Master’s student Yeongtak Oh, from the System Health and Risk Management Lab (Advisor: Prof. Byeng Dong Youn) of Seoul National University Dept. of Mechanical and Aerospace Engineering, received Best Poster Award at 2019 PHM Korea Conference for his paper titled “Leak Detection and Evaluation for Power Plant Boiler Tubes Using Acoustic Emission.”

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In the above paper, Mr. Oh applied the sliding window technique to transform multi-channel time series data from the sensors into 2-dimensional correlation matrix, and generated a correlation image of the matrix to use as input data for the CNN. This method analyzes big data acquired from sensors attached to large structures such as power plant boilers and performs real-time monitoring of the structural integrity.