Kyumin Na
Seoul National University
11 Papers
2 Citations
Kyumin Na is an academic researcher from Seoul National University. The author has contributed to research in topics: Computer science & Fault detection and isolation. The author has an hindex of 4, co-authored 11 publications.
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Papers
Phase-based time domain averaging (PTDA) for fault detection of a gearbox in an industrial robot using vibration signals
TL;DR: The proposed phase-based time domain averaging (PTDA) method can estimate deterministic signals that are more synchronized by considering the phase angle of the vibration signals and improve the performance of fault detection for gearboxes in industrial robots.
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A positive energy residual (PER) based planetary gear fault detection method under variable speed conditions
TL;DR: The proposed positive energy residual (PER) method is capable of detecting faults of a planetary gear under variable speed conditions, while showing better performance than the two other methods.
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A new auto-encoder-based dynamic threshold to reduce false alarm rate for anomaly detection of steam turbines
TL;DR: In this article, an ensemble denoising auto-encoder-based dynamic threshold (EDAE-DT) is proposed to overcome the false alarm issue in anomaly detection in thermal power plant datasets.
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A health-adaptive time-scale representation (HTSR) embedded convolutional neural network for gearbox fault diagnostics
TL;DR: Wang et al. as discussed by the authors proposed a health-adaptive time-scale representation (HTSR) embedded CNN, which is designed to exploit the concept of TSR, informed by the physics of the time and frequency characteristics induced by the faultrelated signals.
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Variance of energy residual (VER): An efficient method for planetary gear fault detection under variable-speed conditions
TL;DR: The proposed VER method does not need angular information, and offers the potential to reduce computation time by using short-time Fourier transform (STFT) instead of WT, and shows better fault sensitivity – with less computation time – than the previous method that uses WT.
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