随机共振在微弱信号检测中的机理研究

It is difficult to implement extraction of weak signals in strong noise background. Although the traditional noise suppression technology can significantly reduce noise level, but the target signal can also be greatly damaged during the detection process. Based on stochastic resonance theory for weak signal detection and combined with the scholars of the existing research results at home and abroad, the project proposes the weak signal detection methods under different models combined with the traditional stochastic resonance, through which trying to solve the problems about utilization of low noise energy into signal energy. The research content includes: adaptive nonlinear coupling system of weak signal detection model; single potential function; tri-stable stochastic resonance system to improve the system performance of weak signal detection and to solve the problems of insufficient traditional bistable system noise utilization; Artificial intelligence algorithms are also introduced into stochastic resonance of nonlinear equation parameters optimization, so that the optimum parameters of the new model can be found; For aperiodic signal detection, more effective detection model is proposed; Finally, the new stochastic resonance models are implemented for the practical engineering data detection. Through this project, the stochastic resonance research of weak signal detection range is extended using different model research. The innovative models and detection methods are proposed by introducing artificial intelligence algorithms, thus improve the signal-to-noise ratio, interference noise suppression to achieve target signal detection.

微弱信号检测在强噪声背景中难以实现信号提取，传统降噪技术虽能够大幅度降低噪声，但目标信号在检测过程中同样也会造成损失。本项目以随机共振微弱信号检测理论为基础，参考国内外广大学者现有的研究成果，结合传统随机共振研究提出不同模型下微弱信号检测，解决噪声能量转化信号能量利用率低问题。具体研究内容有：自适应非线性耦合系统的微弱信号检测模型，单稳势函数，三稳态随机共振系统提升微弱信号检测性能，解决传统双稳态系统噪声利用率不足的问题；人工智能算法引入随机共振非线性方程参数寻优，提出新模型随机共振寻找实验最佳参数；对于非周期信号检测提出更为有效的检测模型；最后将随机共振模型进行实际工程数据检测，通过本项目研究扩展了随机共振微弱信号检测研究范围，创新模型思路与检测方法，引入人工智能算法，提高信噪比，扰抑噪声干扰达到目标信号检测目的。

本项目主要对Levy噪声驱动下的随机共振机理进行了一系列研究。主要包含Levy噪声驱动下的三稳随机共振机理研究与应用，Levy噪声下的耦合非线性系统中的随机共振机理研究以及Levy噪声下的一阶线性系统的微弱信号检测。在三稳系统中，通过引入非对称因子，形成了不同于经典三稳系统的非对称系统，通过改变Levy噪声中的一系列参数探究了不同参数给随机共振现象带来的变化。基于两个系统在耦合因子的作用下形成的非线性耦合系统的性能往往由于单个系统，通过将Levy噪声引入到耦合系统中，分析了其系统的随机共振特性，并验证了系统在工程应用中的有效性。在采用提出的随机共振系统检测微弱信号时，为了获得更好的检测结果，利用自适应遗传算法等对系统的参数进行优化。本项目的研究成果为Levy噪声在随机共振现象产生时参数的选择提供了参考，并为所提系统在实际工程中的应用奠定了基础。