Six-cylinder diesel engine is taken as a sample; the sound quality of the radiated noise varied with loads/speeds is studied so as to improve the radiated noise quality and establish the theoretical foundation for the structure acoustical design. On the basis of studying the objective evaluation of diesel engine radiated noise at home and abroad, five objective evaluation parameters consisting of loudness, sharpness, roughness and fluctuation strength are chosen to describe the objective characteristics of the diesel engine noise; considering the characteristics of the diesel engine noise, the paired comparison was applied in the jury evaluation; the prediction model of noise quality was established through the genetic support vector machines algorithm(GA-SVM), compared with neural network prediction model, the results showed that the GA-SVM prediction model for forecasting the sound quality of engine radiated noise has achieved higher accuracy than the neural network prediction model, which can reflect the non-linear relationship between characteristic parameters and subjection evaluation results accurately.
LIU Hai;ZHANG Junhong;BI Fengrong;LIU Yu;ZHANG Guichang HE Wenyun XU Meng.
Sound Quality Prediction of Diesel Engine Noise Based onSupport Vector Machines Algorithm[J]. Journal of Vibration and Shock, 2013, 32(2): 111-114
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