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Peregrina-Barreto H.,National Institute of Astrophysics, Optics and Electronics | Morales-Hernandez L.A.,Autonomous University of Queretaro | Rangel-Magdaleno J.J.,National Institute of Astrophysics, Optics and Electronics | Avina-Cervantes J.G.,University of Guanajuato | And 2 more authors.
Computational and Mathematical Methods in Medicine | Year: 2014

Thermography is a useful tool since it provides information that may help in the diagnostic of several diseases in a noninvasive and fast way. Particularly, thermography has been applied in the study of the diabetic foot. However, most of these studies report only qualitative information making it difficult to measure significant parameters such as temperature variations. These variations are important in the analysis of the diabetic foot since they could bring knowledge, for instance, regarding ulceration risks. The early detection of ulceration risks is considered an important research topic in the medicine field, as its objective is to avoid major complications that might lead to a limb amputation. The absence of symptoms in the early phase of the ulceration is conceived as the main disadvantage to provide an opportune diagnostic in subjects with neuropathy. Since the relation between temperature and ulceration risks is well established in the literature, a methodology that obtains quantitative temperature differences in the plantar area of the diabetic foot to detect ulceration risks is proposed in this work. Such methodology is based on the angiosome concept and image processing. © 2014 H. Peregrina-Barreto et al.

De Jesus Rangel-Magdaleno J.,National Institute of Astrophysics, Optics and Electronics | Peregrina-Barreto H.,Laboratorio Of Investigacion En Control Reconfigurable Ac | Ramirez-Cortes J.M.,National Institute of Astrophysics, Optics and Electronics | Gomez-Gil P.,National Institute of Astrophysics, Optics and Electronics | Morales-Caporal R.,Apizaco Institute of Technology
IEEE Transactions on Instrumentation and Measurement | Year: 2014

Broken bars detection on induction motors has been a topic of interest in recent years. Its detection is important due to the fact that the failure is silent and the consequences it produces as power consumption increasing, vibration, introduction of spurious frequencies in the electric line, among others, can be catastrophic. In this paper, the use of motor current signature analysis and mathematical morphology to detect broken bars on induction motors under different mechanical load condition is analyzed. The proposed algorithm first identifies the motor load and then the motor condition. The statistical analysis of several tests under different motor loads (100%, 75%, 50%, and 25%) and motor condition (healthy, one broken bar, and two broken bars) is presented. The proposed method has been implemented in a field programmable gate array, to be used in real-time online applications. The algorithm obtained in average a 95% accuracy of failure detection. © 1963-2012 IEEE.

Bonilla Huerta E.,Apizaco Institute of Technology | Duval B.,University of Angers | Hao J.-K.,University of Angers
Neurocomputing | Year: 2010

In supervised classification of Microarray data, gene selection aims at identifying a (small) subset of informative genes from the initial data in order to obtain high predictive accuracy. This paper introduces a new embedded approach to this difficult task where a genetic algorithm (GA) is combined with Fisher's linear discriminant analysis (LDA). This LDA-based GA algorithm has the major characteristic that the GA uses not only a LDA classifier in its fitness function, but also LDA's discriminant coefficients in its dedicated crossover and mutation operators. Computational experiments on seven public datasets show that under an unbiased experimental protocol, the proposed algorithm is able to reach high prediction accuracies with a small number of selected genes. © 2010 Elsevier B.V.

Valles-Novo R.,National Institute of Astrophysics, Optics and Electronics | Rangel-Magdaleno J.,National Institute of Astrophysics, Optics and Electronics | Ramirez-Cortes J.,National Institute of Astrophysics, Optics and Electronics | Peregrina-Barreto H.,National Institute of Astrophysics, Optics and Electronics | Morales-Caporal R.,Apizaco Institute of Technology
Conference Record - IEEE Instrumentation and Measurement Technology Conference | Year: 2014

Induction motors are an ubiquitous machine. In industrial settings, online monitoring of motors' health status in order to schedule maintenance operations with the goal of damage prevention has become an essential necessity. Broken rotor bar is one of the most common failures in the rotor of a squirrel cage motor. Motor current signature analysis (MCSA) has become a popular method for its detection due to its high reliability. Recent works perform MCSA with a combination of different signal processing techniques to identify the presence of broken bars. In this work, MCSA is done with Empirical Mode Decomposition (EMD) from which a set of Intrinsic Mode Functions (IMF) is obtained. The extracted features of the arithmetical sum of the obtained IMFs form the basis of the proposed classification criteria. Unlike other works, the only employed signal processing technique in our methodology is EMD. Experimental results using our method show high accuracy in the detection of one broken rotor bar. © 2014 IEEE.

Szwedowicz D.,CENIDET | Bedolla J.,Apizaco Institute of Technology
DYNA (Colombia) | Year: 2012

Stress concentrations at the ends of a flat contact including frictional sliding are analyzed in this article by using the finite element (FE) method. The numerical studies are conducted with a shaft coupled to the hub by conical rings. The applied mesh refinement at the contact ends assures the reliability of the FE results, which show significantly higher stress peaks than those obtained from the conventional analytical solution recommended in the design guidelines of the frictional conical joints. These notch stresses result in low cycle fatigue (LCF) failures of the shaft-hub connection in service, since the yield point of the shaft material can be locally exceeded. The effect of clearances among the joint components and magnitudes of the friction coefficient on variations of the maximum stress in the contact are considered as well. The paper's findings and conclusions are applicable to the design and manufacturing process of the frictional conical joints with regard to assembly tolerances.

Bonilla-Huerta E.,Apizaco Institute of Technology | Hernandez-Montiel A.,Apizaco Institute of Technology | Morales-Caporal R.,Apizaco Institute of Technology | Arjona-Lopez M.,Technological Institute of La Laguna
IEEE/ACM Transactions on Computational Biology and Bioinformatics | Year: 2016

A hybrid framework composed of two stages for gene selection and classification of DNA microarray data is proposed. At the first stage, five traditional statistical methods are combined for preliminary gene selection (Multiple Fusion Filter). Then, different relevant gene subsets are selected by using an embedded Genetic Algorithm (GA), Tabu Search (TS), and Support Vector Machine (SVM). A gene subset, consisting of the most relevant genes, is obtained from this process, by analyzing the frequency of each gene in the different gene subsets. Finally, the most frequent genes are evaluated by the embedded approach to obtain a final relevant small gene subset with high performance. The proposed method is tested in four DNA microarray datasets. From simulation study, it is observed that the proposed approach works better than other methods reported in the literature. © 2016 IEEE.

Cisneros-Gonzalez M.,Technological Institute of the Valle del Guadiana | Hernandez C.,Technological Institute of La Laguna | Morales-Caporal R.,Apizaco Institute of Technology | Bonilla-Huerta E.,Apizaco Institute of Technology | Arjona M.A.,Technological Institute of La Laguna
IEEE Transactions on Energy Conversion | Year: 2013

This paper presents the application of the time-domain chirp signal excitation to obtain the dq axis parameters of a synchronous machine model. The latest advances on computation tools have allowed the research of existing and novel experimental procedures for the parameter estimation of synchronous-generator models. Hence, different experimental methodologies to reduce the amount of testing time and to obtain more accurate model parameters have been proposed. The chirp is a linear swept-frequency sinusoidal signal that allows exciting the generator over a specified frequency bandwidth. This excitation is applied to the dq axis positions while the generator is at standstill. The estimation of the fundamental parameters is made by using a hybrid optimization algorithm composed by a genetic and a quasi-Newton algorithm. The proposed test has the advantage of requiring a low testing time. The set of estimated parameters was validated using test data of a sudden three-phase short-circuit fault. A 7 kVA, 220 V, 60 Hz, 1800 r/min, four salient-pole synchronous machine was used to evaluate the proposed estimation approach. © 1986-2012 IEEE.

Bonilla Huerta E.,Apizaco Institute of Technology | Hernandez Hernandez J.C.,Apizaco Institute of Technology | Hernandez Montiel L.A.,Apizaco Institute of Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

This paper introduces a new combined filter-wrapper gene subset selection approach where a Genetic Algorithm (GA) is combined with Linear Discriminant Analysis (LDA). This LDA-based GA algorithm has the major characteristic that the GA uses not only a LDA classifier in its fitness function, but also LDA's discriminant coefficients in its dedicated crossover and mutation operators. This paper studies the effect of these informed operators on the evolutionary process. The proposed algorithm is assessed on a several well-known datasets from the literature and compared with recent state of art algorithms. The results obtained show that our filter-wrapper approach obtains globally high classification accuracies with very small number of genes to those obtained by other methods. © 2010 Springer-Verlag Berlin Heidelberg.

Rafael O.,Apizaco Institute of Technology | Saul O.J.,Apizaco Institute of Technology | Roberto M.,Apizaco Institute of Technology
International Power Electronics Congress - CIEP | Year: 2016

This paper presents simulation of a fuzzy control to carried out temperature tracked into an induction furnace implemented with a transistorized inverter. Basically, in this work is shown the fuzzy rules to assure a homogeneous heating in the aluminum bar localized inside to induction coil to arrive to an average temperature of 450° Celsius degrees. This heating method will be used in the extrusion process of aluminum. © 2016 IEEE.

Morales-Caporal R.,Apizaco Institute of Technology | Sandre-Hernandez O.,Apizaco Institute of Technology | Bonilla-Huerta E.,Apizaco Institute of Technology | Crispin Hernandez-Hernandez J.,Apizaco Institute of Technology | Juan Hernandez-Mora J.,Apizaco Institute of Technology
Proceedings - 2012 9th Electronics, Robotics and Automotive Mechanics Conference, CERMA 2012 | Year: 2012

Voltage Source Inverters (VSI) fed variable speed alternating current (AC) drives are widely used in many industrial applications. In order to obtain variable voltage and frequency the VSI is commonly firing by using Pulse Width Modulation (PWM) techniques such as the Space Vector Modulation (SVM), which provides a suitable strategy to control the VSI. This paper presents the digital implementation of a modulation algorithm for a three phase VSI-fed a Permanent Magnet Synchronous Machine (PMSM). The SVM algorithm is first performed by simulation based on the software Matlab/Simulink®, and then it is digital implemented by using a floating TMS320F28335 Digital Signal Processor (DSP). Simulated and experimental results are presented to demonstrate the effectiveness of the adjustable frequency electrical drive. © 2012 IEEE.

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