A5071732509- Machine Fault Diagnosis Techniques
- Gear and Bearing Dynamics Analysis
- Structural Health Monitoring Techniques
- Educational Research and Pedagogy
- Fault Detection and Control Systems
- Education, Safety, and Science Studies
- Probabilistic and Robust Engineering Design
- Engineering Diagnostics and Reliability
- Non-Destructive Testing Techniques
- Advanced Multi-Objective Optimization Algorithms
- Engineering Applied Research
- Educational Systems and Policies
- Electrostatic Discharge in Electronics
- Science Education and Pedagogy
- High-Temperature Coating Behaviors
- Welding Techniques and Residual Stresses
- Oil and Gas Production Techniques
- Education and Learning Interventions
- High Entropy Alloys Studies
- Wind Energy Research and Development
- Reliability and Maintenance Optimization
- Water Systems and Optimization
- Diamond and Carbon-based Materials Research
- Electronic Packaging and Soldering Technologies
- Railway Engineering and Dynamics
Gwangju Institute of Science and Technology
2016-2025
GeneMatrix (South Korea)
2024
Ajou University
2023-2024
Agency for Defense Development
2024
Seoul National University
2008-2023
Sungkyunkwan University
2022
Massachusetts Institute of Technology
2021
University of Maryland, College Park
2009-2016
Korean Register (South Korea)
2015
Myongji University
2014
This paper describes the three methodologies used by CALCE in their winning entry for IEEE 2012 PHM Data Challenge competition. An experimental data set from seventeen ball bearings was provided FEMTO-ST Institute. The consisted of six algorithm training and eleven testing. authors developed prognostic algorithms based on to estimate remaining useful life test bearings. Three are presented this paper. Result accuracies methodology presented.
This paper proposes a scalable and unsupervised feature engineering method that uses vibration imaging deep learning. For scalability, approach is devised incorporates data from systems with various scales, such as small testbeds real field-deployed systems. Moreover, learning proposed for engineering. The overall procedure includes three key steps: 1) image generation; 2) extraction; 3) fault classifier design. To demonstrate the validity of approach, case studies are conducted using an RK4...
Extensive prior studies aimed at the development of diagnostic methods for planetary gearboxes have mainly examined acceleration and acoustic emission signals. Recently, due to relationship between gear mesh stiffness transmission error (TE), TE-based techniques emerged as a promising way analyze dynamic behavior spur helical gears. However, date, TE has not been used measure detect faults in In this paper, we propose new methodology model-based fault diagnostics gears using A lumped...
This paper proposes a new prognostic method for the health state of proton exchange membrane (PEM) fuel cells. The is designed to predict state-of-health (SOH) PEMs and provide root cause analysis predicted degradation. In this method, an equivalent circuit model (ECM) built emulate impedance spectrum PEM Because key degradation parameters in ECM cannot be measured situ, instead estimates indirectly using output voltage. estimation based on linear relationship between Using constructed...
Abstract The detection of nuclear spins using individual electron has enabled diverse opportunities in quantum sensing and information processing. Proof-of-principle experiments have demonstrated atomic-scale imaging nuclear-spin samples controlled multi-qubit registers. However, to image more complex realize larger-scale processors, computerized methods that efficiently automatically characterize spin systems are required. Here, we a deep learning model for automatic identification the...
The interior of a nuclear reactor, filled with water and classified as medium-level radiation area, is inaccessible to humans, requiring underwater remote cutting during decommissioning. However, the process generates bubbles light, hindering camera-based monitoring necessitating status determination through sensor data. This study introduces an adaptive weighted parallel 1D-DenseNet that integrates pressure hydrophone data in both time frequency domains distinguish between idle states....
Pipeline damage in mission‐critical systems, such as pipelines within naval ships, can result substantial consequences. Compared to manual inspection of pipeline by crew members onboard, structural health monitoring systems offers prompt identification sites, enabling efficient mitigation. However, one challenge this approach is deriving an optimal sensor placement (OSP) strategy, given the large and complex found real‐scale vessels. To address issue, a search space reduction method proposed...
Abstract In the fault diagnosis of rolling element bearings (REBs), spall size is a typical indicator severity. Conventionally, estimation relies on expert-knowledge-based or data-driven approaches. Expert-knowledge-based approaches require accurate assumptions about spall-excited events, making them challenging to apply in field environments. contrast, often struggle with insufficient training data and limited generalization across various operating conditions. To address this challenge,...
Despite advantages of organic light-emitting diode (OLED) displays over liquid crystal displays, reliability concerns persist. These must be addressed before OLED are widely adopted. In particular, existing methods unable to reliably estimate the lifetime large (i.e., 55 in or larger). This study proposes a novel model that incorporates physical and statistical uncertainty panels under normal usage conditions. A likelihood-ratio-based validation method is presented determine validity...
We investigate how to manipulate the ratio between thermal conductivity (κ) and yield strength (σy) in face-centered cubic solid-solutions by varying number of principal elements (NPEs) temperature. The influence NPEs on κ its electronic (κe) lattice (κl) contribution is evaluated using Wiedemann–Franz law. Positive Δκ/ΔT highest κl/κe high-entropy alloys (HEAs) can be understood considering severe distortion compositional complexity. Among from Ni quinary alloys, NiCoFeCrMn HEA exhibits...