Prognostics and health management: A review from the perspectives of design, development and decision
Prognostics and health management (PHM) is an enabling technology used to maintain the
reliable, efficient, economic and safe operation of engineering equipment, systems and …
reliable, efficient, economic and safe operation of engineering equipment, systems and …
[HTML][HTML] Semi-supervised learning for industrial fault detection and diagnosis: A systemic review
JM Ramírez-Sanz, JA Maestro-Prieto… - ISA transactions, 2023 - Elsevier
Abstract The automation of Fault Detection and Diagnosis (FDD) is a central task for many
industries today. A myriad of methods are in use, although the most recent leading …
industries today. A myriad of methods are in use, although the most recent leading …
Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis
In the engineering practice, lacking of data especially labeled data typically hinders the wide
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …
Challenges to IoT-enabled predictive maintenance for industry 4.0
The Industry 4.0 paradigm is boosting the relevance of predictive maintenance (PdM) for
manufacturing and production industries. PdM strongly relies on Internet of Things (IoT) …
manufacturing and production industries. PdM strongly relies on Internet of Things (IoT) …
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis
Fault diagnosis is an indispensable basis for the collaborative maintenance in prognostic
and health management. Most of existing data-driven fault diagnosis approaches are …
and health management. Most of existing data-driven fault diagnosis approaches are …
Quality analysis in metal additive manufacturing with deep learning
As a promising modern technology, additive manufacturing (AM) has been receiving
increasing research and industrial attention in the recent years. With its rapid development …
increasing research and industrial attention in the recent years. With its rapid development …
Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery
Despite the recent advances on intelligent data-driven machinery fault diagnostics, large
amounts of high-quality supervised data are mostly required for model training. However, it …
amounts of high-quality supervised data are mostly required for model training. However, it …
A generative adversarial network-based intelligent fault diagnosis method for rotating machinery under small sample size conditions
Rotating machinery plays a key role in mechanical equipment, and the fault diagnosis of
rotating machinery is a popular research topic. To overcome the dependency on expert …
rotating machinery is a popular research topic. To overcome the dependency on expert …
Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications
Abstract Prognostics and Health Management (PHM) is an integrated technique for
improving the availability and efficiency of high-value industry equipment and reducing the …
improving the availability and efficiency of high-value industry equipment and reducing the …
A framework for predicting the remaining useful life of machinery working under time-varying operational conditions
Remaining useful life (RUL) prediction can provide additional capabilities to condition-
based maintenance (CBM) and predictive maintenance (PdM) for the reliability and service …
based maintenance (CBM) and predictive maintenance (PdM) for the reliability and service …