ChatGPT-like large-scale foundation models for prognostics and health management: A survey and roadmaps
PHM technology is vital in industrial production and maintenance, identifying and predicting
potential equipment failures and damages. This enables proactive maintenance measures …
potential equipment failures and damages. This enables proactive maintenance measures …
LiConvFormer: A lightweight fault diagnosis framework using separable multiscale convolution and broadcast self-attention
In recent studies, Transformer collaborated with convolution neural network (CNN) have
made certain progress in the field of intelligent fault diagnosis by leveraging their respective …
made certain progress in the field of intelligent fault diagnosis by leveraging their respective …
Application of deep learning to fault diagnosis of rotating machineries
H Su, L Xiang, A Hu - Measurement Science and Technology, 2024 - iopscience.iop.org
Deep learning (DL) has attained remarkable achievements in diagnosing faults for rotary
machineries. Capitalizing on the formidable learning capacity of DL, it has the potential to …
machineries. Capitalizing on the formidable learning capacity of DL, it has the potential to …
Dynamic model-assisted transferable network for liquid rocket engine fault diagnosis using limited fault samples
The accurate detection and diagnosis of faults in Liquid Rocket Engines (LREs) are critical
for ensuring space mission safety. However, the limited availability of actual fault samples …
for ensuring space mission safety. However, the limited availability of actual fault samples …
Toward purifying defect feature for multilabel sewer defect classification
An automatic vision-based sewer inspection plays a key role of sewage system in a modern
city. Recent advances focus on utilizing a deep learning model to realize the sewer …
city. Recent advances focus on utilizing a deep learning model to realize the sewer …
A lightweight transformer with strong robustness application in portable bearing fault diagnosis
Although Transformer has achieved excellent results in various tasks in industrial scenes,
owing to the environmental noise and cost limitation, the fault diagnosis approaches based …
owing to the environmental noise and cost limitation, the fault diagnosis approaches based …
Like draws to like: A Multi-granularity Ball-Intra Fusion approach for fault diagnosis models to resists misleading by noisy labels
Although data-driven fault diagnosis methods have achieved remarkable results, these
achievements often rely on high-quality datasets without noisy labels, which can mislead the …
achievements often rely on high-quality datasets without noisy labels, which can mislead the …
Empowering intelligent manufacturing with edge computing: A portable diagnosis and distance localization approach for bearing faults
H Fang, J An, B Sun, D Chen, J Bai, H Liu… - Advanced Engineering …, 2024 - Elsevier
Recent intelligent diagnostic algorithms for industrial practice have achieved impressive
results. However, due to safety considerations, complex environments and deployment cost …
results. However, due to safety considerations, complex environments and deployment cost …
The method based on clustering for unknown failure diagnosis of rolling bearings
Effective fault diagnosis is an important guarantee for the safe and stable operation of
mechanical systems. Nowadays, most fault diagnosis methods are for known classes …
mechanical systems. Nowadays, most fault diagnosis methods are for known classes …
A customized meta-learning framework for diagnosing new faults from unseen working conditions with few labeled data
J Long, R Zhang, Y Chen, R Zhao… - IEEE/ASME …, 2023 - ieeexplore.ieee.org
Few-shot fault diagnosis aims to detect novel faults with only a few labeled samples in each
category. Most of the few-shot learning (FSL)–based fault diagnosis models use meta …
category. Most of the few-shot learning (FSL)–based fault diagnosis models use meta …