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Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers

Author

Listed:
  • Iago Búa-Núñez

    (Department of Electronics Technology, Universidad Carlos III de Madrid, Av. Universidad 30, E-28911 Leganés, Madrid, Spain)

  • Julio E. Posada-Román

    (Department of Electronics Technology, Universidad Carlos III de Madrid, Av. Universidad 30, E-28911 Leganés, Madrid, Spain)

  • José A. García-Souto

    (Department of Electronics Technology, Universidad Carlos III de Madrid, Av. Universidad 30, E-28911 Leganés, Madrid, Spain)

Abstract

The detection of acoustic emissions with multiple channels and different kinds of sensors (external ultrasound electronic sensors and internal optical fiber sensors) for monitoring power transformers is presented. The source localization based on the times of arrival was previously studied, comparing different strategies for solving the location equations and the most efficient strategy in terms of computational and complexity costs versus performance was selected for analyzing the error propagation. The errors of the acoustic emission source location (localization process) are evaluated from the errors of the times of arrival (detection process). A hybrid programming architecture is proposed to optimize both stages of detection and location. It is formed by a virtual instrumentation system for the acquisition, detection and noise reduction of multiple acoustic channels and an algorithms-oriented programming system for the implementation of the localization techniques (back-propagation and multiple-source separation algorithms could also be implemented in this system). The communication between both systems is performed by a packet transfer protocol that allows continuous operation (e.g., on-line monitoring) and remote operation (e.g., a local monitoring and a remote analysis and diagnosis). For the first time, delay errors are modeled and error propagation is applied with this error source and localization algorithms. The 1% mean delay error propagation gives an accuracy of 9.5 mm (dispersion) and a maximum offset of 4 mm (<1% in both cases) in the AE source localization process. This increases proportionally for more severe errors (up to 5% reported). In the case of a multi-channel internal fiber-optic detection system, the resulting location error with a delay error of 2% is negligible when selecting the most repeated calculated position. These aim at determining the PD area of activity with a precision of better than 1% (<10 mm in 110 cm).

Suggested Citation

  • Iago Búa-Núñez & Julio E. Posada-Román & José A. García-Souto, 2021. "Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers," Energies, MDPI, vol. 14(23), pages 1-20, November.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7873-:d:686628
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    References listed on IDEAS

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    1. Muhammad Hakirin Roslan & Norhafiz Azis & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Zulkifli Ibrahim & Azalan Ahmad, 2017. "A Simplified Top-Oil Temperature Model for Transformers Based on the Pathway of Energy Transfer Concept and the Thermal-Electrical Analogy," Energies, MDPI, vol. 10(11), pages 1-15, November.
    2. Janvier Sylvestre N’cho & Issouf Fofana, 2020. "Review of Fiber Optic Diagnostic Techniques for Power Transformers," Energies, MDPI, vol. 13(7), pages 1-24, April.
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    Cited by:

    1. Jun Qiang Chan & Wong Jee Keen Raymond & Hazlee Azil Illias & Mohamadariff Othman, 2023. "Partial Discharge Localization Techniques: A Review of Recent Progress," Energies, MDPI, vol. 16(6), pages 1-31, March.
    2. Zhiheng Liu & Yongqing Wang & Jiuxi Cheng & Peijie Han & Zhibin Liu & Zhaoyan Zhang & Xiaoguang Li & Jianquan Yao, 2023. "Dual Sagnac Interferometer Distributed Optical Fiber Localization Method Based on Hilbert–Huang Transform," Energies, MDPI, vol. 16(8), pages 1-13, April.

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