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Development of an MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete

Authors
Song, HominPark, JongwoongPopovics, John S.
Issue Date
Oct-2020
Publisher
IOP PUBLISHING LTD
Keywords
air-coupled; MEMS microphones; rapid wavefield data collection; sparse wavefield reconstruction; alkali-silica reactivity; cracking
Citation
SMART MATERIALS AND STRUCTURES, v.29, no.10
Journal Title
SMART MATERIALS AND STRUCTURES
Volume
29
Number
10
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/85378
DOI
10.1088/1361-665X/ababe5
ISSN
0964-1726
Abstract
Although contactless ultrasonic wavefield imaging shows potential for effective nondestructive inspection of various engineering materials, it has been rarely applied to concrete materials owing to technical challenges including low signal-to-noise ratio (SNR) caused by inherent heterogeneity of concrete. This paper presents development of a multi-channel MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete materials. The developed multi-channel MEMS ultrasonic microphone array system contains eight MEMS ultrasonic microphone elements and a signal conditioning circuit that enables measurements of ultrasonic signals with high SNR. A compressed sensing approach, based on the multiple measurement vector (MMV) concept, is applied to reconstruct a full dense ultrasonic wavefield data from sparsely sampled ultrasonic wavefield data. Experiments are carried out on a laboratory concrete sample to verify the performance of the developed MEMS microphone array system and proposed compressed sensing approach and then large-scale concrete samples to demonstrate practical application. The experimental results demonstrate that the developed MEMS microphone array system provides high-quality (SNR > 20 dB) ultrasonic data collected from concrete elements; furthermore, the proposed compressed sensing approach provides accurate reconstruction of dense wavefield data, as determined by peak signal-to-noise ratio (PSNR), from sparsely measured wavefield data with compression ratios up to 85% and PSNR above 25 dB in data collected form realistic large-scale concrete samples. By combining the MEMS array system and compressed sensing approach, the total ultrasonic data acquisition time needed to produce dense wavefield data can be significantly reduced.
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Song, Homin
Engineering (Department of Civil & Environmental Engineering)
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