Optimization of Shunted Loudspeaker for Sound Absorption by Fully Exhaustive and Backtracking Algorithm
Clicks: 207
ID: 269456
2021
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
30.0
/100
207 views
30 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #123 of 187 articles by views in applied sciences
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 187 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The shunted loudspeaker with a negative impedance converter is a physical system with multiple influencing parameters. In this paper, a fully exhaustive backtracking algorithm was used to optimize these parameters, such as moving mass, total stiffness, damping, coil inductance, force factor, circuit resistance, inductance and capacitance, in order to obtain the best sound absorption in a specific frequency range. Taking the maximum average sound absorption coefficient in the range of 100–450 Hz as the objective function, the optimized parameters of the shunted loudspeaker were analyzed. Simulation results indicated that the force factor and moving mass can be sufficiently reduced in comparison with that of a typical four-inch loudspeaker available on the market. For a given loudspeaker from the market as an example, the four optimized parameters of the shunted loudspeaker were given, and the sound absorption coefficient was measured for verification. The measured results were in good agreement with the predicted results, demonstrating the applicability of the algorithm.
| Reference Key |
li2021appliedoptimization
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Zihao Li;Xin Li;Bilong Liu;Li, Zihao;Li, Xin;Liu, Bilong; |
| Journal | applied sciences |
| Year | 2021 |
| DOI |
10.3390/app11125574
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.