CNN-based fault detection for smart manufacturing
A smart factory is a highly digitized and networked production facility based on smart
manufacturing. A smart manufacturing plant is the result of intelligent systems deployed in …
manufacturing. A smart manufacturing plant is the result of intelligent systems deployed in …
Implementation of a novel algorithm of wheelset and axle box concurrent fault identification based on an efficient neural network with the attention mechanism
D Yao, H Liu, J Yang, J Zhang - Journal of Intelligent Manufacturing, 2021 - Springer
With the rapid development of urban rail transit in recent years, it becomes necessary to
ensure the operation safety of train wheelset axle boxes. Aiming at the problems of large …
ensure the operation safety of train wheelset axle boxes. Aiming at the problems of large …
Densely connected semi-Bayesian network for machinery fault diagnosis with non-ideal data
W Liu, J Yu - Mechanical Systems and Signal Processing, 2023 - Elsevier
Fault diagnosis techniques (FDT) face the challenge of implementing model learning in the
presence of limited, imbalanced, or non-ideal data, which is a fundamental and crucial …
presence of limited, imbalanced, or non-ideal data, which is a fundamental and crucial …
Spatio-temporal anomaly detection with graph networks for data quality monitoring of the hadron calorimeter
The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-
energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data …
energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data …
Prognostics and health management of wind energy infrastructure systems
The improvements in wind energy infrastructure have been a constant process throughout
many decades. There are new advancements in technology that can further contribute …
many decades. There are new advancements in technology that can further contribute …
Improved multiclass support vector data description for planetary gearbox fault diagnosis
H Hou, H Ji - Control Engineering Practice, 2021 - Elsevier
Planetary gearbox is one of the most important components of rotating machinery and plays
a key role in modern industry. Due to the complex physical structures and harsh working …
a key role in modern industry. Due to the complex physical structures and harsh working …
Transfer learning models for detecting six categories of phonocardiogram recordings
M Wang, B Guo, Y Hu, Z Zhao, C Liu… - Journal of Cardiovascular …, 2022 - mdpi.com
Background and aims: Auscultation is a cheap and fundamental technique for detecting
cardiovascular disease effectively. Doctors' abilities in auscultation are varied. Sometimes …
cardiovascular disease effectively. Doctors' abilities in auscultation are varied. Sometimes …
Data augmentation on convolutional neural networks to classify mechanical noise
Mechanical noise identification and classification are essential for automotive and
machinery fault diagnosis. The scarcity of labelled audio data for noise-related mechanical …
machinery fault diagnosis. The scarcity of labelled audio data for noise-related mechanical …
An improved prototype network and data augmentation algorithm for few-shot structural health monitoring using guided waves
The significance of implementing online structural health monitoring (SHM) for aerospace
structures under harsh service environments cannot be overemphasized. Deep learning has …
structures under harsh service environments cannot be overemphasized. Deep learning has …
Robustness enhancement of machine fault diagnostic models for railway applications through data augmentation
The performance of machine learning based machine fault diagnosis (MFD) models could
be impaired due to operating condition variations encountered in the real-world industrial …
be impaired due to operating condition variations encountered in the real-world industrial …