【作者】 赵伟；

【导师】 张菊香；

【作者基本信息】 西安电子科技大学 ， 精密仪器及机械， 2008， 硕士

【摘要】 噪声对人体健康的影响已得到了广泛的关注。管道消声器已经被提出来应用于工厂、办公室等地方。被动阻尼技术是一种传统的消声技术,但是它只对高频段的噪声有较好的降噪效果,很难对低频段噪声产生作用。有源噪声控制技术正是基于此产生的一种有效的噪声控制方法。有源噪声控制是指人为的产生次级噪声去抵消原有噪声的一种方法。有源噪声控制的基本原理是根据两列同频率、相位差固定的声波会发生相消性干涉。AANC是采用自适应方式完成次级声源控制的有源消声。AANC系统的核心是自适应滤波器和相应的自适应算法。自适应滤波器可以按某种事先设定的准则自动调节其本身的传递函数以达到所需要的输出。设计自适应滤波器时可以不必预先先知道其输入的统计特性,而且,在滤波过程中输入的统计特性如随时间作慢变化它也能自动适应。这些突出的优点使它顺理成章的被有源噪声控制研究所接纳和发展。本文利用神经网络理论对控制器进行了优化设计,在对控制器进行设计时,选择恰当的网络模型及扩散常数,将对函数的逼近能力产生积极的影响。采用RBF(Radial Basis Function)设计的新控制器不仅克服了BP网络设计时需要预设初值的问题,而且进一步提高了一维输入一维输出的训练速度。文中利用RBF网络的任意精度逼近函数的能力对控制器的传递函数进行逼近,对输入样本进行训练从而尽可能达到理想传递函数应有的输出量。针对RBF网络的特点,用RBF网络对控制器的传递函数进行了逼近,可以取的较理想的输出效果,从而达到提高系统鲁棒性的目的。仿真结果表明,利用RBF网络对控制器进行设计,使有源噪声控制系统的鲁棒性得到了明显的改善。更多还原

【Abstract】 Noise impact on human health has been a widespread concern. Pipeline muffler has been put forward to the factory, office, and other places. Passive damping technology is a traditional muffler technology, but only on the high frequency noise is good noise effects, it is very difficult to produce an effect of low frequency noise. Active Noise Control Technology based on this emerged as an effective noise control methods.Active Noise Control refers to the formation of sub-human noise to offset a way of the original noise. Active Noise Control in accordance with the basic principles of the same two frequencies, the acoustic phase will be fixed in cancellation of interference. AANC is accomplished by adaptive secondary source of the active noise control. AANC the heart of the system is adaptive filter and the corresponding adaptive algorithm. Adaptive filter can be set according to certain criteria in advance automatically adjust its own transfer function to achieve the required output. Adaptive filter design can not know in advance the statistical characteristics of the input, but also in the process of filtering the input statistical characteristics such as intercropping slow change at any time it can automatically adapt to. These highlight the advantages of it was logical to accept the Active Noise Control Institute and development.This paper uses the theory of neural network controller has been optimized design, the controller design, select the appropriate network model and the proliferation of constant, function approximation ability will have a positive impact. By RBF (Radial Basis Function), the new controller not only overcome the BP network design needs default initial value problems, and has further enhanced the one-dimensional input output training speed. RBF network, the use of arbitrary precision approximating function of the ability of a controller transfer function approximation, the importation of samples for training to the extent possible, should be the ideal transfer function output. RBF for the characteristics of the network, the controller with RBF network for the transfer function approximation, can take the better output, thereby raising the robustness of the system purposes. The simulation results show that, using the controller RBF network design, the active noise control system robustness have been significantly improved.更多还原