中文摘要：

针对强噪声背景下多频微弱信号检测的难题，提出一种基于自适应变尺度频移带通随机共振（Adaptivere．scalingfrequency．shinedband．passstochasticresonance，ARFBSR）降噪的经验模态分解（Empiricalmodedecomposition，EMD）多频微弱信号检测方法。对不同频段的信号进行频率尺度变换处理，使其满足随机共振条件，根据噪声强度自适应地优化系统的参数，进而对每个频段信号分别进行随机共振处理，使得待检信号目标频段得到增强，对各个频段的共振输出进行带通滤波再合成，实现多频微弱信号的增强。对处理后的信号进行EMD分解，得到每个频率的信号分量，实现多频微弱信号的检测。仿真分析和滚动轴承内圈故障诊断实例表明，该方法不仅能够增强信号幅值，同时减少虚假分量，提高EMD算法的精度，有效检测出被噪声淹没的多频微弱信号。

英文摘要：

Aiming at the detection problem of the multi-frequency signal under noise background, a novel method based on empirical mode decomposition（EMD） alter de-noising by adaptive re-scaling frequeucy-shiRed band-pass stochastic resonance is proposed. In this method, different frequency bands of the signal are processed by re-scaling sub-sampling compression to make each frequency band meet the conditions of stochastic resonance. Further parameters are adaptively optimized according to noise intensity and the weak signal frequency components are enhanced through stochastic resonance system. Before the enhanced components of the signal are synthesized, they are processed through band-pass filter only leaving the enhanced sections of the signal, to achieve the enhancement signal. The processed signal is decomposed by EMD into intrinsic mode functions to achieve detection of multi-frequency weak signals. The simulation results show that the proposed method, can enhance the signal amplitude, reduce the false component and improve the accuracy of the EMD algorithm, effectively detect multi-frequency weak signal submerged by noise.