scholarly journals A noise source detection system using nearfield acoustical holography

1988 ◽  
Vol 84 (S1) ◽  
pp. S173-S173
Author(s):  
Takuro Hayashi
Keyword(s):  
Noise Source ◽  
Detection System ◽  
Source Detection ◽  
Acoustical Holography ◽  
Nearfield Acoustical Holography

scholarly journals Development of Noise Source Detection System using Array Microphone in Power Plant Equipment

2015 ◽  
Vol 1 (1) ◽  
pp. 99-104
Author(s):  
Seok-Man Sohn ◽  
Dong-Hwan Kim ◽  
Wook-Ryun Lee ◽  
Jae-Raeyang Koo ◽  
Jin-Pyo Hong
Keyword(s):  
Power Plant ◽  
Noise Source ◽  
Detection System ◽  
Source Detection ◽  
Power Plant Equipment ◽  
Plant Equipment

Reconstruction of Noise Source in a Ducted Fan Using a Generalized Nearfield Acoustical Holography

2010 ◽  
Author(s):  
Weiguo Zhang ◽  
S. T. Raveendra ◽  
Moohyung Lee ◽  
J Stuart Bolton
Keyword(s):  
Noise Source ◽  
Ducted Fan ◽  
Acoustical Holography ◽  
Nearfield Acoustical Holography

scholarly journals Increasing The Precision Of Noise Source Detection System using KNN Method

2019 ◽  
pp. 157-168
Author(s):  
Parlin Nando ◽  
Aji Gautama Putrada ◽  
Maman Abdurohman
Keyword(s):  
Nearest Neighbor ◽  
Noise Source ◽  
Detection System ◽  
Sound Intensity ◽  
Learning Method ◽  
Loud Noise ◽  
Source Detection ◽  
K Nearest Neighbor ◽  
Average Accuracy ◽  
Method Noise

This paper proposes Accurate Noise Source Detection System using K-Nearest Neighbor (KNN) Method. Noise or sound intensity is usually measured in decibels (dB). In an educational environment the recommended noise index limit is 55 dB. It means that noise louder than that limit is prohibited. While a loud noise in a campus area occurred, it will be troublesome for the authorities to deal with the matter. This paper proposes a noise source detection system that can locate the position of the noise source. This system used Df analog V2 voice sensor for detecting the loud noise intensity. A microcontroller with WiFi capabilities will allow the system to communicate with an Internet of Things (IoT) platform that can perform a learning method to detect the location of the loud noise source. KNN method is used as the learning method. The result shows a user is able to get a warning related to the noise that occurs in an area at once. The precision position of the noise source can be detected with 70% average accuracy rate

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