首页|Data on Machine Learning Described by a Researcher at Daejeon University (ML- an d LSTM-Based Radiator Predictive Maintenance for Energy Saving in Compressed Air Systems)
Data on Machine Learning Described by a Researcher at Daejeon University (ML- an d LSTM-Based Radiator Predictive Maintenance for Energy Saving in Compressed Air Systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on artificial intelligen ce have been presented. According to news reporting from Daejeon, South Korea, b y NewsRx journalists, research stated, "Air compressors are widely used in indus trial fields." Financial supporters for this research include Korea Institute of Energy Technol ogy Evaluation And Planning; Ministry of Trade, Industry & Energy (Motie) of The Republic of Korea. Our news journalists obtained a quote from the research from Daejeon University: "Compressed air systems aggregate air flows and then supply them to places of d emand. These huge systems consume a significant amount of energy and generate he at internally. Machine components in compressed air systems are vulnerable to he at, and, in particular, a radiator to cool the heat of the overall air compresso r is the core component. Dirty radiators increase energy consumption due to anom alous cooling. To reduce the energy consumption of air compressors, this mechani sm emphasizes a machine learning-based radiator fault detection, using features such as RPM, motor power, outlet pressure, air flow, water pump power, and outle t temperature with slight true fault labels."
Daejeon UniversityDaejeonSouth KoreaAsiaCyborgsEmerging TechnologiesMachine Learning
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