Research On Interior Noise Analysis And Active Control Method Of Rail Vehicle

With the rapid development of rail transportation industry, the problems caused by rail vehicle interior noise have become increasingly severe. Rail vehicle interior noise affects passenger comfort severely. Moreover, noise and vibration can result in the early fatigue damage of some parts of rail vehicle, which will reduce the service life of rail vehicles.Therefore, studying the control method of vehicle interior noise has theoretical and practical significance.This paper uses the Danish B&K pulse multi-channel acoustic measurement system.Measuring points is arranged in rail vehicle during normal operation, to collect rail vehicle interior noise under various operating conditions, and analysis A-weighted sound pressure level and 1/3 octave spectrum. Results show that rail vehicle interior noise concentrated in the 0~500Hz low-frequency range. Conventional passive noise control method has good suppression effect on high-frequency noise, but cannot effectively control low-frequency noise. Thus, in order to control the low and medium frequency noise in the interior rail vehicles, this paper adopts active noise control method based on the least mean square(LMS) algorithm.Wheel-rail noise(rolling noise, impulsive noise and squealing noise) is the main part of rail vehicle interior noise. As the traditional LMS algorithm convergence performance will deteriorate when containing impulsive noise, thus influences control effect. Therefore,this paper proposes an improved median LMS(Median-LMS, MLMS) algorithm, the two algorithms simulation control results show that MLMS algorithm is superior to the traditional LMS algorithm both in steady-state error and appropriate step size scope.MLMS algorithm is more effective for controlling rail vehicle interior low and medium frequency noise.As the step size value of MLMS algorithm is constant, existing inherent defects of unable to balance convergence speed and steady-state error, this paper adopts variable step size LMS algorithm to active control rail vehicle interior noise. Simulation results show that variable step size LMS algorithm is better than traditional fixed step size LMSalgorithm in terms of convergence speed and steady-state error. Variable step size LMS algorithm is an effective active control method for rail vehicle interior noise.