Active Noise Control Simulation and Sound Quality Evaluation of Automotive Cooling Fans
The noise of automobile cooling fans is studied.Based on the collected noise sample of the cooling fan,the modeled noise with different tone characteristics is generated.The improved tonality model is used to calculate the tone scheduling,and the subjective evaluation experiments is carried out on the generated modeled noise using the rank scoring method.According to the characteristic that the rotational noise frequency is closely related to the fan speed,the fan speed signal is used to construct the secondary sound source reference signal for active noise control.Finally,the parallel grey neural network model is established and the noise reduction effect is tested.The results show that the tone characteristics of the cooling fan noise is one of the important factors affecting the perceived annoyance,and active noise control can effectively reduce the peak of narrowband noise and thus reduce the tone scheduling.The average relative error of prediction introducing the parallel grey neural network model is only 2.86%,and the annoyance degree after the denoising is improved.
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