Optimal Design and Experimental Verification of Low Radiation Noise of Gearbox

Abstract

Abstract Reducing the radiated noise of a gearbox is a difficult problem in aviation, navigation, machinery, and other fields. Structural improvement is the main means of noise reduction for a gearbox, and it is realized primarily through contribution analysis and structure optimization. However, these approaches have certain limitations. In this study, a low-noise design method for a gearbox that combines the two approaches is proposed, and experimental verification is performed. First, a finite element/boundary element model is established using a single-stage herringbone gearbox. Considering the vibration excitation of the gear system, the radiation noise of a single-stage gearbox is predicted based on the modal acoustic transfer vector (MATV) method. Subsequently, the maximum field point of the radiated noise is determined, and the acoustic transfer vector (ATV) analysis and modal acoustic contribution (MAC) analysis are conducted to determine the region that contributes significantly to the radiated noise of the field point. The optimization region is selected through the panel acoustic contribution (PAC) analysis. Next, to reduce the normal speed in the optimization region, topology optimization is performed. According to the topology optimization results, four different noise reduction structures are added to the gearbox, and the low-noise optimization models are established respectively. Finally, by measuring the radiated noise of the gearbox before and after optimization under a given working condition, the validity of the radiated noise prediction method and the low-noise optimization design method are verified by comparing the simulation and experimental data. A comparison of the four optimization models proves that the noise reduction effect can be achieved only by adding a noise reduction structure to the center of the density nephogram.

Keywords

• Radiated noise prediction
• Acoustic contribution analysis
• Topology optimization
• Noise reduction structures
• Experimental verification