A review of the application of deep learning in intelligent fault diagnosis of rotating machinery
Z Zhu, Y Lei, G Qi, Y Chai, N Mazur, Y An, X Huang - Measurement, 2023 - Elsevier
With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …
recent years and has become an important technique for scholars to study and apply. The …
Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing
Fault diagnosis of rolling bearings has attracted extensive attention in industrial fields, which
plays a vital role in guaranteeing the reliability, safety, and economical efficiency of …
plays a vital role in guaranteeing the reliability, safety, and economical efficiency of …
An integrated multitasking intelligent bearing fault diagnosis scheme based on representation learning under imbalanced sample condition
Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary
mechanical system. In practice, the sample proportion between faulty data and healthy data …
mechanical system. In practice, the sample proportion between faulty data and healthy data …
Attention-guided joint learning CNN with noise robustness for bearing fault diagnosis and vibration signal denoising
Mechanical system usually operates in harsh environments, and the monitored vibration
signal faces substantial noise interference, which brings great challenges to the robust fault …
signal faces substantial noise interference, which brings great challenges to the robust fault …
Interpretable convolutional neural network with multilayer wavelet for Noise-Robust Machinery fault diagnosis
Convolutional neural networks (CNNs) are being utilized for mechanical fault diagnosis, due
to its excellent automatic discriminative feature learning ability. However, the poor …
to its excellent automatic discriminative feature learning ability. However, the poor …
GTFE-Net: A gramian time frequency enhancement CNN for bearing fault diagnosis
Fault diagnosis of the bearing is vital for the safe and reliable operation of rotating machines
in the manufacturing industry. Convolutional neural networks (CNNs) have been popular in …
in the manufacturing industry. Convolutional neural networks (CNNs) have been popular in …
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 …
Selective kernel convolution deep residual network based on channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis
S Zhang, Z Liu, Y Chen, Y Jin, G Bai - ISA transactions, 2023 - Elsevier
This paper proposes a selective kernel convolution deep residual network based on the
channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis. First …
channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis. First …
Explainable graph wavelet denoising network for intelligent fault diagnosis
Deep learning (DL)-based intelligent fault diagnosis methods have greatly promoted the
development of the field of fault diagnosis due to their powerful feature extraction ability for …
development of the field of fault diagnosis due to their powerful feature extraction ability for …