Vector analysis of transformer tank vibration

Kornatowski, E.

doi:10.1109/imitel.2018.8370475

Cited by 1 publication

(2 citation statements)

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“…Another noise source identification technology that combines the far-field beamforming method with the near-site acoustic holography can be applied to the transformer for a higher resolution [6]. The application of direct acoustic intensity measurements to localize noise on 16 MVA and 75 MVA transformers is explained in [7] and [8], respectively. This study pointed out the possibility of the beamforming met hod application for localizing low-frequency transformer sound.…”

Section: Introductionmentioning

confidence: 99%

“…The motivation for the work is to develop an easily applicable and accurate method with high resolution at low frequencies at which the transformer operates. A simple application of the method is achieved with only one microphone and the possibility of measurement automatization without requiring measurements at very short distances from the surface, as in [6][7][8]. Sound localization accuracy is achieved using an unconventional finite-focus method, and increased resolution is achieved using an adaptive beamformer, thus avoiding the conventional acoustic camera problems [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

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Application of adaptive finite focus beamforming method for localization of low-frequency transformer sound

Petrović,

Petošić,

Župan

2024

joe

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In this paper, the developed adaptive linearly constrained minimum variance finite focus beamforming method is used to increase the accuracy and resolution of low-frequency transformer sound source localization. In the first step, simulations on virtual arrays are conducted to define the array size and compare the influence of three different beamforming algorithms on sound localization accuracy and resolution. In the second step, measurements of the regulating transformer as a noise source are conducted in the semi-anechoic chamber. A large rectangular microphone array, with 90 microphone positions spaced 0.44 meters apart, is used for that purpose. The developed algorithm is compared with infinite and finite focus beamforming for the localization of total noise and noise at specific noise harmonics.

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Section: Introductionmentioning

confidence: 99%