Observer-biased bearing condition monitoring: from fault detection to multi-fault classification

Bearings are simultaneously a fundamental component and one of the principal causes of failure in rotary machinery. The work focuses on the employment of fuzzy clustering for bearing condition monitoring, i.e., fault detection and classification. The output of a clustering algorithm is a data partition (a set of clusters) which is merely a hypothesis on the structure of the data. This hypothesis requires validation by domain experts. In general, clustering algorithms allow a limited usage of domain knowledge on the cluster formation process. In this study, a novel method allowing for interactive clustering in bearing fault diagnosis is proposed. The method resorts to shrinkage to generalize an otherwise unbiased clustering algorithm into a biased one. In this way, the method provides a natural and intuitive way to control the cluster formation process, allowing for the employment of domain knowledge to guiding it. The domain expert can select a desirable level of granularity ranging from fault detection to classification of a variable number of faults and can select a specific region of the feature space for detailed analysis. Moreover, experimental results under realistic conditions show that the adopted algorithm outperforms the corresponding unbiased algorithm (fuzzy c-means) which is being widely used in this type of problems. (C) 2016 Elsevier Ltd. All rights reserved.Grant number: 145602

Gearbox Fault Identification and Classification with Convolutional Neural Networks

Vibration signals of gearbox are sensitive to the existence of the fault. Based on vibration signals, this paper presents an implementation of deep learning algorithm convolutional neural network (CNN) used for fault identification and classification in gearboxes. Different combinations of condition patterns based on some basic fault conditions are considered. 20 test cases with different combinations of condition patterns are used, where each test case includes 12 combinations of different basic condition patterns. Vibration signals are preprocessed using statistical measures from the time domain signal such as standard deviation, skewness, and kurtosis. In the frequency domain, the spectrum obtained with FFT is divided into multiple bands, and the root mean square (RMS) value is calculated for each one so the energy maintains its shape at the spectrum peaks. The achieved accuracy indicates that the proposed approach is highly reliable and applicable in fault diagnosis of industrial reciprocating machinery. Comparing with peer algorithms, the present method exhibits the best performance in the gearbox fault diagnosis

Representaciones sociales en la prensa radial de Latacunga en torno al fútbol femenino

The objet of this research is to transmit a radio segement, dealing with women´s soccer, practicing with the main gool like letting society know about this sport practiced by women, because of this, we have quoted many authors, who affirm in their writings that women can develop and thive in the various disciplines they choose to do. Many research methods were used, such a the inductive, deductive, methods as research tools. Like interviews and surveys, allowing us to carry out an investigation with statistics that will support the research, this way the percentage of people that agree with the proposal will be known, as well as letting us make an analisis of each of the questions that survey contains, and therefore the respective interpretation….La presente investigación tiene como objetivo emitir un segmento radial, entorno al fútbol femenino con la finalidad que la sociedad conozca acerca de este deporte, por esta razón hemos citado varios autores que aportan a la indagación para desarrollar la propuesta en la emisora. Se utilizaron varios métodos de investigación como el inductivo, deductivo herramientas, entre las cuales tenemos entrevistas, encuestas, permitiendo realizar una investigación con datos estadísticos que sustentaran la presente investigación, de este modo se podrá conocer el porcentaje de personas que concuerden con la presente propuesta, por otro lado también se podrá realizar un análisis de cada pregunta que contiene la encesta y por ende s respectiva interpretación…

Análisis de los factores a tomar en cuenta para el estudio de la competitividad de los productos agrí­colas

El objetivo de esta investigación fue  realizar un estudio de tipo bibliográfico que permitiera detectar los vací­os existentes en la literatura especializada, en relación con el análisis de los factores que deben tomarse en cuenta para poder estudiar la competitividad de los productos agrí­colas. Se pudo analizar que la determinación de los factores que inciden en competitividad de los productos agroindustriales es un problema complejo en que no resulta tan simple determinar estos y en ocasiones la gestión productiva de los productos agrí­colas puede estar determinada por factores que pueden considerarse empí­ricos relacionados con la cultura local y que se enmarcan dentro de la lógica agroindustrial intensiva. Se  pudieron determinar cómo lí­neas investigativas de importancia: el estudio de modelos de predicción de ventas para un producto agrí­cola dado, el análisis de la relación entre el manejo social y el desarrollo rural agrario, el estudio de  la competitividad de redes de valor agroindustrial y estudios para el manejo productivo de un sistema agroindustrial y de los factores relacionados con esta problemática. Se reveló igualmente que no existen muchos estudios en relación con los productos agrí­colas que pueden considerarse no tradicionales  El análisis de la literatura reflejó  igualmente que las empresas agroindustriales presentan caracterí­sticas propias y diferenciadoras en relación con otro tipo de empresas por lo que se requiere su estudio de forma especí­fica. En el caso particular de Ecuador no existen estudios que precisen los posibles factores que pueden incidir en la competitividad de los productos agrí­colas, situación que se presenta igualmente en otros paí­ses de América Latina.

STUDY OF THE VARROASIS INFESTATION RATE IN THE CENTRAL AREA OF ECUADOR

Objective: To study the Varroasis Infestation rate in the central area of Ecuador. Methods: The experimental phase was developed in four apiaries distributed in the provinces: Bolivar, Tungurahua, Chimborazo and Los Rios (12 hives), the experimentation lasted 65 d. A DCA design was applied. Three different systems were used for the identification of varroa: soapy water (SW), honeycomb cut (HC) and the cardboard with semi-solid petrolatum (CSP). Results: With the SW method, it was obtained that Chimborazo has 23.14%; followed by Tungurahua (7.99%); Los Rios (3.24%) and finally Bolivar with (0.51%); with the HC method, it was determined that Chimborazo has the highest incidence with 9.13%; followed by Bolivar and finally Los Rios; with the CSP method, the province of Chimborazo presents the highest infestation (26250 individuals); followed by Bolivar, Tungurahua, and Los Rios. Regarding the production of eggs for each frame, 3 frames taken from the brood chamber were used in each of the apiaries under study; Chimborazo being where there is less quantity of eggs for each frame, followed by Bolivar, Tungurahua and finally Los Ríos. Conclusion: The higher the geographical height, the greater the Varroa infestation

Vibration-based gearbox fault diagnosis using deep neural networks

Vibration-based analysis is the most commonly used technique to monitor the condition of gearboxes. Accurate classification of these vibration signals collected from gearbox is helpful for the gearbox fault diagnosis. In recent years, deep neural networks are becoming a promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data. In this paper, a study of deep neural networks for fault diagnosis in gearbox is presented. Four classic deep neural networks (Auto-encoders, Restricted Boltzmann Machines, Deep Boltzmann Machines and Deep Belief Networks) are employed as the classifier to classify and identify the fault conditions of gearbox. To sufficiently validate the deep neural networks diagnosis system is highly effective and reliable, herein three types of data sets based on the health condition of two rotating mechanical systems are prepared and tested. Each signal obtained includes the information of several basic gear or bearing faults. Totally 62 data sets are used to test and train the proposed gearbox diagnosis systems. Corresponding to each vibration signal, 256 features from both time and frequency domain are selected as input parameters for deep neural networks. The accuracy achieved indicates that the presented deep neural networks are highly reliable and effective in fault diagnosis of gearbox

Asociatividad y desarrollo económico de las PYMES del sector turístico en Ecuador

Debido a la creciente competencia tanto nacional como internacional, las pequeñas y medianas empresas procuran adaptar nuevas ideas de negocios que le permitan acceder a nuevos y diferentes mercados en la búsqueda de mayores niveles de eficiencia y rendimientos para su expansión, como en el caso de este tipo de empresas en el cantón La Troncal de Ecuador. En este sentido, se pretende analizar la relación entre asociatividad empresarial entre pequeñas y medianas empresas del sector turístico y el desarrollo económico del cantón La Troncal. Desde el punto de vista metodológico, en este estudio se recurre a una muestra compuesta por quince empresas del sector. Para la obtención de la información, se usó una encuesta y como instrumento un cuestionario compuesto por 14 items de escala tipo Likert, donde los resultados fueron analizados por medio de la estadística descriptiva. Como resultado se pudo conocer que existe una relación entre la asociatividad y el desarrollo económico, al contar con organizaciones agrupadas, con objetivos comunes que persiguen su crecimiento y aportan al desarrollo económico de la región. Solo es necesario programas de capacitación formativa y administrativa

Determinación de residuos de tetraciclinas en muestras de carne bovina destinadas al consumo humano

Determination of tetracycline residues in samples of bovine beef used for Human Consumption Resumen La presencia de residuos de antibióticos encontrados en la carne bovina destinada al consumo humano ha incrementado considerablemente en los últimos años, constituyendo un grave problema en salud pública. Para evaluar la presencia de residuos de tetraciclinas se estudió 74 muestras de carne bovina del Camal de Santa Rosa (El Oro), y se aplicó una prueba rápida de detección de tetraciclina (Smarkit). En el análisis se encontraron 24 casos positivos a la presencia de tetraciclinas en la carne representando el 32.4 % del total, y 50 casos negativos a la prueba representando el 67.6%. De los 24 casos positivos a la prueba, el 33.34% correspondían a animales cuya edad estaba entre 3 a 4 años existiendo una diferencia estadística significativa (p< 0.05). Estos hallazgos confirman el incumplimiento de los tiempos de retiro en la práctica pecuaria en nuestro país. Palabras clave: antibiótico; antimicrobiano; ganado bovino; músculo; smarkit. Abstract The presence of antibiotic residues found in beef intended for human consumption has increased considerably in recent years, constituting a serious problem in public health. To evaluate the presence of tetracycline residues, 74 samples of beef from Camal de Santa Rosa (El Oro) were studied, and a rapid tetracycline detection test (Smarkit) was applied. In the analysis we found 24 cases positive to the presence of tetracyclines in the meat representing 32.4% of the total, and 50 negative cases to the test representing 67.6%. Of the 24 positive test cases, 33.34% were animals aged 3 to 4 years, with a statistically significant difference (p <0.05). These findings confirm the non-fulfillment of the withdrawal times in the livestock practice in our country. Keywords: antibiotic; antimicrobial; cattle; muscle; smarkit

ECMO for COVID-19 patients in Europe and Israel

Since March 15th, 2020, 177 centres from Europe and Israel have joined the study, routinely reporting on the ECMO support they provide to COVID-19 patients. The mean annual number of cases treated with ECMO in the participating centres before the pandemic (2019) was 55. The number of COVID-19 patients has increased rapidly each week reaching 1531 treated patients as of September 14th. The greatest number of cases has been reported from France (n = 385), UK (n = 193), Germany (n = 176), Spain (n = 166), and Italy (n = 136) .The mean age of treated patients was 52.6 years (range 16–80), 79% were male. The ECMO configuration used was VV in 91% of cases, VA in 5% and other in 4%. The mean PaO2 before ECMO implantation was 65 mmHg. The mean duration of ECMO support thus far has been 18 days and the mean ICU length of stay of these patients was 33 days. As of the 14th September, overall 841 patients have been weaned from ECMO support, 601 died during ECMO support, 71 died after withdrawal of ECMO, 79 are still receiving ECMO support and for 10 patients status n.a. . Our preliminary data suggest that patients placed on ECMO with severe refractory respiratory or cardiac failure secondary to COVID-19 have a reasonable (55%) chance of survival. Further extensive data analysis is expected to provide invaluable information on the demographics, severity of illness, indications and different ECMO management strategies in these patients