Sistema de control para una turbina eólica

La potencia entregada por las turbinas eólicas es afectada por las constantesfluctuaciones en la velocidad y dirección del viento, razón por la cual se hace necesariala utilización de sistemas de control que permitan un buen rendimiento de losaerogeneradores. En este trabajo se proponen dos sistemas de control PIindependientes; el primer sistema de control permite la regulación del ángulo de ataquedel viento en las aspas de la turbina a través de un actuador electromagnético; por otraparte, el segundo sistema de control orienta la góndola hacia la velocidad de vientopredominante

Celdas de combustible con convertidores elevadores para energías alternativas

The need for energy in the world has led to the search for new ways of electric power generation, among which is the use of fuel cells as a renewable source that does not contribute to environmental pollution and has high efficiency in energy conversion. In this type of technology the system suffers voltage fluctuations due to the connected loads. Booster converters of boost type are used, which allow to regulate the tension to an optimal value, without great fluctuations. We chose the design of the PI type control by means of the state space method to obtain the transfer functions, and the Routh-Hurwitz criterion to obtain the constants of the PI controller. A fuel cell system of 1 kW was simulated keeping the regulator output voltage at 48 V constant with an overvoltage not greater than 30% of the desired value.The need for energy in the world has led to the search for new ways of electric power generation, among which is the use of fuel cells as a renewable source that does not contribute to environmental pollution and has high efficiency in energy conversion. In this type of technology the system suffers voltage fluctuations due to the connected loads. Booster converters of boost type are used, which allow to regulate the tension to an optimal value, without great fluctuations. We chose the design of the PI type control by means of the state space method to obtain the transfer functions, and the Routh-Hurwitz criterion to obtain the constants of the PI controller. A fuel cell system of 1 kW was simulated keeping the regulator output voltage at 48 V constant with an overvoltage not greater than 30% of the desired value

Evaluación de la eficiencia de un calentador solar de tubos evacuados implementado con una tarjeta Arduino Mega

El siguiente documento presenta el rendimiento térmico obtenido de un sistema de calentamiento de agua de tubos evacuados; caracterizado y evaluado en el Campus Universitario Siglo XXI de la Universidad Autónoma de Zacatecas. Donde se refleja la evaluación del sistema operando dinámicamente, con el objetivo de describir la existencia de afecciones por nubosidad y mala estratificación del fluido las cuales provocan la caída de la eficiencia del colector. Por ende al obtener las curvas de operación del sistema y realizar un ajuste lineal, se observan que las afecciones provocadas por la nubosidad y la estratificación deficiente del fluido al iniciar la operación del sistema por la mañana, limitan considerablemente el calentamiento del agua de una forma eficaz

Drive of a brushless direct current motor with hall type sensors

In the present article, an electronic bi-directional power converter applied to the control of a brushless direct current motor (Brushless) was designed, implemented and automatically activated, by means of which part of the electric bicycle is recovered. The kinetic energy is converted to electrical energy efficiently, with a positive ecological impact. The converters were implemented with isolated gate transistors (IGBT), these devices have high switching frequency, which allows significantly reduce the harmonics, which is very attractive in different applications therefore the results of this work can be generalized for the speed control of higher power direct current motors which can not be fed directly from the electrical system and require a variable speed, as is the case of electric vehicles.En el presente artículo se diseño, implemento y se caracterizo un convertidor electrónico de potencia bidireccional aplicado al control de un motor de corriente directa sin escobillas (Brushless), para el impulso de una bicicleta eléctrica de modo automático, mediante el cual se recupera parte de la energía cinética y se convierte a energía eléctrica de modo eficiente, con un impacto ecológico positivo. Los convertidores se implementaron con transistores de compuerta aislada (IGBT), estos dispositivos tienen alta frecuencia de conmutación, lo que permite reduce significativamente los armónicos, lo cual es muy atractivo en diferentes aplicaciones por lo tanto los resultados del presente trabajo se pueden generalizar para el control de velocidad de motores de corriente directa de mayor potencia los cuales no puedan ser alimentados directamente del sistema eléctrico y requieran de una velocidad variable, como es el caso de los vehículos eléctricos

Energy quality analysis of CH-bridge inverter and SPWM control

This document shows the results obtained by implementing a multicarrier SPWM level displacement control system to a singlephase seven level cascade H-bridge inverter. The tests consisted of using three multicarrier methods with different modulation rates in frequency and for every one different modulation rates in amplitude. Obtaining a set of results of the values of the harmonics present in them for each method. The control algorithm was programmed using SolidThinking Embed software and the digital signal processor TMDSCNCD28379D from Texas Instruments is used as an interface with the inverter. Experimental results show that energy quality varies using low frequency or amplitude modulation rates with respect to high frequency modulation rates and amplitude modulation rates close to unity. The results indicate that energy quality improves with increasing modulation rates in frequency or amplitude.En este documento se muestran los resultados obtenidos al implementar un sistema de control por desplazamiento de nivel SPWM multicarrier a un inversor monofásico de puentes H en cascada. Las pruebas consistieron en usar tres métodos multicarrier con diferentes índices de modulación en frecuencia y amplitud. Obteniéndose un conjunto de resultados de los valores de los armónicos presentes en las mismas para cada método. El algoritmo de control fue programado usando el software SolidThinking Embed y el procesador digital de señales TMDSCNCD28379D de Texas Instruments se utiliza como interface con el inversor. Los resultados experimentales muestran que la calidad de la energía varía usando índices de modulación en frecuencia o en amplitud bajos con respecto a índices de modulación en frecuencia altos y modulación en amplitud cercanos a la unidad. Los resultados indican que la calidad de la energía mejora al incrementar los índices de modulación en frecuencia o amplitud

Métricas de Registro de Imágenes y Predicción de Dolor de Rodilla por Osteoartritis Crónica: Datos de la Osteoarthritis Initiative

Osteoarthritis (OA) is the most common type of arthritis, is a growing disease in the industrialized world. OA is an incapacitate disease that affects more than 1 in 10 adults over 60 years old. X-ray medical imaging is a primary diagnose technique used on staging OA that the expert reads and quantify the stage of the disease. Some Computer-Aided Diagnosis (CADx) efforts to automate the OA detection have been made to aid the radiologist in the detection and control, nevertheless, the pain inherits to the disease progression is left behind. In this research, it’s proposed a CADx system that quantify the bilateral similarity of the patient’s knees to correlate the degree of asymmetry with the pain development. Firstly, the knee images were aligned using a B-spline image registration algorithm, then, a set of similarity measures were quantified, lastly, using this measures it’s proposed a multivariate model to predict the pain development up to 48 months. The methodology was validated on a cohort of 131 patients from the Osteoarthritis Initiative (OAI) database. Results suggest that mutual information can be associated with K&L OAI scores, and Multivariate models predicted knee chronic pain with: AUC 0.756, 0.704, 0.713 at baseline, one year, and two years’ follow-up.Osteoarthritis (OA) is the most common type of arthritis, is a growing disease in the industrialized world. OA is an incapacitate disease that affects more than 1 in 10 adults over 60 years old. X-ray medical imaging is a primary diagnose technique used on staging OA that the expert reads and quantify the stage of the disease. Some Computer-Aided Diagnosis (CADx) efforts to automate the OA detection have been made to aid the radiologist in the detection and control, nevertheless, the pain inherits to the disease progression is left behind. In this research, it’s proposed a CADx system that quantify the bilateral similarity of the patient’s knees to correlate the degree of asymmetry with the pain development. Firstly, the knee images were aligned using a B-spline image registration algorithm, then, a set of similarity measures were quantified, lastly, using this measures it’s proposed a multivariate model to predict the pain development up to 48 months. The methodology was validated on a cohort of 131 patients from the Osteoarthritis Initiative (OAI) database. Results suggest that mutual information can be associated with K&L OAI scores, and Multivariate models predicted knee chronic pain with: AUC 0.756, 0.704, 0.713 at baseline, one year, and two years’ follow-up

Front-End Design Guidelines for Infotainment Systems

This paper presents a set of front-end design guidelines intended to provide a starting point to designers of user interfaces for infotainment systems. The proposed approach suggests guidance on four dimensions inferred from state of the art such as crucial to achieve well designed automotive interfaces: a) Design; b) Interaction; c) Security; and d) Connectivity. Guidelines were thought by integrating conceptual-insights from Graphic Design; User Centered Design; Human-Machine Interfaces; Usability; and Human-Computer interaction. Additionally, were specified and structured to be used also as a comparing tool (Like Heuristic- Evaluation technique) to analyze front-end of existent infotainment systems. Said duality allowed to revise the pertinence of the proposal through a case study where 30 participants (25 regular users and 5 technicalexperts) compared suggested guidelines’ specification against interactions provided by the front–end of Mazda Connect© infotainment System. Obtained results suggested that setting of proposed guidelines was compatible with participants’ perceptions facilitating to identify pain-points on current design; thus, proposed guidance could scaffold base-insights for new front-end designs

Control platform of an unmanned aerial vehicle for the detection of weeds

In the present work, a remote control platform for the stabilization of a drone was developed through trajectory planning with the objective of detecting weeds in a bean field. The weed detection was carried out completely autonomously, using a decision tree as a classification algorithm in the final stage. The results obtained in the evaluation of the performance of the proposed method were satisfactory. The linear regression model between estimated and observed weed densities yielded a coefficient of determination of 0.987 and an average square error of 0.075. Of the total area of the field of study, 84% was estimated with less than 1% coverage of weeds, which indicates a high potential for reducing the volume of applied herbicides. Currently, we are working on automatic control algorithms that detect any anomaly in the flight of the Drones.En el presente trabajo se desarrolló una plataforma de control remota para la estabilización de un Dron mediante la planificación de trayectorias con el objetivo de la detección de malezas en un campo de frijol. La detección de malezas se llevó a cabo de manera completamente autónoma, empleando un árbol de decisión como algoritmo de clasificación en la etapa final. Los resultados obtenidos en la evaluación del desempeño del método propuesto fueron satisfactorios. El modelo de regresión lineal entre las densidades de maleza estimadas y observadas arrojó un coeficiente de determinación de 0.987 y un error cuadrático medio de 0.075. Del área total del campo de estudio, se estimó un 84 % con menos del 1 % de cobertura de malezas, lo cual indica un alto potencial para la reducción del volumen de herbicidas aplicados. Actualmente, estamos trabajando en algoritmos de control automáticos que detecten cualquier anomalía en el vuelo de los Drones

A generalized model for indoor location estimation using environmental sound from human activity recognition

The indoor location of individuals is a key contextual variable for commercial and assisted location-based services and applications. Commercial centers and medical buildings (eg, hospitals) require location information of their users/patients to offer the services that are needed at the correct moment. Several approaches have been proposed to tackle this problem. In this paper, we present the development of an indoor location system which relies on the human activity recognition approach, using sound as an information source to infer the indoor location based on the contextual information of the activity that is realized at the moment. In this work, we analyze the sound information to estimate the location using the contextual information of the activity. A feature extraction approach to the sound signal is performed to feed a random forest algorithm in order to generate a model to estimate the location of the user. We evaluate the quality of the resulting model in terms of sensitivity and specificity for each location, and we also perform out-of-bag error estimation. Our experiments were carried out in five representative residential homes. Each home had four individual indoor rooms. Eleven activities (brewing coffee, cooking, eggs, taking a shower, etc.) were performed to provide the contextual information. Experimental results show that developing an indoor location system (ILS) that uses contextual information from human activities (identified with data provided from the environmental sound) can achieve an estimation that is 95% correct

Study and comparison of objects detection algorithms using convolutional neural networks for plant diseases detection in leaves

Recently Machine Learning and computational vision have generated interest and have found new applications in engineering. In agriculture, "smart" systems have become important tools in the detection of anomalies that decrease the quality and quantity in the harvest of agricultural products. In this research, we developed a comparison of the main object detection algorithms using Convolutional Neural Networks (CNN) implemented in Deep Learning. The results were analyzed based on the accuracy and processing time obtained with the object detection algorithms R-CNN, Fast R-CNN, and Faster R-CNN. The CCN topologies of AlexNet, GoogleNet, ResNet50, ResNet101, SqueezeNet and InceptionV3 were implemented to generate Transfer Learning in image detectors and classifiers. The topologies were trained with the PlantVillage - Dataset which is made up of more than 40,000 leaf images of 9 plant species and 24 diseasesRecientemente el Machine Learning y la visión computacional han originado interés y han encontrado nuevas aplicaciones en la ingeniería. En la agricultura, sistemas “inteligentes” se han convertido en herramientas importantes para la detección de anomalías que decrecen la calidad y cantidad en la cosecha de productos agrícolas. En esta investigación desarrollamos una comparativa de los principales algoritmos de detección de objetos usando Redes Neuronales Convolucionales (RNC) implementadas en Deep Learning. Se analizaron los resultados en base a la superposición y tiempo de procesamiento obtenidos con los algoritmos de detección de objetos R-CNN, Fast R-CNN, y Faster R-CNN. Se implementaron las arquitecturas de RNC de AlexNet, GoogleNet, ResNet50, ResNet101, SqueezeNet e InceptionV3, para generar Transfer Learning en los detectores y clasificadores de imágenes. Las arquitecturas fueron entrenadas con PlantVillage - Dataset, conformado por más 40,000 imágenes de hojas de 9 especies de plantas y 24 enfermedades