along with other inherent advantages provided by this technology are relevant aspects that have allowed the proliferation of flux-based techniques. This paper reviews the most recent scientific contributions related to the development and application of flux-based methods for the monitoring of rotating electric machines. Particularly, aspects related to the main sensors used to acquire magnetic flux signals as well as the leading signal processing and classification techniques are commented. The discussion is focused on the diagnosis of different types of faults in the most common rotating electric machines used in industry, namely: squirrel cage induction machines (SCIM), wound rotor induction machines (WRIM), permanent magnet machines (PMM) and wound field synchronous machines (WFSM). A critical insight of the techniques developed in the area is provided and several open challenges are also discussed.This work was supported by the Spanish 'Ministerio de Ciencia Innovación y Universidades' and FEDER program in the framework of the "Proyectos de I+D de Generación de Conocimiento del Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnologico del Sistema de I+D+i, Subprograma Estatal de Generacion de Conocimiento" reference PGC2018-095747-B-I00 and by the Consejo Nacional de Ciencia y Tecnología under CONACyT Scholarship with key code 2019-000037-02NACF. Paper no. TII-20-5308.Zamudio-Ramírez, I.; Osornio-Rios, RA.; Antonino-Daviu, J.; Razik, H.; Romero-Troncoso, RDJ. (2022). Magnetic Flux Analysis for the Condition Monitoring of Electric Machines: A Review. IEEE Transactions on Industrial Informatics. 18(5):2895-2908. https://doi.org/10.1109/TII.2021.30705812895290818