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ABSTRACT:The typical electrical engineering (EE) undergraduate curriculum is packed with foundational materials and offers limited room for other desirable materials that could be readily applied in the power industry. A Motor Current Signature Analysis (MCSA) tool is developed for effectively teaching the concepts of induction motor fault detection within one lecture or laboratory period. ß

A survey study was conducted to analyze the reproductive and productive performances of four indigenous chicken breeds under different rearing system. Six villages located in Eastern Cape, South Africa were used for the study from July 2017 to June 2018. Data on clutch per year (CPY), hatchability (HATCH), egg per clutch (EGC), survivability at 10-12 weeks (SURV), egg per year (EPY), recovery period (RP), average age at production (AA), duration of rearing (DR), mortality, egg laying length (EGL), natural brooding period (NBP) and natural incubating period (NIP) were obtained from Seven thousand, five hundred and thirty eight (7538) indigenous chicken. Potchefstroom Kooekok is observed to be a good egg producing breed with 15.11±0.25eggs per clutch. Venda breed possess good mothering ability (hatchability) and high survivability with 86.03±0.31days and 82.70±0.26 days respectively. Naked Neck is known to be more prone to diseases with least (survivability) 60.08±0.25days. Village was positively correlated with EGC and HATCH, EGY and SURV at p≤0.01 and p≤0.05 respectively. Rearing system was positively correlated with EGC. Rearing system was positively correlated at p≤0.05 on EGC than CPY, HATCH, EGY and SURV. Breed and village interactions were significant at p≤0.05 on RP, AA, DR, EGL, NBP and NIP. Therefore, productive and reproductive traits of indigenous chicken differ across different rearing systems, breeds and villages.

Este trabajo presenta un nuevo algoritmo basado en wavelets para la detección de fallas en máquinas de inducción de tres fases. Este nuevo método utiliza la desviación estándar de los coeficientes wavelet, que se obtiene de la descomposición de n-niveles de cada fase, para identificar fallas en el voltaje en una fase o fallas en la resistencia del estator en máquinas de inducción. El algoritmo propuesto puede funcionar independiente de la frecuencia de operación, tipo de falla y condiciones de carga. Los resultados muestran que este algoritmo tiene una mejor respuesta de detección que las técnicas basadas en la transformada de Fourier. Palabras clave: Wavelets, detección de fallas, máquinas de inducción, transformada rápida de Fourier, detección temprana.

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