[HTML][HTML] Condition monitoring using machine learning: A review of theory, applications, and recent advances
In modern industry, the quality of maintenance directly influences equipment's operational
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …
A review on fault detection and diagnosis techniques: basics and beyond
Safety and reliability are absolutely important for modern sophisticated systems and
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …
Deep order-wavelet convolutional variational autoencoder for fault identification of rolling bearing under fluctuating speed conditions
X Yan, D She, Y Xu - Expert Systems with Applications, 2023 - Elsevier
Because of the complex operating environment of high-end industrial machinery, rolling
bearing is generally operated at fluctuating working conditions such as variable speeds or …
bearing is generally operated at fluctuating working conditions such as variable speeds or …
Construction of health indicators for condition monitoring of rotating machinery: A review of the research
The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
Self-supervised learning (SSL) has recently achieved impressive performance on various
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …
Artificial intelligence applications for microgrids integration and management of hybrid renewable energy sources
The integration of renewable energy sources (RESs) has become more attractive to provide
electricity to rural and remote areas, which increases the reliability and sustainability of the …
electricity to rural and remote areas, which increases the reliability and sustainability of the …
Deep learning for prognostics and health management: State of the art, challenges, and opportunities
B Rezaeianjouybari, Y Shang - Measurement, 2020 - Elsevier
Improving the reliability of engineered systems is a crucial problem in many applications in
various engineering fields, such as aerospace, nuclear energy, and water declination …
various engineering fields, such as aerospace, nuclear energy, and water declination …
Wind turbine gearbox anomaly detection based on adaptive threshold and twin support vector machines
Data-driven condition monitoring reduces downtime of wind turbines and increases
reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that …
reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that …
Modified stacked autoencoder using adaptive Morlet wavelet for intelligent fault diagnosis of rotating machinery
Intelligent fault diagnosis techniques play an important role in improving the abilities of
automated monitoring, inference, and decision making for the repair and maintenance of …
automated monitoring, inference, and decision making for the repair and maintenance of …
Federated transfer learning for intelligent fault diagnostics using deep adversarial networks with data privacy
Intelligent data-driven machinery fault diagnosis methods have been popularly developed in
the past years. While fairly high diagnosis accuracies have been obtained, large amounts of …
the past years. While fairly high diagnosis accuracies have been obtained, large amounts of …