PhD student Kyumin Na, 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 Presentation Award at 2019 PHM Korea Conference for his paper titled “Optimal Frequency Selection Method for Fault Detection of Industrial Robots.”

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In the above paper, Mr. Na calculated the uncertainty of the signal, taking into account the signal truncation of rotary machines, and did a conversion of time frequency representation according to the uncertainty. He was able to increase the fault distinguishability in signal energy based features for fault detection, by using the filtering weight which extracts energy from statistically meaningful parts in the time-frequency area of fault vibration signal. The suggested method can be helpful in designing filtering systems for fault detection in industrial fields in which rotary machines are used.