Optimization of Noise Cancellation Mufflers and Optimal Placement of Absorption Materials

• Main Authors: Li-Wei Wu, 吳立偉
• Other Authors: Ying-Chun Chang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/22099242565201400593

碩士 === 大同大學 === 機械工程學系(所) === 97 === The thesis combines Neural Network System and Genetic Algorithm with acoustic analysis software SYSNOISE and which uses Boundary Element Method (BEM) to perform the muffler optimum design. The thesis is composed of three parts: (1) The performance of noise cancellation muffler: the tube of muffler is separated into two or more, and converge on one tube to reducing noise. Discussing the influence of variation of dimensions on the performance of noise cancellation muffler; (2) Combining Neural Network System and Genetic Algorithm with acoustic analysis software SYSNOISE to the optimum design of dimension of noise cancellation muffler: using Neural Network System to build network system and combining Genetic Algorithm to search the optimum of dimension and transmission loss(TL) of the muffer; (3) Combining Genetic Algorithm with acoustic analysis software SYSNOISE to the optimum design of noise cancellation muffler: using Genetic Algorithm to layout the distribution of absorptive materials to optimized the performance of the muffle. For the industrial applications, it can save time of design, decrease the production cost, and promote the production competition.