Showing 1 - 6 of 6
This paper presents an Improved Bagging Algorithm (IBA) to recognize ultra-high-frequency (UHF) signals of partial discharges (PDs). This approach establishes the sample information entropy for each sample and the re-sampling process of the traditional Bagging algorithm is optimized. Four...
Persistent link: https://www.econbiz.de/10010668159
The development of the smart grid has resulted in new requirements for fault prediction of power transformers. This paper presents an entropy-based Bagging (E-Bagging) method for prediction of characteristic parameters related to power transformers faults. A parameter of comprehensive...
Persistent link: https://www.econbiz.de/10010668170
Dissolved gas analysis (DGA) has been widely applied to diagnose internal faults in transformer insulation systems. However, the accuracy of DGA technique is limited because of the lack of positive correlation of the fault-identifying gases with faults found in power transformers. This paper...
Persistent link: https://www.econbiz.de/10010668181
Data collected from the supervisory control and data acquisition (SCADA) system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs), is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind...
Persistent link: https://www.econbiz.de/10010765423
Oil-impregnated paper is widely used in power transmission equipment as a reliable insulation. However, copper sulphide deposition on oil-paper insulation can lead to insulation failures in power transformers. This paper presents the influences of copper sulfur corrosion and copper sulphide...
Persistent link: https://www.econbiz.de/10011030703
Converter transformers are the key and the most important components in high voltage direct current (HVDC) power transmission systems. Statistics show that the failure rate of HVDC converter transformers is approximately twice of that of transformers in AC power systems. This paper presents an...
Persistent link: https://www.econbiz.de/10011031340