Operation-Adaptive Damage Assessment of Steam Turbines Using a Nonlinear Creep-Fatigue Interaction Model. - Woosung Choi; Heonjun Yoon; Byeng Dong Youn (IEEE Access, 2020)

A new calibration metric that considers statistical correlation: Marginal Probability and Correlation Residuals. - Wongon Kim; Heonjun Yoon; Guesuk Lee; Taejin Kim; Byeng D. Youn (Reliab. Eng. Syst. Saf., 2020)

Design principle for effective mechanical boundary using a resonance band gap under elastic waves. - Yong Chang Shin; Soo-Ho Jo; Heonjun Yoon; Byeng D. Youn (J. Comput. Des. Eng., 2022)

A health image for deep learning-based fault diagnosis of a permanent magnet synchronous motor under variable operating conditions: Instantaneous current residual map. - Chan Hee Park; Hyeongmin Kim; Chaehyun Suh; Minseok Chae; Heonjun Yoon; Byeng D. Youn (Reliab. Eng. Syst. Saf., 2022)

PERL: Probabilistic energy-ratio-based localization for boiler tube leaks using descriptors of acoustic emission signals. - Kyumin Na; Heonjun Yoon; Jaedong Kim; Sungjong Kim; Byeng D. Youn (Reliab. Eng. Syst. Saf., 2023)

MPARN: multi-scale path attention residual network for fault diagnosis of rotating machines. - Hyeongmin Kim; Chan Hee Park; Chaehyun Suh; Minseok Chae; Heonjun Yoon; Byeng D. Youn (J. Comput. Des. Eng., 2023)

Probabilistic framework for reliable optimal design of gearboxes in general-purpose industrial robots considering random use conditions. - Jin-gyun Park; Heonjun Yoon; Byeng D. Youn (J. Comput. Des. Eng., 2023)

Opt-TCAE: Optimal temporal convolutional auto-encoder for boiler tube leakage detection in a thermal power plant using multi-sensor data. - Hyeongmin Kim; Jin Uk Ko; Kyumin Na; Hyeonchan Lee; Hee-soo Kim; Jong-Duk Son; Heonjun Yoon; Byeng D. Youn (Expert Syst. Appl., 2023)

Revolution and peak discrepancy-based domain alignment method for bearing fault diagnosis under very low-speed conditions. - Seungyun Lee; Sungjong Kim; Su J. Kim; Jiwon Lee; Heonjun Yoon; Byeng D. Youn (Expert Syst. Appl., 2024)

PCDC: prototype-assisted dual-contrastive learning with depthwise separable convolutional neural network for few-shot fault diagnosis of permanent magnet synchronous motors under new operating conditions. - Minseok Chae; Hyeongmin Kim; Hye Jun Oh; Chan Hee Park; Chaehyun Suh; Heonjun Yoon; Byeng D. Youn (J. Comput. Des. Eng., 2024)

Self-supervised feature learning for motor fault diagnosis under various torque conditions. - Sang Kyung Lee; Hyeongmin Kim; Minseok Chae; Hye Jun Oh; Heonjun Yoon; Byeng D. Youn (Knowl. Based Syst., 2024)

FASER: Fault-affected signal energy ratio for fault diagnosis of gearboxes under repetitive operating conditions. - Kyumin Na; Yunhan Kim; Heonjun Yoon; Byeng D. Youn (Expert Syst. Appl., 2024)

FL-SSDAN: Fleet-level semi-supervised domain adaptation network for fault diagnosis of overhead hoist transports. - Chaehyun Suh; Hyeongmin Kim; Chan Hee Park; Minseok Chae; Joung Taek Yoon; Ilkyu Lee; Heonjun Yoon; Byeng D. Youn (J. Comput. Des. Eng., 2025)