Design of Intelligent Sensing System for Insulation State of Power Transformer Based on Moisture Content

被引:1
|
作者
Zhang, Wenze [1 ]
Guo, Jian [1 ]
机构
[1] Nangjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing, Jiangsu, Peoples R China
来源
2021 24TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2021) | 2021年
关键词
Transformer oil; moisture content; real-time monitor; Capacitive humidity sensor; Finite element;
D O I
10.23919/ICEMS52562.2021.9634286
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The small amount of moisture in transformer oil will reduce its insulation performance and cause major accidents such as insulation breakdown of the transformer. Traditional methods for measuring the content of moisture in transformer oil have disadvantages such as poor real-time performance and low accuracy. This paper proposes a method to indirectly measure the content of moisture in oil by measuring the dielectric constant of the dielectric layer of a capacitive sensor on-line. A capacitive sensor with multi-interdigital electrode structure on the same plane is designed. The influence of plate width and plate spacing on sensitivity is analyzed by finite element method, and the dielectric layer thickness is determined by electric field simulation to determine the optimal structural parameters of the sensor.Use the Pcap02 chip to measure the capacitance, and upload the data to the cloud platform through the microprocessor and narrowband Internet of things technology. Experimental verification shows that the system has high measurement accuracy, good stability, and meets the requirements of on-site operation, providing a reliable basis for transformer maintenance personnel to analyze its operating status.
引用
收藏
页码:1465 / 1469
页数:5
相关论文
共 50 条
  • [21] Investigating a New Approach for Moisture Assessment of Transformer Insulation System
    Zhang, Tao
    Wang, Shuo
    Zhang, Chen
    Abu-Siada, A.
    Li, Linduo
    Han, Jianwei
    Du, Zhengbo
    IEEE ACCESS, 2020, 8 : 81458 - 81467
  • [22] Investigating a new approach for moisture assessment of transformer insulation system
    Zhang, Tao
    Wang, Shuo
    Zhang, Chen
    Abu-Siada, A.
    Li, Linduo
    Han, Jianwei
    Du, Zhengbo
    IEEE Access, 2020, 8 : 81458 - 81467
  • [23] Design and optimization of power current transformer based on FBG sensing
    Ren, N. K.
    Xiong, Y. L.
    Liang, H.
    Meng, S.
    Wu, M. Z.
    AOPC 2015: OPTICAL FIBER SENSORS AND APPLICATIONS, 2015, 9679
  • [24] Moisture Content Assessment of Transformer Solid Insulation using Return Voltage Spectrum
    Cai, Jin-ding
    Zhang, Tao
    ICPADM 2009: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON PROPERTIES AND APPLICATIONS OF DIELECTRIC MATERIALS, VOLS 1-3, 2009, : 257 - 260
  • [25] Assessment of moisture content in power transformer based on traditional techniques and Adaptive neuro-fuzzy interference system
    Sekatane, Permit
    Jordaan, Johan
    Bokoro, Pitshou
    2019 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO 2019), 2019, : 987 - 991
  • [26] Design of an Intelligent Transformer Management System
    Ku, T. T.
    Chen, C. S.
    Lin, C. H.
    Shyu, W. C.
    2014 IEEE PES T&D CONFERENCE AND EXPOSITION, 2014,
  • [27] DYNAMICS MODEL OF MOISTURE IN PAPER INSULATION-TRANSFORMER OIL SYSTEM IN NON-STATIONARY THERMAL MODES OF THE POWER TRANSFORMER
    Vasilevskij, V. V.
    ELECTRICAL ENGINEERING & ELECTROMECHANICS, 2016, (03) : 17 - 20
  • [28] The application of intelligent systems in power transformer design
    Geromel, LH
    Souza, CR
    PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, 2002, : 1504 - 1509
  • [29] The application of intelligent systems in power transformer design
    Geromel, LH
    Souza, CR
    IEEE CCEC 2002: CANADIAN CONFERENCE ON ELECTRCIAL AND COMPUTER ENGINEERING, VOLS 1-3, CONFERENCE PROCEEDINGS, 2002, : 285 - 290
  • [30] Transformer insulation-based vegetable seed oil for power system analysis
    Karthik, M.
    Narmadhai, N.
    BIOMASS CONVERSION AND BIOREFINERY, 2024, : 21565 - 21578