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

Iago Búa-Núñez, Julio E. Posada-Román and José A. García-Souto
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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

Energies, 2021, vol. 14, issue 23, 1-20

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).

Keywords: partial discharges; power transformers; acoustic emission; ultrasonic detection; source location; multichannel instrumentation; optical fiber sensors; denoising; LabVIEW; hybrid programming system (LabVIEW—Matlab) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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