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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Xiaoli Wang
Huaihai institute of technology
Computer Science & IT

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Acoustic Performance of Exhaust Muffler Based Genetic Algorithms and Artificial Neural Network Bing Wang; Xiaoli Wang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 2: June 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i2.931

Abstract

 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.
The Optimization Design of Six-bar Linkage Mechanism Xiaoli Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 7: July 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

At present, multi-bar linkage mechanism is one of the most important directions of mechanical presses’ development. Utilizing the typical multi-linkage drawing mechanism of the plunger slide and compounding its parameters scientifically are a fairly effective way to realize the drawing technology demand. This paper established kinematics mode of the six-bar drawing mechanism by bar-group method, and produced simulated system by Visual Basic, which simulated the actual motion of the mechanism. With the objective function-velocity fluctuation in drawing and drawing depth, using chaos genetic algorithm method, carried out optimization design of the mechanism, and acquired several groups’ data. The optimization results showed that their performance in kinematics was improved greatly and had exceeded the original mechanism. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2863 
Co-Authors Bing Wang