Design of a sound insulation measurement system based on 3D reconstruction technology

Traditional sound intensity scanning methods for measuring sound insulation require manual operation, heavily reliant on the operator’s experience. This makes it challenging to measure complex three-dimensional irregular components, as manual measurements face difficulties in path planning, process control, and result analysis. To overcome these limitations, this paper proposes an improved sound insulation measurement method and system. The intelligent system integrates 3D reconstruction technology and features a specialized point cloud post-processing procedure, including surface fitting, path planning, and coordinate transformation algorithms. Manual operations are replaced by a triaxial sliding platform and a dual-servo gimbal control system with precise control algorithms. A customized clustering algorithm is used for data processing, generating transmission loss curves and visualizing 3D sound intensity distributions on the measured component model. Comparative experiments demonstrate that the proposed system achieves higher positional accuracy, resulting in more stable measurement processes and more precise results compared to traditional methods. The system significantly reduces operator workload during long-term, repeated measurements. It measures irregular 3D surfaces with a maximum error of less than 2 dB compared to international standard methods, validating its feasibility. Furthermore, unlike conventional 2D sound intensity maps, this system calculates and visualizes 3D normal sound intensity distributions using color gradients. This enables direct observation and analysis of weak sound insulation points on the 3D model. The method provides a novel and practical solution for acoustic measurement, offering substantial research value and societal benefits.