A broadband MVDR beamforming core for ultrasound imaging

Kidav, Jayaraj U; Sivamangai, N. M.; Pillai, M. P.; Sreejeesh, S. G.

doi:10.1016/j.vlsi.2021.07.006

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…The MVDR algorithm can adaptively minimize the power in the desired direction of the array output and maximize the signal-to-drying ratio. It can greatly improve the resolution and suppress noise in spatial spectral estimation [19][20][21]. This study implemented traditional MVDR beamforming in the frequency domain based on the Acoular library.…”

Section: Mvdrmentioning

confidence: 99%

MVDR-LSTM Distance Estimation Model Based on Diagonal Double Rectangular Array

Zhang

et al. 2023

Sensors

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Deep learning algorithms have the advantages of a powerful time series prediction ability and the real-time processing of massive samples of big data. Herein, a new roller fault distance estimation method is proposed to address the problems of the simple structure and long conveying distance of belt conveyors. In this method, a diagonal double rectangular microphone array is used as the acquisition device, minimum variance distortionless response (MVDR) and long short-term memory network (LSTM) are used as the processing models, and the roller fault distance data are classified to complete the estimation of the idler fault distance. The experimental results showed that this method could achieve high-accuracy fault distance identification in a noisy environment and had better accuracy than the conventional beamforming algorithm (CBF)-LSTM and functional beamforming algorithm (FBF)-LSTM. In addition, this method could also be applied to other industrial testing fields and has a wide range of application prospects.

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Section: Mvdrmentioning

confidence: 99%

MVDR-LSTM Distance Estimation Model Based on Diagonal Double Rectangular Array

Zhang

et al. 2023

Sensors

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“…The sound source localization methods mainly contain beamforming, time differences of arrival, and high-resolution spectral estimation [14]. At present, beamforming algorithm [15][16][17][18] is mostly used in sound source positioning. Nascimento et al [19] proposed a beamforming algorithm based on the least squares problem under non-linear constraints.…”

Section: Introductionmentioning

confidence: 99%

“…FIGURE15 The MUSIC spectrum obtained when the needle-plate electrode was located at the upper right: (a) normalized space spectrum, (b) pseudo colour map…”

mentioning

confidence: 99%

Optimization scheme of partial discharge location of external insulation based on 2‐D multiple signal classification algorithm

Pei

Liu

et al. 2022

IET Science Measure & Tech

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Partial discharge (PD) localization is critical to ensure the safe operation of power equipment. In this paper, an optimization scheme is developed for PD positioning of external insulation equipment. The optimization scheme is based on an eight‐element cross sensor array to receive the ultrasonic signal generated by the PD, and uses the highly accurate 2‐D multiple signal classification (2‐D MUSIC) algorithm to locate the signal. Simulated discharge signal is adopted to test the optimization scheme, and the results show that the positioning error is less than 0.61° when the signal‐to‐noise ratio (SNR) is above −5 dB. In addition, three discharge models are tested at various locations. The average azimuth errors are 0.9°, 1.9°, and 1.55° for the needle‐plate, cone‐plate, and ball‐plate discharge models, respectively, and the average pitch angle errors are 0.75°, 2.1°, and 1.4°, respectively. These show that the needle‐plate model has the best positioning effect. Simulations and experiments are also carried out on the double discharge source scenario, and the error is within 2.2°. A PD location visualization equipment based on the proposed optimization scheme is developed and applied on‐site. The equipment is capable of satisfying the requirements of operation and maintenance.

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