信号调制下色噪声间关联的周期调制对单模激光随机共振的影响

在色噪声间的关联程度受时间周期调制的激光系统中,研究噪声受信号调制情况下的随机共振.用线性化近似的方法计算了光强关联函数及信噪比.具体讨论信噪比随噪声强度、噪声自关联时间、信号频率以及时间周期调制频率的变化关系.发现一种新的随机共振：信噪比随时间周期调制频率的变化出现周期振荡型随机共振;发现广义随机共振：信噪比随抽运噪声自关联时间的变化、随信号频率的变化出现随机共振;同时也存在典型的信噪比随噪声强度的变化而出现的随机共振.而信噪比随量子噪声自关联时间的变化表现为抑制. 关键词： 信号调制 时间周期调制 噪声间关联程度 周期振荡型随机共振     

调幅波的单模激光线性模型随机共振

对单模激光增益模型的光强方程加入调幅波，用线性化近似方法计算了以δ函数形式关联的两白噪声驱动下光强的输出功率谱及信噪比. 结果表明，信噪比不但随着抽运噪声和量子噪声强度的变化出现随机共振，而且随着高频载波信号频率和低频调制信号频率的变化也出现了随机共振. 关键词： 抽运噪声 单模激光 随机共振 调幅波     

偏置调幅波调制噪声的单模激光随机共振

采用偏置信号的调幅波调制抽运噪声的单模激光增益模型，用线性化近似方法计算了以e指数形式关联的两色噪声驱动下光强的功率谱及信噪比.结果表明，信噪比随着噪声强度的变化、抽运噪声自关联时间的变化、激光系统参数的变化、载波频率及信号频率的变化均存在随机共振现象. 关键词： 抽运噪声 单模激光 随机共振 调幅波     

色噪声驱动下调幅波的单模激光随机共振

对单模激光增益模型的光强方程加入调幅波，用线性化近似方法计算了以e指数形式关联的两色噪声驱动下光强的输出功率谱及信噪比. 结果表明噪声间互关联时间及互关联程度对随机共振影响很大，信噪比随着载波信号频率ω和调制信号频率Ω的变化也和白噪声的变化曲线有很大不同. 关键词： 色噪声 单模激光 随机共振 调幅波     

噪声交叉关联强度的时间周期调制对线性过阻尼系统的随机共振的影响

针对由加性、乘性噪声和周期信号共同作用的线性过阻尼系统, 在噪声交叉关联强度受到时间周期调制的情况下,利用随机平均法推导了系统响应的信噪比的解析表达式. 研究发现这类系统比噪声间互不相关或噪声交叉关联强度为常数的线性系统具有更丰富的动力学特性, 系统响应的信噪比随交叉关联调制频率的变化出现周期振荡型随机共振, 噪声的交叉关联参数导致随机共振现象的多样化.噪声交叉关联强度的时间周期调制的引入有利于提高对微弱周期信号检测的灵敏度和实现对周期信号的频率估计. 关键词： 随机共振 周期振荡型共振 噪声交叉关联强度 信噪比     

调频信号的单模激光线性模型随机共振

对单模激光增益模型的光强方程加入调频信号,用线性化近似方法计算了以δ函数形式关联的两白噪声驱动下光强的输出功率谱及信噪比. 结果表明,信噪比随抽运噪声和量子噪声强度的变化可出现典型随机共振,受调制信号振幅的影响,信噪比随载波信号频率和调制信号频率的变化出现抑制、单调上升、共振、抑制和共振等几种情况. 关键词： 抽运噪声 单模激光 随机共振 调频信号     

具有周期信号调制噪声的线性模型的随机共振

研究了具有周期信号调制噪声的过阻尼线性系统的随机共振现象.当采用非对称的分段噪声 时，可以得到系统响应的一、二阶矩和信噪比的精确表达式.通过对信噪比的分析, 发现了 “真实的"随机共振和传统的随机共振现象，讨论了乘性噪声的非对称性、自相关时间和噪 声之间的相关强度对信噪比的影响. 关键词： 随机共振 信噪比 周期信号调制噪声 线性模型     

具有色关联的色噪声驱动下单模激光线性模型的随机共振

研究了具有指数形式关联的两色噪声驱动下单模激光线性模型受信号调制后其输出信噪比，发现了随机共振现象.根据计算结果讨论了噪声（即噪声强度、噪声间互关联程度和关联时间）和信号（信号频率和信号振幅）对信噪比的影响. 关键词： 随机共振 噪声关联时间 信噪比     

偏置信号调制下噪声关联的周期调制对单模激光随机共振的影响

在噪声受偏置信号调制的情况下,讨论色噪声之间的关联受时间周期调制所驱动的单模激光系统中的随机共振.用线性化近似的方法计算了输出信噪比.具体讨论输出信噪比随噪声自关联时间、噪声强度和偏置信号的变化关系.发现输出信噪比随抽运噪声强度和自关联时间的变化出现随机共振,而偏置信号会降低随机共振的峰值.实际应用中应控制优选偏置信号强度. 关键词： 偏置信号 色噪声 时间周期调制 噪声间关联程度     

调制与解调用于随机共振的微弱周期信号检测

提出了调制随机共振方法，实现了在大参数条件下从强噪声中检测微弱周期信号.将混于噪声中的较高频率的弱信号经调制变为一差频的低频信号作用于随机共振体系，该低频信号满足绝热近似理论，因而能产生随机共振；再经解调可获得埋于噪声中的原较高频率的弱信号.对埋于噪声中的未知频率，可采用连续改变调制振荡器的频率，以获得一个适当的差频信号输入到随机共振体系，根据输出信号共振谱峰的变化经解调而得待检弱信号的未知频率.该方法应具有较高的应用前景. 关键词： 调制与解调 非线性双稳系统 随机共振 微弱信号检测     

INHOMOGENEOUS FLUCTUATION DISTRIBUTION IN THE OUTPUT OF STOCHASTIC RESONANCE SYSTEMS AND ITS APPLICATION

Inputting a periodic signal mixed with white noise into a bistable system, we find that the fluctuation distribution in the time series of the output is strongly inhomogeneous. In certain phase part fluctuation is very low under the stochastic resonance condition, and consequently, the signal-to-noise ratio (SNR) there is much higher than that of the input. This mechanism can be used to design a nonlinear receiver to extract the signed from noise with SNR three times higher than the largest SNR obtained so far by the optimal linear filter.     

Resonance behavior for an underdamped bistable system driven by square-wave signal and multiplicative noise

The stochastic resonance (SR) behavior for an underdamped bistable system driven by square-wave signal and multiplicative noise is investigated. Under the adiabatic approximation condition, the expression for the system output signal-to-noise ratio (SNR) is obtained. The analysis results show that stochastic multi-resonance phenomenon occurs when the SNR varies with the intensities of the multiplicative and additive noise. SR phenomenon can be observed on the curves of the SNR versus the system bias, versus the amplitude of the dichotomous noise and versus the amplitude of the square-wave signal. Moreover, the SNR varies non-monotonously with the variety of other system parameters.     

Stochastic multi-resonance in an overdamped bistable system with two types of modulation signal

The stochastic resonance (SR) phenomenon in an overdamped bistable system with multiplicative and additive noise is investigated. The signal-to-noise ratio (SNR) is calculated when two types of modulation signal are added to the system. The effects of the intensities, the frequencies and relative phase shift of two types of modulation signal on the SNR are discussed, respectively. Research results show that: (i) the intensities of two types of modulation signal can enhance the maximum in the SNR as a function of the noise intensity, and the frequencies can restrain it; (ii) the additive modulation signal can enhance the maximum in the SNR as a function of the noise intensity in comparison with the multiplicative modulation signal; (iii) when both modulation frequencies are equal, the SNR as a function of the relative phase shift exhibits multiple maxima. The multiple maxima in the SNR identifies the characteristic of the stochastic multi-resonance phenomenon.     

Stochastic resonance characteristic analysis of new potential function under Levy noise and bearing fault detection

Based on the output saturation of classcial bistable stochastic resonance (CBSR), a new type of piecewise nonlinear bistable stochastic resonance (PNBSR) system is constructed. The mean signal-to-noise ratio gain is regarded as an index to measure the stochastic resonance phenomenon. The laws for the resonant output of piecewise nonlinear bistable system governed by l, c, a, b and D of Levy noise are explored under different characteristic index α and symmetry parameter β of Levy noise. The results show that the output of PNBSR system has increased 4?dB by comparing with the output signal-to-noise ratio of CBSR system. And the stochastic resonance phenomenon can be induced by adjusting the piecewise nonlinear system's parameters under any α or β of Levy noise. The interval of the parameters of system which induces good stochastic resonance is roughly the same. And the output signal waveform of resonance is very similar to the input signal waveform, which has some reference value for the signal recovery. Moreover, we can find the good stochastic resonance interval of the system parameters do not change with D of Levy noise under the different noise intensity D of Levy noise. On the basis of this, adjusting the intensity amplification factor D of Levy noise, which induces good stochastic resonance, and the interval does not change with α or β. At last, the piecewise nonlinear bistable system is applied to detect bearing fault signals, which achieves better performance compared with the classical bistable system.     

Stochastic resonance in an asymmetric bistable system driven by multiplicative and additive Gaussian noise and its application in bearing fault detection

The phenomenon of stochastic resonance (SR) in a new asymmetric bistable model is investigated. Firstly, a new asymmetric bistable model with an asymmetric term is proposed based on traditional bistable model and the influence of system parameters on the asymmetric bistable potential function is studied. Secondly, the signal-to-noise ratio (SNR) as the index of evaluating the model are researched. Thirdly, Applying the two-state theory and the adiabatic approximation theory, the analytical expressions of SNR is derived for the asymmetric bistable system driven by a periodic signal, unrelated multiplicative and additive Gaussian noise. Finally, the asymmetric bistable stochastic resonance (ABSR) is applied to the bearing fault detection and compared with classical bistable stochastic resonance (CBSR) and classical tri-stable stochastic resonance (CTSR). The numerical computations results show that:(1) the curve of SNR as a function of the additive Gaussian noise and multiplicative Gaussian noise first increased and then decreased with the different influence of the parameters a, b, r and A; This demonstrates that the phenomenon of SR can be induced by system parameters; (2) by parameter compensation method, the ABSR performs better in bearing fault detection than the CBSR and CTSR with merits of higher output SNR, better anti-noise and frequency response capability.     

二值噪声激励下欠阻尼周期势系统的随机共振

研究了二值噪声和周期信号共同激励下欠阻尼周期势系统的随机共振. 利用随机能量法计算了系统的平均输入能量和平均输出信号的振幅和相位差, 讨论了二值噪声对随机共振的影响. 发现随着噪声强度的增大, 平均输入能量曲线存在一个极小值和一个极大值, 系统出现先抑制后共振的现象; 同时, 系统信噪比曲线随噪声强度的增加出现单峰现象, 说明系统存在随机共振现象.     

光学双稳系统中的随机共振

运用绝热近似理论，研究了由加性噪声和乘性噪声及周期信号驱动的光学双稳系统的随机共振现象. 发现该模型中输出信噪比R～随着加性噪声强度D_a的变化曲线中会出现随机共振现象，而信噪比R～随着乘性噪声强度D_m的变化曲线是单调减小的，信噪比曲线中没有出现随机共振现象. 因此，加性噪声和乘性噪声对输出信噪比的影响是不同的. 关键词： 随机共振 信噪比 乘性噪声 加性噪声     

基于自适应随机共振理论的太赫兹雷达信号检测方法

太赫兹雷达系统在差频信号频谱分析过程中,干扰噪声影响其测距能力.针对上述问题,提出基于自适应随机共振理论的太赫兹雷达信号检测方法,通过对含噪差频信号进行二次采样,利用自适应随机共振系统提取信号,进行尺度恢复完成测距计算.实验数据显示,不同测量距离时,相较于快速傅里叶变换法,输出信噪比的平均增益为9.684 d B,其中测量距离为1000 mm处,差频信号初始频谱值提高了64.1倍,系统信噪比增益为11.761 d B;相较于滤波法,在测量距离为1000 mm处信噪比增益最大,提高了70.56%;输入噪声强度为1—5 V之间时,输出信噪比曲线的曲率相对于滤波法降低了86.5%,其中噪声强度为5 V时信噪比增益最大,为14.018 d B.实验表明太赫兹雷达系统的测距能力大幅提高.     

基于随机共振进行弱信号探测的实验研究

非线性随机共振系统可利用噪声增强微弱信号检测的能力,为强噪声背景下微弱信号的检测开创了新方法.基于随机共振的基本原理设计了硬件电路系统,并将其应用于检测单频和多频微弱信号;通过输入模拟工程实际的带噪信号,采样所得的输出信号的频谱分析结果表明,利用随机共振技术可从强噪声背景下有效地提取出单频和多频弱信号.多频弱信号的有效提取拓展了基于随机共振原理的弱信号检测技术的应用领域,结合数字滤波处理技术有效地消除了低频噪声对信号识别的影响.基于随机共振的弱信号检测技术在信息识别与信息处理方面具有巨大的潜在的应用价值.     

A new method for weak fault feature extraction based on piecewise mixed stochastic resonance

In a continuous bistable system, when the input signal is continuously increased, the output signal tends to be stable and no longer increases. At this time, the weak signal under strong background noise is difficult to be extracted, which means saturation occurs. Aiming at the saturation characteristics of stochastic resonance (SR), the proposed piecewise nonlinear bistable system (PNBSR) model has achieved certain results. However, the potential barrier in the middle of the PNBSR method still completely uses the potential function of classical bistable stochastic resonance (CBSR). There is no fundamental solution to the fourth-order limitation. This paper explores an improved piecewise mixed stochastic resonance (PMSR) potential model. The fourth-order potential function that restricts particle motion in CBSR is improved to a piecewise second-order potential function. This potential function subverts the shape of the traditional potential function and presents a symmetrical double-hook shape. Based on PMSR model, this paper uses particle swarm optimization (PSO) to select system parameters and elaborates the characteristics of the potential function curve in detail. Under the same conditions, the output signal-to-noise ratio (SNR) curve of the improved system is generally higher than that of the CBSR and PNBSR systems. Experiments on bearings and gears show that the proposed method can accurately extract weak fault features, and the effect is better than the PNBSR method.