Mutual information and meta-heuristic classifiers applied to bearing fault diagnosis in three-phase induction motors

Producción CientíficaThree-phase induction motors are extensively used in industrial processes due to their robustness, adaptability to different operating conditions, and low operation and maintenance costs. Induction motor fault diagnosis has received special attention from industry since it can reduce process losses and ensure the reliable operation of industrial systems. Therefore, this paper presents a study on the use of meta-heuristic tools in the diagnosis of bearing failures in induction motors. The extraction of the fault characteristics is performed based on mutual information measurements between the stator current signals in the time domain. Then, the Artificial Bee Colony algorithm is used to select the relevant mutual information values and optimize the pattern classifier input data. To evaluate the classification accuracy under various levels of failure severity, the performance of two different pattern classifiers was compared: The C4.5 decision tree and the multi-layer artificial perceptron neural networks. The experimental results confirm the effectiveness of the proposed approach.Consejo Nacional de Desarrollo Científico y Tecnológico - (processes 474290/2008-5, 473576/2011-2, 552269/2011-5, 201902/2015-0 and 405228/2016-3

Highly diverse and rapidly spreading: Melanagromyza sojae threatens the soybean belt of South America

The soybean stem fly, Melanagromyza sojae, an Asian native insect, has successfully established in Brazil, Argentina, Paraguay and Bolivia. These countries are among the lead global soybean producing nations, being collectively known as the soybean belt of South America. Infestation levels of M. sojae grow by the year, facilitated by the lack of efficient management strategies. Previous studies have revealed a high number of maternal lineages in M. sojae populations from Southern Brazil and Paraguay, but a comprehensive survey on genetic diversity combining samples from all countries within the South American soybean belt remains absent. We used the mitochondrial DNA cytochrome oxidase I partial gene (mtCOI) to characterize specimens of M. sojae collected in fourteen Brazilian sites and one Argentine site, and then combined our mtCOI data with previously published data from Australia, Bolivia, Paraguay, and other Brazilian sites, to investigate genetic diversity in this invasive agricultural pest species. Based on the molecular characterisation of the mtCOI gene, haplotypes Msoj-COI-01 and Msoj-COI-02 have the highest frequencies in the continent. The high genetic diversity found is evidence of introductions involving multiple female founders into the continent, and the high proportion of unique mtDNA haplotypes identified from Brazil, Paraguay and Bolivia (~ 50%) suggests potential novel introductions have taken place. The findings from our study will contribute to a better understanding of M. sojae genetic diversity in South America, supporting the development of management strategies for this highly invasive pest and assisting with biosecurity preparedness of other emerging Agromyzidae flies of economic importance.EEA ParanáFil: Pozebon, Henrique. Federal University of Santa Maria. Crop Protection Department; BrasilFil: Ugalde, Gustavo Andrade. Federal University of Santa Maria. Crop Protection Department; BrasilFil: Smagghe, Guy. Ghent University. Department of Plants and Crops; BélgicaFil: Tay, Wee Tek. CSIRO. Black Mountain Laboratories; AustraliaFil: Karut, Kamil. Çukurova University. Agricultural Faculty. Department of Plant Protection; TurquíaFil: Copa Bazán, Angel Fernando. Universidad Autonoma Gabriel René Moreno; BoliviaFil: Vitorio, Lucas. Syngenta Crop Protection S.A. Research and Development; BoliviaFil: Peralta, Roberto. Halcón Monitoreos; ArgentinaFil: Saluso, Adriana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Ramírez-Paredes, Mónica Lucía. Universidad Católica Nuestra Señora de La Asunción; ParaguayFil: Murúa, María Gabriela. Instituto de Tecnologia Agroindustrial del Noroeste Argentino; ArgentinaFil: Guedes, Jerson Vanderlei Carús. Federal University of Santa Maria. Crop Protection Department; BrasilFil: Arnemann, Jonas André. Federal University of Santa Maria. Crop Protection Department; Brasi