Version 1
: Received: 29 May 2024 / Approved: 29 May 2024 / Online: 29 May 2024 (10:32:38 CEST)
How to cite:
Triki, O.; Cherif, P. R. Improving Measurement Accuracy of Sound Pressure in Vibrating Machines Using a Doosan Robot. Preprints2024, 2024051946. https://doi.org/10.20944/preprints202405.1946.v1
Triki, O.; Cherif, P. R. Improving Measurement Accuracy of Sound Pressure in Vibrating Machines Using a Doosan Robot. Preprints 2024, 2024051946. https://doi.org/10.20944/preprints202405.1946.v1
Triki, O.; Cherif, P. R. Improving Measurement Accuracy of Sound Pressure in Vibrating Machines Using a Doosan Robot. Preprints2024, 2024051946. https://doi.org/10.20944/preprints202405.1946.v1
APA Style
Triki, O., & Cherif, P. R. (2024). Improving Measurement Accuracy of Sound Pressure in Vibrating Machines Using a Doosan Robot. Preprints. https://doi.org/10.20944/preprints202405.1946.v1
Chicago/Turabian Style
Triki, O. and Pr. Raef Cherif. 2024 "Improving Measurement Accuracy of Sound Pressure in Vibrating Machines Using a Doosan Robot" Preprints. https://doi.org/10.20944/preprints202405.1946.v1
Abstract
Measuring sound pressure is a complex and tedious task in industrial environments. Classical methods can be costly, inaccurate, and potentially dangerous for workers. Integrating robotics and computer vision into acoustic measurement processes offers an innovative solution to these problems. This paper uses a Doosan Robotic Vision System to investigate an innovative automatic acoustic sound pressure measurement solution. The Doosan robot, equipped with a scanning camera and microphone, captures acoustic data and produces a map of the machine’s acoustic radiation using computer vision algorithms. The measurement technique is accurate, efficient, and safe for workers. It can also be used for continuous monitoring of the industrial acoustic environment. The developed measurement method offers a promising way to automate acoustic measurement, which can be performed faster and with better accuracy to help industries improve their product sound quality and reduce noise levels. The method was compared to analytical predictions. A 3D acoustic mapping was conducted to visualize the spatial distribution of sound sources within the environment. The experimental results show a good correlation with the theory.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
