Research on transformer condition evaluation method based on association rule set pair analysis theory
More details
Hide details
State Grid Jinjiang Electric Power Company,Jinjiang 362200,China
State Grid Dehua Electric Power Company,Dehua 362500,China
Submission date: 2023-10-10
Acceptance date: 2023-11-06
Online publication date: 2023-11-07
Publication date: 2023-11-07
Corresponding author
Shanyuan Wang   

State Grid Jinjiang Electric Power Company,Jinjiang 362200,China
Diagnostyka 2023;24(4):2023410
Combining the advantages of set pair analysis and association rules,This paper proposes a transformer condition evaluation based on association rule with set pair analysis theory.In this paper,by analyzing the correlation between the various fault symptoms of transformer,a set of fault types is obtained.At the same time,this paper introduces variable weight formula based on the support degree and confidence degree of association rules,and finally the weight coefficients of fault types and fault symptoms are obtained.By comparing and calculating the support and confidence of association rules,while introducing variable weight formulas,the weight coefficients of fault types and fault symptoms are effectively avoid the subjectivity of expert opinions or experiences.Based on the scalability of set pair analysis,a 5-element connection degree is adopted to improve the accuracy of handling uncertain factors in transformer fault diagnosis.
This work is supported by Science Foundation of State Grid Fujian Electric Power Company(Grant , No. 52133121001F)
Tang W, Niu Z, Zhao B. Research and application of data-driven artificial intelligence technology for condition analysis of power equipment. High Voltage Engineering 2020; 46(09): 2985-2999.
Chu J, Wang Q, Liu Y, Pan J, Yuan H, Yang A, Wang X, Rong M. Fault Diagnosis of SF6-Insulated Equipment by Micro Gas Sensor Array. IEEE Transactions on Power Delivery 2023; 38(01): 222-230.
Zhang S, Wang R, Wang L, Si Y, Lin A, Wang Y. Fault Diagnosis for Power Converters Based on Incremental Learning. IEEE Transactions on Instrumentation and Measurement 2023; 72: 1–13.
Wang Y, Yan J, Yang Z, Qi Z, Wang J, Geng Y. Gas-Insulated Switchgear Insulation Defect Diagnosis via a Novel Domain Adaptive Graph Convolutional Network. IEEE Transactions on Instrumentation and Measurement 2022; 71: 1–10.
Carvalho Fagundes MV, Cheles Keler Á, Oliveira Teles E, Vieira de Melo SAB, Mendonça Freires FG. Multicriteria Decision-Making System for Supplier Selection Considering Risk: A Computational Fuzzy AHP-Based Approach. IEEE Latin America Transactions 2021; 19(9): 1564–1572.
Liu JB, Malik MA, Ayub N, H. Siddiqui MA. Distance measures for multiple-attributes decision-making based on connection numbers of set pair analysis with dual hesitant fuzzy sets. IEEE Access 2020; 8: 9172-9184.
Rastogi SK, Shah SS, Singh BN, Bhattacharya S. Mode Analysis, Transformer Saturation, and Fault Diagnosis Technique for an Open-Circuit Fault in a Three-Phase DAB Converter. IEEE Transactions on Power Electronics 2023; 38(6): 7644–60.
Gao X, Pan L, Deng Y. Quantum Pythagorean Fuzzy Evidence Theory: A Negation of Quantum Mass Function View. IEEE Transactions on Fuzzy Systems 2022; 30(5): 1313–27.
Song SY, Wu F, Bai H, Wang HY. Evaluation of Reservoir Bank Landslide Susceptibility Degree Based on Interval Number and Set Pair Analysis Theory. Journal of Northeastern University (Natural Science) 2022; 43(2): 251-257.
Bazin A, Gros N, Bertaux A, Nicolle C. Condensed Representations of Association Rules in n-Ary Relations. IEEE Transactions on Knowledge and Data Engineering 2023; 35(5): 4598–607.
Grzejda R. Designation of a normal stiffness characteristic for a contact joint between elements fastened in a multi-bolted connection. Diagnostyka 2019; 15(2): 61–4.
Ziani D, Bendimerad E, Ayad A. Influence of the variety of steel tube materials on the impedance behavior of non-destructive eddy current testing. Diagnostyka. 2023;24(2):2023207.
Zhang D. Fault diagnosis of ship power equipment based on adaptive neural network. International Journal of Emerging Electric Power Systems 2022; 23(6): 779–91.
Huang L, Song H, Wang Z, Li H, Ma D, Yu P. The Study of 2-D Magnetic Focusing Inversion Based on the Adjustable Exponential Minimum Support Stabilizing Functional. IEEE Transactions on Geoscience and Remote Sensing 2023; 61: 1–10.
Khelafi A, Ibtiouen R, Djebli A, Touhami O. Design and modelling of three-to-five phase three-limbed transformer. IET Electric Power Applications 2023; 17(5): 670-686.
Mingzhong P, Weiliang J, Ying J. On line monitoring device of bolt pressing force. 2020 7th International Forum on Electrical Engineering and Automation (IFEEA) 2020; 33-36.
Peng F, Gao H, Huang J, Guo Y, Liu Y, Zhang Y. Power Differential Protection for Transformer Based on Fault Component Network. IEEE Transactions on Power Delivery 2023; 38(4): 2464–77.
Wang F, Liang K, Zhong L, Sun Q, Chen S, Duan X, i in. On-Load Tap Changer Internal Contact Health Assessment Based on Ion Detection in Oil. IEEE Transactions on Dielectrics and Electrical Insulation 2023; 30(4): 1825–33.
Zhou H, Yin H, Zhao D, Cai L. Incremental Learning and Conditional Drift Adaptation for Nonstationary Industrial Process Fault Diagnosis. IEEE Transactions on Industrial Informatics 2023; 19(4): 5935–44.
Geng SJ, Wang XL. Predictive Maintenance Scheduling of Parallel Multiple Power Equipment Considering Fault State Deterioration. Systems Engineering 2023; 1-10.
Zhang S, Song H, Cai K. Multiobjective Optimization Design for Lightweight and Crash Safety of Body-in-White Based on Entropy Weighted Grey Relational Analysis and MNSGA-II. IEEE Access 2022; 10: 67413-67436.
Journals System - logo
Scroll to top