학술논문

Application of Cloud Model and Matter Element Theory in Transformer Fault Diagnosis
Document Type
Conference
Source
2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2018 IEEE 3rd. :2089-2092 Oct, 2018
Subject
Computing and Processing
Robotics and Control Systems
Oil insulation
Power transformers
Correlation
Uncertainty
Standards
Fault diagnosis
Clouds
Transformer
Cloud model
Improved Matter-Element Model
Language
Abstract
Based on cloud model and matter element theory, and combining the uncertain reasoning characteristics of the cloud model and qualitative and quantitative analysis can be carried out at the same time by matter element theory, a power transformer fault diagnosis method is proposed, which effectively solves the problem of fewer data samples, especially fewer fault data samples. Taking the actual data as an example, the improved matter-element theory model and correlation calculation data are compared, and the results show that the improved matter element theory model has higher diagnostic accuracy than traditional methods. Example analysis verifies the correctness and effectiveness of the method.