Toward cognitive predictive maintenance: A survey of graph-based approaches
Abstract Predictive Maintenance (PdM) has continually attracted interest from the
manufacturing community due to its significant potential in reducing unexpected machine …
manufacturing community due to its significant potential in reducing unexpected machine …
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 …
Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises
Anomaly detection of machine tools plays a vital role in the machinery industry to sustain
efficient operation and avoid catastrophic failures. Compared to traditional machine learning …
efficient operation and avoid catastrophic failures. Compared to traditional machine learning …
You can get smaller: A lightweight self-activation convolution unit modified by transformer for fault diagnosis
The fault diagnosis methods based on convolutional neural network (CNN) have achieved
many excellent results. However, owing to the deployment cost, numerous CNNs with large …
many excellent results. However, owing to the deployment cost, numerous CNNs with large …
Compound fault diagnosis for industrial robots based on dual-transformer networks
The accurate diagnosis of the compound fault of industrial robots can be highly beneficial to
maintenance management. In the actual noisy working environment of industrial robots, the …
maintenance management. In the actual noisy working environment of industrial robots, the …
Conditional distribution-guided adversarial transfer learning network with multi-source domains for rolling bearing fault diagnosis
Z Wu, H Jiang, S Liu, Y Liu, W Yang - Advanced Engineering Informatics, 2023 - Elsevier
The application of transfer learning to effectively identify rolling bearing fault has been
attracting much attention. Most of the current studies are based on single-source domain or …
attracting much attention. Most of the current studies are based on single-source domain or …
Graph neural network architecture search for rotating machinery fault diagnosis based on reinforcement learning
In order to improve the accuracy of fault diagnosis, researchers are constantly trying to
develop new diagnostic models. However, limited by the inherent thinking of human beings …
develop new diagnostic models. However, limited by the inherent thinking of human beings …
Research on fault diagnosis method of MS-CNN rolling bearing based on local central moment discrepancy
Z Meng, W Cao, D Sun, Q Li, W Ma, F Fan - Advanced Engineering …, 2022 - Elsevier
Transfer learning is an excellent approach to deal with the problem that the target domain
label can not be adequately obtained when rolling bearing cross-condition fault detection. A …
label can not be adequately obtained when rolling bearing cross-condition fault detection. A …
Reinforcement learning-based distant supervision relation extraction for fault diagnosis knowledge graph construction under industry 4.0
Fault diagnosis is the key concern in the operation and maintenance of industrial assets. A
fault diagnosis knowledge graph (KG) can provide decision support to the engineers to …
fault diagnosis knowledge graph (KG) can provide decision support to the engineers to …
[HTML][HTML] Fault diagnosis and self-healing for smart manufacturing: a review
Manufacturing systems are becoming more sophisticated and expensive, particularly with
the development of the intelligent industry. The complexity of the architecture and concept of …
the development of the intelligent industry. The complexity of the architecture and concept of …