Acoustic source location using a microphone array

2003 ◽  
Vol 113 (6) ◽  
pp. 2957
Author(s):  
Pi Sheng Chang
Keyword(s):  
Microphone Array ◽  
Source Location ◽  
Acoustic Source

scholarly journals An Acoustic Source Localization Method Using a Drone-Mounted Phased Microphone Array

Drones ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 75
Author(s):  
Yeong-Ju Go ◽  
Jong-Soo Choi
Keyword(s):  
Signal To Noise Ratio ◽  
Microphone Array ◽  
Direction Of Arrival ◽  
Source Location ◽  
Correlated Noise ◽  
Acoustic Source ◽  
Body Frame ◽  
Error Performance ◽  
Mems Microphone ◽  
Acoustic Sources

Currently, the detection of targets using drone-mounted imaging equipment is a very useful technique and is being utilized in many areas. In this study, we focus on acoustic signal detection with a drone detecting targets where sounds occur, unlike image-based detection. We implement a system in which a drone detects acoustic sources above the ground by applying a phase difference microphone array technique. Localization methods of acoustic sources are based on beamforming methods. The background and self-induced noise that is generated when a drone flies reduces the signal-to-noise ratio for detecting acoustic signals of interest, making it difficult to analyze signal characteristics. Furthermore, the strongly correlated noise, generated when a propeller rotates, acts as a factor that degrades the noise source direction of arrival estimation performance of the beamforming method. Spectral reduction methods have been effective in reducing noise by adjusting to specific frequencies in acoustically very harsh situations where drones are always exposed to their own noise. Since the direction of arrival of acoustic sources estimated from the beamforming method is based on the drone’s body frame coordinate system, we implement a method to estimate acoustic sources above the ground by fusing flight information output from the drone’s flight navigation system. The proposed method for estimating acoustic sources above the ground is experimentally validated by a drone equipped with a 32-channel time-synchronized MEMS microphone array. Additionally, the verification of the sound source location detection method was limited to the explosion sound generated from the fireworks. We confirm that the acoustic source location can be detected with an error performance of approximately 10 degrees of azimuth and elevation at the ground distance of about 150 m between the drone and the explosion location.

scholarly journals Rotating equipment fault noise location based on adaptive beamforming algorithm

2021 ◽  
Vol 2113 (1) ◽  
pp. 012042
Author(s):  
Yongshao Xu ◽  
Bingzheng Liu ◽  
Haotian Shang ◽  
Mingduo Wang
Keyword(s):  
Microphone Array ◽  
State Parameter ◽  
Noise Signal ◽  
Source Location ◽  
Adaptive Beamforming ◽  
Rotating Machinery ◽  
Acoustic Sensor ◽  
Unsteady State ◽  
Beamforming Algorithm ◽  
Fault Source

Abstract Rotating machinery often produces continuous impact during operation due to the change of load and speed, which shows the characteristics of unsteady state and time-varying. Its working state can not be comprehensively judged by a single vibration state parameter. Therefore, this paper proposes to use acoustic sensors to collect the fault noise signal of rotating machinery, and use the whole column of sensors to detect the fault noise signal. Based on the microphone array, this paper studies the adaptive beamforming algorithm (MVDR) to locate the fault source of rotating machinery in space. The effect of fault source location is verified by simulation and equipment measurement experiments. The acoustic sensor does not in contact with the equipment, which will not damage the generator set, but also provide more effective information for fault source location and fault diagnosis and analysis.

Algorithms for Acoustic Source Orientation Based on Microphone Array in Robot Audition

2013 ◽  
Vol 347-350 ◽  
pp. 922-926
Author(s):  
Ming Wang ◽  
Jian Hui Chen ◽  
Guang Long Wang ◽  
Feng Qi Gao ◽  
Ji Chen Li ◽  
...  
Keyword(s):  
Indoor Environment ◽  
Microphone Array ◽  
Time Difference ◽  
Acoustic Source ◽  
Time Difference Of Arrival ◽  
Orientation Process ◽  
Robot Audition ◽  
Three Stages ◽  
Source Orientation

Acoustic source orientation is an important feature in robot audition. This paper applied a spatial cone six-element (SCSE) microphone array and combined with the time difference of arrival (TDOA) between pairs of spatial separated microphones to estimate acoustic source orientation. Simulate three stages of the acoustic orientation process in a real indoor environment, and results show that the algorithm is simple and effective, reducing the amount of calculation, having anti-noise and reverberation ability to meet the requirements of orientation accuracy.

Acoustic source localization using drone-embedded microphone array

2019 ◽  
Vol 146 (4) ◽  
pp. 3058-3059
Author(s):  
Mateusz Guzik ◽  
Konrad Kowalczyk ◽  
Szymon Woźniak ◽  
Mieszko Fraś ◽  
Klara Juros ◽  
...  
Keyword(s):  
Source Localization ◽  
Microphone Array ◽  
Acoustic Source ◽  
Acoustic Source Localization
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