From the 2 of 4 linked papers with an AI index.
4 papers
Gradient-enhanced spline dimensional decomposition for uncertainty quantification with limited training samples
Eunho Heo, Dongjin Lee
The paper introduces a gradient-enhanced spline dimensional decomposition (GE‑SDD) surrogate that incorporates both function values and partial derivatives to improve uncertainty q…
Fine-Grained Open-Set Fault Diagnosis via Metric-Guided Time-Frequency Configuration Selection and Class-Specific Autoencoders
Youngjae Jeon, Dongjin Lee
The paper introduces a method for fine-grained open-set fault diagnosis of rotating machinery that selects optimal time‑frequency representations using a metric‑guided approach and…
Data-driven dimensionally decomposed generalized polynomial chaos expansion for forward uncertainty quantification
Hojun Choi, Eunho Heo, Dongjin Lee
Dimensionally decomposed generalized polynomial chaos expansion (DD-GPCE) efficiently performs forward uncertainty quantification (UQ) in complex engineering systems with high-dime…
A Robust Method for Fault Detection and Severity Estimation in Mechanical Vibration Data
Youngjae Jeon, Eunho Heo, Jinmo Lee +2
This paper proposes a robust method for fault detection and severity estimation in multivariate time-series data to enhance predictive maintenance of mechanical systems. We use the…