Modeling and Optimization of Two-Chamber Muffler by Genetic Algorithm

Abstract

In this study, Taguchi design method is used to optimize the acoustic performance of two-chamber muffler. The excellent parameter combination for high signal to noise ratio (S/N) of transmission loss (TL) is obtained by the range analysis, and influence sequence of four parameters on TL is determined. TL is evaluated by a COMSOL software based on the finite element method. Further, by the modification on the radius of hole in the baffle, a revised parameter combination for better S/N is found. Finally, the stepwise regression method is used to decide a statistically significant model with a high correlation coefficient. A potential muffler is obtained by the use of genetic algorithm and has high S/N ratio of 27.097 and average value of 33.21 dB for TL in a frequency range from 10 Hz to 1400 Hz.