Optimization of pneumatic mufflers hybridized with metal sintered bronze porous material,expansion cone,and extended tube

Abstract

Because of high pressure impulse noise emitted from the outlet of pneumatic equipment, an appropriate noise abatement device installed at the top of a venting outlet is compulsory. However, a given known noise reduction using a bronze-made sintered porous plug at the venting outlet is insufficient. An exploration of advanced noise reducing device is required. In this paper, three kinds of mufflers (Muffler A: with part AA (a bronze-made sintered porous inlet); Muffler B: with part BB (a casing with expansion cones and extended perforated/non-perforated tubes); and Muffler C: part AA (a bronze-made sintered porous inlet) + part BB (a casing with expansion cones and extended perforated/non-perforated tubes)) have been introduced and acoustically analyzed. To assist the optimization of mufflers composing of complicated acoustical mechanism, a finite element method using finite element method (run on COMSOL) together with a simplified objective function model and Genetic Algorithm (GA) is presented. Here, the simplified model of objective function is established by means of Artificial Neural Networks (ANNs). In addition, three kinds of frequencies, including one low frequency (500 Hz) and two high frequencies (3000 Hz, and 5000 Hz), have been chosen as the target frequencies during the muffler C’s optimization process. Consequently, considering a space-constrained situation, an optimally shaped muffler using both parameters D and L is efficiently accomplished within space-constraint situation.

Keywords

Pneumatic bronze-made sintered porous genetic algorithm optimization polynomial neural network model

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