BA-PNN-based methods for power transformer fault diagnosis
This paper presents a machine learning-based approach to power transformer fault
diagnosis based on dissolved gas analysis (DGA), a bat algorithm (BA), optimizing the …
diagnosis based on dissolved gas analysis (DGA), a bat algorithm (BA), optimizing the …
Improving diagnostic performance of a power transformer using an adaptive over-sampling method for imbalanced data
Dissolved gas analysis (DGA) of insulating oil in power transformers can offer valuable
information related to faults. Due to the poor and unbalanced characteristics of typical DGA …
information related to faults. Due to the poor and unbalanced characteristics of typical DGA …
Investigation on machine learning algorithms to support transformer dissolved gas analysis fault identification
Dissolved gas analysis (DGA) is a powerful tool to monitor the condition of a power
transformer. Several interpretation methods have been proposed, one of the most reliable of …
transformer. Several interpretation methods have been proposed, one of the most reliable of …
Technical and tactical diagnosis model of table tennis matches based on BP neural network
W Huang, M Lu, Y Zeng, M Hu, Y Xiao - BMC Sports Science, Medicine …, 2021 - Springer
Background The technical and tactical diagnosis of table tennis is extremely important in the
preparation for competition which is complicated by an apparent nonlinear relationship …
preparation for competition which is complicated by an apparent nonlinear relationship …
Faults diagnostics of high-voltage equipment based on the analysis of the dynamics of changing of the content of gases
O Shutenko - Energetika, 2018 - lmaleidykla.lt
In the article, the gas content of oils in high-voltage equipment with defects of different types
is analysed. Typical gas contents and gas ratios for 38 most frequently encountered defects …
is analysed. Typical gas contents and gas ratios for 38 most frequently encountered defects …
A Hybrid machine‐learning method for oil‐immersed power transformer fault diagnosis
This paper presents a hybrid machine‐learning method based on oil‐immersed power
transformer fault diagnosis Probability Neural Network (PNN) optimized via a Multi‐Verse …
transformer fault diagnosis Probability Neural Network (PNN) optimized via a Multi‐Verse …
Integrated decision‐making method for power transformer fault diagnosis via rough set and DS evidence theories
Y Xu, Y Li, Y Wang, C Wang… - IET Generation …, 2020 - Wiley Online Library
Precise power transformer fault diagnosis involves incorporating multi‐source monitoring
information. Uncertain information, missing data, usually occurs in transformer fault cases …
information. Uncertain information, missing data, usually occurs in transformer fault cases …
Defect Prediction for Capacitive Equipment in Power System
Q Peng, Z Zheng, H Hu - Applied Sciences, 2024 - mdpi.com
As a core component of the smart grid, capacitive equipment plays a critical role in modern
power systems. When defects occur, they pose a significant threat to the safety of both other …
power systems. When defects occur, they pose a significant threat to the safety of both other …
Analysis of gas composition in oil-filled faulty equipment with acetylene as the key gas
O Shutenko - Energetika, 2019 - lmaleidykla.lt
The article presents results of oil-dissolved gas analysis for 239 units of high-voltage
equipment with faults under which acetylene is the key gas. The analysis revealed 13 types …
equipment with faults under which acetylene is the key gas. The analysis revealed 13 types …
Synthesis of aryloxyacetylthiourea derivatives for the development of radicle elongation inhibitor of parasitic weeds
M Sonoda, Y Mimura, S Noda, A Okazawa - Tetrahedron, 2023 - Elsevier
Abstract Aryloxyacetylthiourea, 1-(3, 4-dichlorophenyl)-3-(2-phenoxyacetyl) thiourea (PI-28),
has attracted attention as a lead compound for the development of radicle elongation …
has attracted attention as a lead compound for the development of radicle elongation …