Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines
As industries become automated and connectivity technologies advance, a wide range of
systems continues to generate massive amounts of data. Many approaches have been …
systems continues to generate massive amounts of data. Many approaches have been …
Anomaly detection for IoT time-series data: A survey
Anomaly detection is a problem with applications for a wide variety of domains; it involves
the identification of novel or unexpected observations or sequences within the data being …
the identification of novel or unexpected observations or sequences within the data being …
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
Application of big data and machine learning in smart grid, and associated security concerns: A review
This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …
learning in the electrical power grid introduced through the emergence of the next …
Cybersecurity for industrial control systems: A survey
Abstract Industrial Control System (ICS) is a general term that includes supervisory control &
data acquisition (SCADA) systems, distributed control systems (DCS), and other control …
data acquisition (SCADA) systems, distributed control systems (DCS), and other control …
Anomaly detection and critical SCADA parameters identification for wind turbines based on LSTM-AE neural network
H Chen, H Liu, X Chu, Q Liu, D Xue - Renewable Energy, 2021 - Elsevier
Continuous monitoring of wind turbine health conditions using anomaly detection methods
can improve the reliability and reduce maintenance costs during operation of wind turbine …
can improve the reliability and reduce maintenance costs during operation of wind turbine …
An evaluative study on IoT ecosystem for smart predictive maintenance (IoT-SPM) in manufacturing: Multiview requirements and data quality
With the recent advances of the Internet of Things (IoT), innovative techniques, and concepts
have emerged, such as digital twins and industrial 4.0. As one of the essential parts of a …
have emerged, such as digital twins and industrial 4.0. As one of the essential parts of a …
Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future
J Chatterjee, N Dethlefs - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
Wind energy has emerged as a highly promising source of renewable energy in recent
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …
Fault detection of wind turbines using SCADA data and genetic algorithm-based ensemble learning
Due to global efforts to reduce the rise in the average global temperature by replacing fossil
fuels, the amount of wind power installed worldwide is continuously increasing. The costs …
fuels, the amount of wind power installed worldwide is continuously increasing. The costs …
An effective predictive maintenance framework for conveyor motors using dual time-series imaging and convolutional neural network in an industry 4.0 environment
KS Kiangala, Z Wang - Ieee Access, 2020 - ieeexplore.ieee.org
The ascent of Industry 4.0 and smart manufacturing has emphasized the use of intelligent
manufacturing techniques, tools, and methods such as predictive maintenance. The …
manufacturing techniques, tools, and methods such as predictive maintenance. The …