Automated Sound Intensity Measurement Using Doosan Robot: Off-Line Programming for Enhanced Accuracy

Sound intensity measurement is a critical task in numerous industries, particularly in assessing the noise levels generated by vibrating machinery. Existing methods for such measurements often prove cumbersome, time-consuming, and reliant on multiple measurement tools, requiring continuous operator intervention throughout the process. To address this challenge, several studies have explored the integration of collaborative robots to automate these measurements. However, the diversity of programming languages among different robots complicates the implementation process and prolongs setup time. To resolve this issue, our work introduces a unified Python program, leveraging the RoboDK software, to seamlessly adapt our Python code for various robot types. Additionally, we employ offline simulation to ensure smooth operation and validate the effectiveness of our approach through experimental validation. This holistic approach not only streamlines the measurement process but also enhances accuracy and minimizes the need for continuous human intervention.