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Acoustic Performance of Exhaust Muffler Based Genetic Algorithms and Artificial Neural Network
Acoustic Performance of Exhaust Muffler Based Genetic Algorithms and Artificial Neural Network
Journal from gdlhub / 2016-11-07 09:33:40Oleh : Bing Wang, Xiaoli Wang, Telkomnika
Dibuat : 2013-06-01, dengan 1 file
Keyword : acoustic performance, genetic algorithm, neural network, noise
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/931
Tingkat kebisingan merupakan salah satu indikator penting sebagai tolok ukur kualitas dan kinerja suatu mesin diesel. Kebisingan saluran buang pada mesin diesel dapat diperhitungkan sebagai bagian penting dari peredam suara saluran buang yang terpasang dan merupakan sebuah cara yang efektif untuk mengatur kebisingan gas buang. Paper ini menggunakan program uji ortogonal untuk menentukan parameter struktur peredam dengan masukan tingkat suara yang dihasilkan serta bahan bakar diesel. This article using orthogonal test program for the muffler structure parameters as input to the sound pressure level and diesel fuel each output artificial neural network (BP network) learning sample. Matlab artificial neural network toolbox to complete the training of the network, and better noise performance and fuel consumption rate performance muffler internal structure parameters combination was obtained through genetic algorithm gifted collaborative validation of artificial neural networks and genetic algorithms to optimize application exhaust muffler design is entirely feasible.
Deskripsi Alternatif :The noise level was one of the important indicators as a measure of the quality and performance of the diesel engine.Exhaust noise in diesel engines machine accounted for an important proportion of installed performance exhaust muffler and it was an effective way to control exhaust noise. This article using orthogonal test program for the muffler structure parameters as input to the sound pressure level and diesel fuel each output artificial neural network (BP network) learning sample. Matlab artificial neural network toolbox to complete the training of the network, and better noise performance and fuel consumption rate performance muffler internal structure parameters combination was obtained through genetic algorithm gifted collaborative validation of artificial neural networks and genetic algorithms to optimize application exhaust muffler design is entirely feasible.
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