Analysis of Transformers by Acoustic Emission

Gutten, Miroslav; Kučera, Matej; Cefer, Viktor; Brncal, Peter; Jarina, Roman

doi:10.1109/rtucon51174.2020.9316564

Cited by 2 publications

(2 citation statements)

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“…However, dominant frequency components of transformer noise are often below that frequency. The problem is highlighted in the literature [1], [2], and [3], where an acoustic camera is used for the localization of low-frequency transformer sound. The hotspot localization results show low spatial resolution in the frequency range below 300 Hz.…”

Section: Introductionmentioning

confidence: 99%

“…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]. Compared to the previous research, this work developed a new, improved method that needs only one microphone and combines finite-focus and adaptive beamforming with a known distance from the source to localize low-frequency sound.…”

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%