Multi-Timescale Electromechanical Identification and Stress-Reflective Modeling of Lithium-Ion Battery for Reliability-Based Design

Statistical Model Calibration and Validation for Battery Packs

Unsupervised Domain Adaptation for Cross-Domain Fault Diagnosis of Rotating Machinery Under Limited Data Information

Prognostics and Health Management for a Journal Bearing System

Design of General-Purpose Industrial Robot Considering Random Use Condition and Manufacturing Uncertainty

Resilience-driven Design for an Industrial Robot

Motor Fault Scale-focused Feature Learning Considering Operation Variability and Diagnosis Uncertainty

Prognostics and Health Management for Motors

An Uncertainty-Aware Framework for Fault Diagnosis in Industrial Systems Using Low and High Sampling Rate Signals

Prognostics and Health Management for Gearbox 

Deep-learning-based Methodology for Macro- and Micro-level Fault Diagnosis of Rotating Machinery Using Low- and High-resolution Signals

Prognostics and Health Management for a Journal Bearing System

A Study on Diagnosis of Bearings in Incipient Fault Stage Considering Vibration Generation Mechanisms

Prognostics and Health Management for a Rolling Element Bearing System

Deep Learning Based Health Prognostics of Oil-immersed Transformers for Contaminated Dissolved Gas Analysis Data

Prognostics and Health Management for Industrial Power Transformers

Investigation on Fault Information Extraction for Acoustic Emission based Rolling Element Bearing Diagnostics under Noisy Conditions

Prognostics and Health Management for a Rolling Element Bearing System

Inference of Central Blood Pressure Waveform and Arterial Disease Diagnosis using Explainable Artificial Intelligence Regularized for Individuality

Prognostics and Health Management for Humans

Vibration-based Gearbox Diagnostics by Enhancement of Weak Fault-characteristic Information

Prognostics and Health Management for Gearboxes in Industrial Robots

Physics-guided Deep Learning Study for Fault Diagnostics of Industrial Motors Under Variable Operating Conditions Using Stator Current Signals

Prognostics and Health Management for Motors

Investigation on Statistical Model Calibration and Updating of Physics and Data-driven Modeling for Hybrid Digital Twin

Statistial Model Verification and Validation for Digital Twin

Maximal Information Use for Deep Learning Based Fault Diagnosis Techniques

Prognostics and Health Management for Rotating Machinery

Optimization-based Model Improvement for Error Sources Identification in a Computational Model

Statisticsl Model Calibration & Validation

Deep-Learning-Based Fault Diagnosis Using Dissolved Gas Analysis for Unlabeled Fault Data of Industrial Power Transformers

Prognostics and Health Management for Industrial Power Transformers