首页|New Findings in Machine Learning Described from University of Edinburgh (Use of digital image correlation and machine learning for the optimal strain placement in a full-scale composite tidal turbine blade)
New Findings in Machine Learning Described from University of Edinburgh (Use of digital image correlation and machine learning for the optimal strain placement in a full-scale composite tidal turbine blade)
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New research on artificial intelligence is the subject of a new report. According to news originating from the University of Edinburgh by NewsRx editors, the research stated, "One of the challenges testing and health monitoring of large structures represents is getting as much information as possible from a specimen with a limited number of sensors." The news reporters obtained a quote from the research from University of Edinburgh: "In this work, a data-driven approach was pursued to decide the optimal location of single-point strain gauges using machine learning algorithms (MLA) and information from Digital Image Correlation (DIC) measurements. The optimal strain gauge placement was computed for a range of sensor numbers and the presence of sensors in the high-gradient regions was identified."
University of EdinburghCyborgsEmerging TechnologiesMachine Learning
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