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Condition monitoring of wind turbine based on deep learning networks and kernel principal component analysis
A Zhu, Q Zhao, T Yang, L Zhou, B Zeng - Computers and Electrical …, 2023 - Elsevier
Condition monitoring is frequently hampered by the abominable working conditions of wind
turbines (WTs). The present study proposes a new approach for condition monitoring of WT …
turbines (WTs). The present study proposes a new approach for condition monitoring of WT …
Optimal detection and classification of grid connected system using MSVM-FSO technique
SRD Stallon, R Anand, R Kannan… - … Science and Pollution …, 2024 - Springer
This paper, a hybrid method, is proposed for protecting the hybrid photovoltaic (PV) and
wind turbine (WT) system. The proposed protecting method is the hybrid wrapper of both the …
wind turbine (WT) system. The proposed protecting method is the hybrid wrapper of both the …
Intelligent Detection Method of Power Grid Fault Big Data Based on Deep Learning
X Tian, Y Wang, Y Liu - … Conference on New Energy and Power …, 2023 - ieeexplore.ieee.org
To ensure the stable operation of the distribution network, a new approach is proposed for
the intelligent detection of power grid faults using deep learning and big data analysis. The …
the intelligent detection of power grid faults using deep learning and big data analysis. The …
Autonomous Inspection Method of UHV Substation Robot Based on Deep Learning in Cloud Computing Environment
Z Wang, R Meng, Z Zhao - Journal of Circuits, Systems and …, 2024 - World Scientific
Aiming at the problem that substation robots cannot automatically find and analyze the fault
equipment and carry out patrol inspection, a method of autonomous patrol inspection for …
equipment and carry out patrol inspection, a method of autonomous patrol inspection for …
Application of bare-bones cuckoo search algorithm for generator fault diagnosis
Y **ong, J Cheng - Recent Advances in Electrical & Electronic …, 2022 - benthamdirect.com
Background: The generator is a mechanical device that converts other forms of energy into
electrical energy. It is widely used in industrial and agricultural production and daily life …
electrical energy. It is widely used in industrial and agricultural production and daily life …
Variable Ordering in Binary Decision Diagram using Spider Monkey Optimization for node and path length optimization
Binary Decision Diagrams (BDDs) are an important data structure for the design of digital
circuits using VLSI CAD tools. The ordering of variables affects the total number of nodes …
circuits using VLSI CAD tools. The ordering of variables affects the total number of nodes …
[PDF][PDF] STUDY ON THE ANALYSIS OF FAULT DATA DURING INTELLIGENT OPERATION OF POWER EQUIPMENT WITH CLUSTER ANALYSIS
M Li, J Zhu, Z Liu - International Journal of Mechatronics and Applied …, 2023 - ijomam.com
Many fault-related data are generated in the intelligent operation of power equipment, and
analyzing these data can help understand the operating condition of the equipment. This …
analyzing these data can help understand the operating condition of the equipment. This …
Minimum error minimax probability machine based residual selection for fault detection
J Zhou, T Xue, M Zhong - 2022 IEEE International Conference …, 2022 - ieeexplore.ieee.org
With the rapid increase of the scale of modern industrial plants, a vast amount of
measurement data is available, which can be used to generate a large number of residuals …
measurement data is available, which can be used to generate a large number of residuals …