Abstract
A novel auto design method of acoustic filter based on genetic programming (GP) is proposed in this paper. Unlike the model-based auto optimization method by genetic algorithms that optimize acoustic filters only in the parameter domain, the proposed method can optimizes the acoustic filter in both the structure region and the parameter region simultaneously thanks to its tree representation of individuals. In the proposed method, the widely used acoustic components have been equivalent to the basic elements in the topology. The acoustic filter individuals in GP are composed of these elements. Transfer matrix method is employed to calculate the transmission loss of the acoustic filter individuals. By a certain number of generations, the GP finds the individuals with good fitness value. The feasibility of the method is validated by two numerical experiments. The first case study is to validate the searching ability of the method. The result shows that the proposed method has excellent ability to search the optimal solution with transmission loss curve close to the objective transmission loss curve. The second experiment is based on a typical automobile muffler design strategies that requires a high noise reduction magnitude at two specified frequency band and a certain noise reduction magnitude at the whole frequency band, the evolution result meets the design requirements well. The results of these two numerical experiments demonstrate that the proposed method has excellent searching ability and is feasible in the auto design of acoustic filter.
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Acknowledgements
This project is supported by Applied Basic Research Project of Wuhan (Grant No. 2016010101010027), Independent Innovation Foundation of Wuhan University of Technology (Grant No. 172104001).
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Appendix
Appendix
Appendix and supplement both mean material added at the end of a book. An appendix gives useful additional information, but even without it the rest of the book is complete: In the appendix are forty detailed charts. A supplement, bound in the book or published separately, is given for comparison, as an enhancement, to provide corrections, to present later information, and the like: A yearly supplement is issue.
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Zhou, Q., Wu, C., Zhao, W., Hua, W., Liu, L. (2018). A Novel Auto Design Method of Acoustic Filter Based on Genetic Programming. In: Tan, J., Gao, F., Xiang, C. (eds) Advances in Mechanical Design. ICMD 2017. Mechanisms and Machine Science, vol 55. Springer, Singapore. https://doi.org/10.1007/978-981-10-6553-8_45
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