首页|New Machine Learning Data Have Been Reported by Researchers at University of Belgrade (Machine Learning for Power Transformer Sfra Based Fault Detection)
New Machine Learning Data Have Been Reported by Researchers at University of Belgrade (Machine Learning for Power Transformer Sfra Based Fault Detection)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Machine Learning. According to news reporting originating from Belgrade, Serbia, by NewsRx correspondents, research stated, "This paper presents machine learning methods for health assessment of power transformer based on sweep frequency response analysis. The paper presents an overview of monitoring and diagnostics based on statistical Sweep Frequency Response Analysis (SFRA) based indicators that are used to evaluate the state of the power transformer." Financial support for this research came from Ministry of Education, Science & Technological Development, Serbia. Our news editors obtained a quote from the research from the University of Belgrade, "Experimental data obtained from power transformers with internal short-circuit faults is used as a database for applying machine learning. Machine learning is implemented to achieve more precise asset management and condition-based maintenance. Unsupervised machine learning was applied through the k-means cluster method for classifying and dividing the examined power transformer state into groups with similar state and probability of failure. Artificial neural network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) as part of supervised machine learning are created in order to detect fault severity in tested power transformers of different lifetime."
BelgradeSerbiaEuropeCyborgsEmerging TechnologiesMachine LearningUniversity of Belgrade
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