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Adaptive nonlinear ANC system based on time-domain signal reconstruction technology
Mechanical Systems and Signal Processing ( IF 8.4 ) Pub Date : 2021-05-26 , DOI: 10.1016/j.ymssp.2021.108056
D.P. Yang , D.F. Song , X.H. Zeng , X.L. Wang , X.M. Zhang

When the primary reference signal obtained by the existing Active noise control (ANC) system is not accurate, the control effect of interior noise will be reduced or even fail. Considering the fault-tolerate and robustness of the system, the study proposes an adaptive nonlinear ANC system for interior noise, which contains noise signal decomposition, multi-network reconstruction model and Variable step-size LMS (VSS-LMS) algorithm. The noise signal decomposition method is used to address the non-stationary of the interior noise; Based on the signal components, the multi-network model for the noise signal reconstruction of passenger ear-sides is designed, which is pre-trained by a restricted Boltzmann machine for improved reconstruction accuracy and realize the adaptive extraction of signal features; And then based on the reconstruction signal components, the controller weights of corresponding components are adaptively updated by the VSS-LMS algorithm to control the passenger ear-sides noise. The effectiveness of the proposed adaptive nonlinear ANC system is validated using noise signal sources collected from a vehicle. Compared with the different ANC systems, the proposed system is superior in terms of fault-tolerant and robustness, which can guarantee stable work of the interior noise control.



中文翻译:

基于时域信号重构技术的自适应非线性ANC系统

当现有的主动噪声控制(ANC)系统获得的主要参考信号不准确时,内部噪声的控制效果将降低,甚至失效。考虑到系统的容错性和鲁棒性,本研究提出了一种适用于室内噪声的自适应非线性ANC系统,该系统包含噪声信号分解,多网络重构模型和可变步长LMS(VSS-LMS)算法。噪声信号分解方法用于解决内部噪声的非平稳性。基于信号成分,设计了一种用于人耳噪声信号重构的多网络模型,该模型由受限的玻尔兹曼机进行预训练,以提高重构精度,实现信号特征的自适应提取。然后,基于重构信号分量,通过VSS-LMS算法自适应更新相应分量的控制器权重,以控制乘客耳侧噪声。所提出的自适应非线性ANC系统的有效性通过使用从车辆收集的噪声信号源进行了验证。与不同的ANC系统相比,该系统在容错性和鲁棒性方面具有优越性,可以保证内部噪声控制的稳定工作。

更新日期:2021-05-26
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