Prognostics and health management of rotating machinery of industrial robot with deep learning applications—A review

P Kumar, S Khalid, HS Kim - Mathematics, 2023 - mdpi.com
The availability of computational power in the domain of Prognostics and Health
Management (PHM) with deep learning (DL) applications has attracted researchers …

A Comprehensive review of emerging trends in aircraft structural prognostics and health management

S Khalid, J Song, MM Azad, MU Elahi, J Lee, SH Jo… - Mathematics, 2023 - mdpi.com
This review paper addresses the critical need for structural prognostics and health
management (SPHM) in aircraft maintenance, highlighting its role in identifying potential …

Online fault diagnosis of industrial robot using IoRT and hybrid deep learning techniques: an experimental approach

H Bilal, MS Obaidat, MS Aslam, J Zhang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
The Internet of Robotic Things (IoRT) is growing rapidly with new applications. Co-operatory
robotics enables the sharing of information, autonomy, and fail-safe interaction with …

Leveraging Deep Learning Algorithms for Predicting Power Outages and Detecting Faults: A Review

M Rizvi - Advances in Research, 2023 - go7publish.com
Power outage prediction and fault detection play crucial roles in ensuring the reliability and
stability of electrical power systems. Traditional methods for predicting power outages and …

Fault Diagnosis of Bearings Using Wavelet Packet Energy Spectrum and SSA-DBN

J Qu, X Cheng, P Liang, L Zheng, X Ma - Processes, 2023 - mdpi.com
To enhance fault characteristics and improve fault detection accuracy in bearing vibration
signals, this paper proposes a fault diagnosis method using a wavelet packet energy …

Design of fire risk estimation method based on facility data for thermal power plants

CJ Song, JY Park - Sensors, 2023 - mdpi.com
Simple Summary We provide a data classification and analysis method to estimate fire risk
using facility data for thermal power plants. Experimental analysis is conducted on the data …

A data-driven regression model for predicting thermal plant performance under load fluctuations

G Prokhorskii, S Rudra, M Preißinger, E Eder - Carbon Neutrality, 2024 - Springer
The global energy demand is still primarily reliant on fossil-fueled thermal power plants. With
the growing share of renewables, these plants must frequently adjust their loads …

Comparison on erosion performance of HVOF sprayed NiCrSiBCFe-WC-Co and NiCrSiBCFe-Cr3C2NiCr coatings

AS Yadav, SB Mishra - Tribology-Materials, Surfaces & …, 2024 - journals.sagepub.com
Hard coatings are used to improve the wear resistance of various engineering materials
while maintaining the mechanical properties of the base material. In this work, the high …

Bayesian Learning of Causal Networks for Unsupervised Fault Diagnosis in Distributed Energy Systems

F Castelletti, F Niro, M Denti, D Tessera, A Pozzi - IEEE Access, 2024 - ieeexplore.ieee.org
Distributed energy generation systems, key for producing electricity near usage points, are
essential to meet theglobal electricity demand, leveraging diverse sources likerenewables …

Review of the opportunities and challenges to accelerate mass‐scale application of smart grids with large‐language models

H Shi, L Fang, X Chen, C Gu, K Ma, X Zhang… - IET Smart …, 2024 - Wiley Online Library
Smart grids represent a paradigm shift in the electricity industry, moving from traditional one‐
way systems to more dynamic, interconnected networks. These grids are characterised by …