Transformers Condition Evaluation Based on Bayesian Classifier
- 1. Electric Power Research Institute, State Grid Tianjin Electric Power Corporation, Tianjin 300384 (China)
- 2. XJ Group Corporation, Xuchang 461000 (China)
- 3. State Grid Tianjin Electric Power Corporation, Tianjin 300010 (China)
- 4. School of Electrical and Information Engineering, Tianjin University, Tianjin 300072 (China)
Description
Higher requirements was put forward to accurate and efficient transformer condition assessment by the large-scale promotion of condition overhaul. Core indicators reflecting the running state of transformer were selected to establish transformer evaluation indicators system with analysis on transformer on-line monitoring, live detection and electrical test, and then the indicator scoring method and subordinating degree function of indicator score and transformer state were given. On this basis Bayesian theory was introduced briefly and a transformer condition assessment method based on Bayesian classifier was presented considering transformer monitoring and test data, the current data included, on multiple time dimensions. Finally, through analysis on transformers actual monitoring data in some power network, accurate assessment of transformer running state was made and the practicability and accuracy of this method was verified. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1757-899X/452/4/042031Additional details
Identifiers
Publishing Information
- Journal Title
- IOP Conference Series. Materials Science and Engineering (Online)
- Journal Volume
- 452
- Journal Issue
- 4
- Journal Page Range
- [6 p.]
- ISSN
- 1757-899X
Conference
- Title
- 3. International Conference on Insulating Materials, Material Application and Electrical Engineering
- Dates
- 15-16 Sep 2018
- Place
- Melbourne (Australia)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 52102162
- Subject category
- S42: ENGINEERING;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- ACCURACY; DETECTION; ELECTRIC CURRENTS; MONITORING; TRANSFORMERS
- Descriptors DEC
- CURRENTS; ELECTRICAL EQUIPMENT; EQUIPMENT