Acoustic comfort evaluation modeling and improvement test of a forklift based on rank score comparison and multiple linear regression

作者：Zhang, Enlai^*; Zhang, Quanming; Xiao, Jingjing; Hou, Liang; Guo, Tao

来源：APPLIED ACOUSTICS, 2018, 135: 29-36.

DOI：10.1016/j.apacoust.2018.01.026

• Acoustic comfort
• Rank score comparison
• Multiple linear regression
• Forklift
• Improvement test

Aiming at the common problems of the engineering vehicles with high environment noise and poor acoustic comfort, this paper proposes an acoustic comfort subjective evaluation method based on rank score comparison (RSC) and develops a corresponding software system; it provides the solution method of evaluation modeling and improvement measure based on multiple linear regression (MLR). The actual application case of 50 noise samples from forklifts is presented to verify the feasibility and effectiveness of the RSC method. Through the subjective evaluation experiment, calculation of psychoacoustic parameters and data statistical tests, acoustic comfort evaluation model is established based on MLR. Consequently, the most significant parameter and improvement measure of acoustic comfort are obtained by means of sensitivity analysis and noise spectrum analysis. Finally, the improvement test of a target prototype is carried out and results indicate that the acoustic comfort has been improved obviously and the noise decibel level has met the industry standard requirement.

• 出版日期2018-6
• 单位集美大学; 厦门大学