Intelligent structural health monitoring of composite structures using machine learning, deep learning, and transfer learning: a review

MM Azad, S Kim, YB Cheon, HS Kim - Advanced Composite …, 2024 - Taylor & Francis
Structural health monitoring (SHM) methods are essential to guarantee the safety and
integrity of composite structures, which are extensively utilized in aerospace, automobile …

Advances in prognostics and health management for aircraft landing gear—progress, challenges, and future possibilities

I Raouf, P Kumar, Y Cheon, M Tanveer, SH Jo… - International Journal of …, 2024 - Springer
Prognostics and health management (PHM) has developed into a crucial discipline because
of its never-ending pursuit of safety, effectiveness, and dependability. The aircraft Landing …

Deep learning-based fault diagnosis of servo motor bearing using the attention-guided feature aggregation network

I Raouf, P Kumar, HS Kim - Expert Systems with Applications, 2024 - Elsevier
This paper introduces a novel approach to fault detection in the servo motor bearings of
industrial robots within the context of Industry 4.0 prognostics and health management. The …

Review on prognostics and health management in smart factory: From conventional to deep learning perspectives

P Kumar, I Raouf, HS Kim - Engineering Applications of Artificial …, 2023 - Elsevier
At present, the fourth industrial revolution is pushing factories toward an intelligent,
interconnected grid of machinery, communication systems, and computational resources …

Deep transfer learning framework for bearing fault detection in motors

P Kumar, P Kumar, AS Hati, HS Kim - Mathematics, 2022 - mdpi.com
The domain of fault detection has seen tremendous growth in recent years. Because of the
growing demand for uninterrupted operations in different sectors, prognostics and health …

Prognostics and health management of the robotic servo-motor under variable operating conditions

H Lee, I Raouf, J Song, HS Kim, S Lee - Mathematics, 2023 - mdpi.com
A robot is essential in many industrial and manufacturing facilities due to its efficiency,
accuracy, and durability. However, continuous use of the robotic system can result in various …

MPARN: multi-scale path attention residual network for fault diagnosis of rotating machines

H Kim, CH Park, C Suh, M Chae… - Journal of …, 2023 - academic.oup.com
Multi-scale convolutional neural network structures consisting of parallel convolution paths
with different kernel sizes have been developed to extract features from multiple temporal …

A diagnosis method for imbalanced bearing data based on improved SMOTE model combined with CNN-AM

Z Wang, T Liu, X Wu, C Liu - Journal of Computational Design …, 2023 - academic.oup.com
A boundary enhancement and Gaussian mixture model (G) optimized synthetic minority
oversampling technique (SMOTE) algorithm (BE-G-SMOTE) is proposed to improve …

A comprehensive multibody model of a collaborative robot to support model-based health management

A Raviola, R Guida, AC Bertolino, A De Martin… - Robotics, 2023 - mdpi.com
Digital models of industrial and collaborative manipulators are widely used for several
applications, such as power-efficient trajectory definition, human–robot cooperation safety …

Transfer learning-based intelligent fault detection approach for the industrial robotic system

I Raouf, P Kumar, H Lee, HS Kim - Mathematics, 2023 - mdpi.com
With increasing customer demand, industry 4.0 gained a lot of interest, which is based on
smart factories. In smart factories, robotic components are vulnerable to failure due to …