A Noise Reduction Method for Narrowband Active Noise Control System Based on Variable Step Algorithm
A technology of active noise control and variable step size, applied in active noise control, sounding instruments, musical instruments, etc., can solve the problems of restricting the overall performance of the system, difficulty in selecting user parameters, high complexity, etc., to enrich the theoretical system and solve complex problems. High degree of noise, the effect of improving the level of noise reduction
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Embodiment 1
[0053] Embodiment 1: Noise reduction method of narrowband active noise control system based on variable step size algorithm
[0054] like figure 1 As shown, this embodiment provides a noise reduction method for a narrowband active noise control system based on a variable step size algorithm, including the following steps:
[0055] Step 1: Build a narrowband active noise control system based on the VSS-FXLMS algorithm, such as figure 2 As shown, p(n) is the target noise usually contains a finite number of frequency components and has a mean of zero and a variance of The additive noise v of p (n); The ith reference channel frequency value ω is calculated according to the synchronization signal obtained by a non-acoustic sensor (such as a tachometer, etc.) i ; i=1, 2, L, q, q is the number of target noise frequencies; n is the time; S(z) is the secondary channel model, and its coefficient is is the secondary channel estimation model, which can be obtained by offline iden...
Embodiment 2
[0106] Example 2: Theoretical verification under simulated noise
[0107] The target noise includes three frequency components and additive white Gaussian noise, and the normalized frequencies of the three frequency channels used are ω 1 =0.1π, ω 2 = 0.2π and ω 3 =0.3π; the corresponding controller coefficients are respectively a 1 =2.0, b 1 =-1.0, a 2 =1.0, b 2 =-0.5a 3 =0.5, b 3 = 0.1; the secondary channel adopts the FIR model, and its length and cut-off frequency are 21 and 0.4π respectively; the estimated FIR model length of the secondary channel is 31, and its coefficients are obtained by offline identification, and the initial value of the step size is 0.0025.
[0108] First, to verify the dynamic performance analysis results related to the controller coefficient estimation error mean and mean square value, and the step size mean and mean square value in the method of the present invention, the unified user parameter values are ξ=0.9995 and η=5×10 -6 , the add...
Embodiment 3
[0109] Example 3: Experimental verification under actual noise conditions
[0110] The actual noise comes from the noise of the large cutting machine, the speed is 1400rpm, and the normalized frequencies of the noise are 0.0804π, 0.1609π, 0.2414π, 0.3218π and 0.4024π. The real secondary channel is the IIR model (S.M.Kuo and D.R.Morgan, Active Noise Control Systems-Algorithms and DSP Implementation, New York: Wiley, 1996.), assuming that the secondary channel estimation model is the same as the real secondary channel model. The initial value of the step size is 0.001.
[0111] First, assuming that the user parameter η=0.005 is fixed, changing the value of the user parameter ξ, Figure 8 The variation curves of residual noise and step size under three different situations are given. When ξ=0.9994, the system noise reduction is 8.79dB; when ξ=0.9996, the system noise reduction is 10.57dB; when ξ=0.9998 When the noise reduction of the system is 11.51dB. It can be seen that in t...
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