Navegando por Autor "NOGUEIRA, Rildo de Mendonça"

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Análise dos Impactos Harmônicos em uma Indústria de Manufatura de Eletroeletrônicos Utilizando Árvores de Decisão
(Universidade Federal do Pará, 2015) NOGUEIRA, Rildo de Mendonça; TOSTES, Maria Emília de Lima
Power Quality (PQ) is constantly the subject of studies, especially in the industrial sector, where large loads of electrical systems are concentrated. With the evolution of industrial processes and the introduction of new technologies, electronic equipment that generates disturbances in the systems has been added, affecting the quality of electricity. This work analyzes the harmonic impacts in an electronics manufacturing industry in the Manaus Industrial Pole (PIM), using data mining techniques and decision trees to monitor and diagnose coupling points and processes that present significant harmonic content. The objective is to identify and quantify the levels of harmonic distortions, avoiding regulatory penalties and improving the quality of electrical energy.
Harmonic Impact analysis coming from the manufacturing processes of a Eletroeletrônica Industry Using KDD and Decision Trees
(INSTITUTO DE TECNOLOGIA, 2015) NOGUEIRA, Rildo de Mendonça; OLIVEIRA, Edson Farias de; SILVA, Waterloo Ferreira da; SANTANA, Ádamo L.; TOSTES, Maria Emília de Lima; SOARES, Thiago Mota; Profa. Dra. Maria Adrina Paixão de Souza da Silva.
The study analyzes the impact of harmonic distortions generated by non-linear loads (computers, notebooks, and tablets) on the electrical grid of an electronics industry in Manaus. Using the KDD (Knowledge Discovery in Databases) methodology and decision trees, data were collected over a week at different points in the production process. The results identified that the 5th and 7th order harmonics, originating from the tablet production line, contributed the most to the total harmonic distortion of voltage (THDv) at the common coupling point (PCC). The decision tree technique proved effective in classifying and prioritizing distortion sources, aiding in decision-making for impact mitigation.
Naive Bayes aplicados en el análisis de impactos armónicos en los sistemas eléctricos industriales
(INSTITUTO DE TECNOLOGIA, 2015) SILVA, Waterloo Ferreira da; NOGUEIRA, Rildo de Mendonça; OLIVEIRA, Edson Farias de; SANTANA, Ádamo L.; TOSTES, Maria Emília de Lima; SOARES, Thiago Mota; Prof Dr. Walter Barra Junior
This paper presents an analysis of harmonic current impacts in an industrial facility in the Manaus Industrial Zone using Naive Bayes classification, a data mining technique. The study measures total harmonic distortion (THDv) and identifies which production processes contribute most to power quality issues, particularly due to non-linear loads like switch-mode power supplies. The methodology includes power quality measurements and statistical analysis with dedicated software.
Naive Bayes applied impacts harmonic analysis in industrial electrical systems
(INSTITUTO DE TECNOLOGIA, 2015) SILVA, Waterloo Ferreira da; NOGUEIRA, Rildo de Mendonça; CASTRO, Anderson; SANTANA, Ádamo L.; TOSTES, Maria Emília de Lima; Profa. Dra. Maria Adrina Paixão de Souza da Silva.
This paper applies the Naive Bayes data mining technique to analyze the impact of current harmonic distortion in an industrial facility located in the Manaus Industrial Pole. During a week-long measurement campaign, data were collected from circuits such as compressors, air conditioning systems, and tablet and notebook testing lines. Using tools like Weka and Genie, the analysis identified correlations between specific harmonic orders and increases in total harmonic distortion of voltage (THDv), with the 7th-order harmonic having the highest impact.
Planning Passive Filters using NSGA II for Industry Applications
(INSTITUTO DE TECNOLOGIA, 2014) LEITE, Jandecy Cabral; SILVA, Waterloo Ferreira da; CASTRO, Anderson de Oliveira; NOGUEIRA, Rildo de Mendonça; AZEVEDO, Manoel Socorro Santos; Prof. Dra. ADRIANA RIBEIRO CARNEIRO FOLADOR
This paper presents a multi-objective optimization approach for planning passive harmonic filters in industrial systems using the NSGA-II genetic algorithm. The method maximizes reactive power compensation benefits, minimizes harmonic distortion in the PCC current and bus voltages, and complies with power quality standards. The algorithm determines the filters' location, configuration, and parameters, demonstrating effectiveness in a practical example.