Hybrid 3D Sound Intensity and Simulation for Optimizing Acoustic Output of Truck Rear Axles

This study presents a novel methodology for optimizing the acoustic performance of rotating machinery by combining scattered 3D sound intensity data with numerical simulations, focusing on the rear axle of a truck. Using Scan&Paint 3D, sound intensity data is rapidly acquired over a large spatial area with the assistance of a 3D sound intensity probe and infrared stereo camera. The experimental data is then integrated into far-field radiation simulations, enabling detailed analysis of the acoustic behavior and accurate predictions of far-field sound radiation. This hybrid approach offers a significant advantage for assessing complex acoustic sources, allowing for quick and reliable evaluation of noise mitigation solutions. While the current application focuses on the truck's rear axle far-field radiation, the same method can be extended to predict in-cabin sound pressure, providing a versatile solution for many industrial problems.