Journal
APPLIED ACOUSTICS
Volume 145, Issue -, Pages 27-40Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.apacoust.2018.09.015
Keywords
Axial piston pump; Sound quality; Semantic differential method; Neural network model
Categories
Funding
- National Basic Research Program of China [2014CB046403]
- National Natural Science Foundation of China [51705451]
- China Post-doctoral Science Foundation [2017M611982]
Ask authors/readers for more resources
Sound quality has been an important attribute closely related to products' competitiveness. A neural network model is proposed to predict the sound quality of an axial piston pump based on the objective and subjective sound quality evaluations. Five psychoacoustic metrics of the objective evaluation and six adjective pairs of semantic evaluation method are utilized. The influences of the speed and outlet pressure on the objective and subjective evaluation results are compared. The correlations between the objective and subjective evaluation results are analyzed. The results show that the A-weighted sound pressure levels (AWSPLs) and loudness of the sound take on increasing with the increase of the speed and outlet pressure. There are strong correlations between the AWSPL and loudness and the perceptions of unpleasant-pleasant and like-dislike, while the correlations between the fluctuation strength and the perception of unpleasant-pleasant and like-dislike are moderate, and the correlations between the roughness and sharpness and the perception of unpleasant-pleasant and like-dislike are weak. In addition, the results show that the sound quality model can predict the sound quality of axial piston pumps with good performance. This study lays the foundation for sound quality improvement of hydraulic displacement pumps. (C) 2018 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available