To find the position of an acoustic source in a room, the relative delay between two (or more) microphone signals for the direct sound must be determined. The generalized cross-correlation method is the most popular technique to do so and is well explained in a landmark paper by Knapp and Carter. In this paper, a new approach is proposed that is based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the microphone signals contains the impulse responses between the source and the microphone signals (and therefore all the information we need for time delay estimation). In experiments, the proposed algorithm performs well and is very accurate.
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http://dx.doi.org/10.1121/1.428310 | DOI Listing |
Sensors (Basel)
January 2025
Department of Industrial Engineering and Mathematical Sciences, Polytechnic University of Marche, 60131 Ancona, Italy.
The acoustic analysis of a moving object, such as in pass-by or fly-over tests, is a very important and demanding issue. These types of analyses make it possible to characterize the machine in quite realistic conditions, but the typical difficulties related to source localization and characterization are usually exacerbated by the need to take into consideration and to compensate for the object movement. In this paper, a technique based on acoustic beamforming is proposed, which is applicable to all those cases where the object under investigation is moving.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
School of Military Medical Psychology, Air Force Medical University, Xi'an 710032, China.
MEMS acoustic sensors are a type of physical quantity sensor based on MEMS manufacturing technology for detecting sound waves. They utilize various sensitive structures such as thin films, cantilever beams, or cilia to collect acoustic energy, and use certain transduction principles to read out the generated strain, thereby obtaining the targeted acoustic signal's information, such as its intensity, direction, and distribution. Due to their advantages in miniaturization, low power consumption, high precision, high consistency, high repeatability, high reliability, and ease of integration, MEMS acoustic sensors are widely applied in many areas, such as consumer electronics, industrial perception, military equipment, and health monitoring.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Aerospace Engineering, University of Bristol, Bristol, BS8 1TR, UK.
This study investigates the aerodynamic and aeroacoustic behavior of propellers operating in ground-effect conditions, with an emphasis on the impact of porous ground surface treatments. The investigation explores the potential of porous materials to reduce propeller noise near the ground, a major barrier to the acceptance and integration of Urban Air Mobility (UAM) systems. Experiments were conducted in an anechoic chamber using an APC [Formula: see text] inch propeller in a pusher configuration.
View Article and Find Full Text PDFAnal Chem
January 2025
International Joint Laboratory for Integrated Circuits Design and Application, Ministry of Education, School of Physics, Zhengzhou University, Zhengzhou 450001, China.
The photoacoustic spectroscopy (PAS) system commonly enhances the efficiency of optical-acoustic-electrical energy conversion by increasing the laser power, optimizing the resonance characteristics of the photoacoustic cell (PAC), and improving the sensitivity of acoustic sensors. However, conventional systems using a single-microphone or a dual-microphone differential setup for point sampling of the photoacoustic signal fail to account for its spatial distribution, leading to a loss of spatial gain. Drawing on microphone array theory derived from sonar technology, this study, for the first time, presents a PAS sensing system based on a four-microphone array, which is applied to detect chloroform gas.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Rangeland Service, Ministry of Agriculture and Food Security, P.O. Box 30, Rishon LeZion 5025001, Israel.
Acoustic monitoring facilitates the detailed study of herbivore grazing by generating a timeline of sound bursts associated with jaw movements (JMs) that perform bite or chew actions. The unclassified stream of JM events was used here in an observational study to explore the notion of "grazing time". Working with shepherded goat herds in a wooded landscape, a horn-based acoustic sensor with a vibration-type microphone was deployed on a volunteer animal along each of 12 foraging routes.
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