随机共振原理在强噪声背景信号检测中的应用

动态系统中的噪声常被认为是令人讨厌的东西 ,但在特定的非线性系统中 ,噪声的存在事实上能够增强微弱信号的检测能力 ,这种现象就是随机共振 (SR ,stochasticresonance) ,它在物理、工业技术和生物医学领域里具有广泛的应用潜力。给出了利用随机共振原理检测微弱周期信号的基本方法 ,并采用模拟的信号对该方法进行了分析与验证。结果表明 ,该方法简单、稳健、可靠 ,能把信噪比较低的周期信号从强背景噪声中可靠地提取出来 ,将在机械故障诊断领域展示诱人的前景

The Application of Stochastic Resonance Theory for Detecting Weak Signals in Heavy Background Noise

Noise in dynamical systems is usually considered a nuisance. But in certain nonlinear systems, the presence of noise can in fact enhance the detection of weak signal. This phenomenon, called stochastic resonance (SR), may find useful application in physical, technological and biomedical fields. A novel approach to detecting weak periodic signal using stochastic resonance theory is presented. This method is analyzed and validated by simulated signal. The result shows that this method is simple, robust and reliable. The weak sinusoid signal of lower signal to noise ratio can be reliably extracted from loud noise. The detection approach of weak signal based on SR indicates a promising prospect for mechanical fault diagnosis.