FRF-based damage localization method with noise suppression approach

In this paper a noise-robust damage identification method is presented for localization of structural damage in presence of heavy noise influences. The method works based on Frequency Response Functions (FRFs) of the damaged structure without any prior knowledge of the healthy state. The main innovation of this study starts with convolving FRFs with Gaussian kernel to suppress the noise. Denoised signals are then used to develop shape signals according to the second derivative of the operational mode shapes at frequencies in the half-power bandwidth of the center resonant frequencies. The scheme is followed by normalization of shape signals to create a two-dimensional map indicating the damage pattern. The validation of the method was carried out based on simulated data and experimental measurements. The simulated data polluted with 10 percent random noise considering four different conditions: (i) un-correlated noise with Gaussian distribution (ii) noise with non-Gaussian exponential distribution (iii) noise with non-Gaussian Log-normal distribution and (iv) correlated colored noise. The robustness of the method was examined with respect to the damage severity with various damage conditions. Finally, damage detection experiments of a fixed–fixed steel beam are presented to illustrate the feasibility and effectiveness of the proposed method. According to the numerical and experimental investigations, it was demonstrated that the proposed approach presents satisfactory damage indices both in single and multiple damage states in presence of high level noise. Hence, the method can overcome the problems of output measurement noise and deliver encouraging results on damage localization.     

非高斯环境下的深度学习脉冲信号去噪与重构*

侧扫声呐进行沉底小目标探测时,底混响是主要背景干扰。底混响通常是一种非平稳、非高斯的带限噪声,它使得白噪声条件下的滤波器性能受到限制。在混响背景下常利用自回归模型对接收信号进预行白化处理,但对于实际侧扫声呐应用,白化后直接匹配滤波的处理效果不甚理想。针对此问题,在自回归模型预白化的基础上,提出采用一种次最佳检测与多分辨二分奇异值分解相结合的改进方法。该方法首先对接收信号进行分段处理,利用改进Burg算法估计每段数据自回归模型的系数及阶数;然后构造白化滤波器对分段数据预白化,并对白化后的数据进行多分辨二分奇异值分解;最后应用ostu方法对原始声图和处理后的声图进行目标检测。仿真与实验结果表明,该方法明显提高了信混比,改善了侧扫声呐沉底静态小目标的成图质量,有利于后期实现基于图像的目标自动检测。     

Energy-independent factors influencing noise-induced hearing loss in the chinchilla model.

The effects on hearing and the sensory cell population of four continuous, non-Gaussian noise exposures each having an A-weighted L(eq)=100 dB SPL were compared to the effects of an energy-equivalent Gaussian noise. The non-Gaussian noise conditions were characterized by the statistical metric, kurtosis (beta), computed on the unfiltered, beta(t), and the filtered, beta(f), time-domain signals. The chinchilla (n=58) was used as the animal model. Hearing thresholds were estimated using auditory-evoked potentials (AEP) recorded from the inferior colliculus and sensory cell populations were obtained from surface preparation histology. Despite equivalent exposure energies, the four non-Gaussian conditions produced considerably greater hearing and sensory cell loss than did the Gaussian condition. The magnitude of this excess trauma produced by the non-Gaussian noise was dependent on the frequency content, but not on the average energy content of the impacts which gave the noise its non-Gaussian character. These results indicate that beta(t) is an appropriate index of the increased hazard of exposure to non-Gaussian noises and that beta(f) may be useful in the prediction of the place-specific additional outer hair cell loss produced by non-Gaussian exposures. The results also suggest that energy-based metrics, while necessary for the prediction of noise-induced hearing loss, are not sufficient.     

Multiplicative non-Gaussian noise and additive Gaussian white noise induced transition in a piecewise nonlinear model

We study the transition problems in a piecewise nonlinear model induced by correlated multiplicative non-Gaussian noise and additive Gaussian white noise. Firstly, applying the path integral approach, the unified colored noise approximation, the analytical expression of the steady-state probability density function (SPD) is derived. Then the change regulation of the SPD is analyzed with the change of the strength and relevance of multiplicative noise and additive noise. From numerical computations we obtain some new nonlinear phenomena: the transition can be induced by the cross-correlation strength between noises, the non-Gaussian noise intensity and the Gaussian noise intensity as well as the non-Gaussian noise deviation parameter. This indicates that the effect of the non-Gaussian noise intensity on SPD is the same as that of the Gaussian noise intensity. Moreover, we also find the correlation time of the non-Gaussian noise can not induce the transition.     

非高斯冲激干扰下基于Softplus函数的核自适应滤波算法

针对非高斯环境下一般自适应滤波算法性能严重下降问题,本文提出了一种基于Softplus函数的核分式低次幂自适应滤波算法(kernel fractional lower algorithm based on Softplus function,SP-KFLP),该算法将Softplus函数与核分式低次幂准则相结合,利用输出误差的非线性饱和特性通过随机梯度下降法更新权重.一方面利用Softplus函数的特点在保证了SP-KFLP算法具有良好的抗脉冲干扰性能的同时提高了其收敛速度;另一方面将低次幂误差的倒数作为权重向量更新公式的系数,利用误差突增使得权重向量不更新的方法来抵制冲激噪声,并对其均方收敛性进行了分析.在系统辨识环境下的仿真表明,该算法很好地兼顾了收敛速度和跟踪性能稳定误差的矛盾,在收敛速度和抗脉冲干扰鲁棒性方面优于核最小均方误差算法、核分式低次幂算法和S型核分式低次幂自适应滤波算法.     

Non-Gaussian statistics of soliton timing jitter induced by amplifier noise

Based on first-order perturbation theory of the soliton, the Gordon-Haus timing jitter induced by amplifier noise is found to be non-Gaussian distributed. Both frequency and timing jitter have larger tail probabilities than Gaussian distribution given by the linearized perturbation theory. The timing jitter has a larger discrepancy from Gaussian distribution than does the frequency jitter.     

相位编码光码分多址系统中的非高斯分析方法

随着相位编解码器关键技术的突破,精确分析相位编码光码分多址(OCDMA)系统误码率性能显得十分必要。为了精确分析相位编码光码分多址系统误码率性能,提出了一种基于判决变量的矩母函数和鞍点近似的非高斯近似方法,该方法能够精确考虑多址干扰、散粒噪声、热噪声各自的统计特性和相互间的非加性关系。比较了高斯近似、精确计算和文中所提出方法在分析相位编码系统误码率时的计算精度和复杂度,结果证明该分析方法具有分析精度高、计算复杂度低的优点。     

非高斯噪声对惯性棘轮中粒子负迁移率的影响

利用随机模拟方法研究了惯性棘轮中非高斯噪声对负迁移率的影响. 分别模拟了绝对负迁移率(ANM), 非线性迁移率(NNM) 和负微分迁移率(NDM) 等三种反常输运现象. 计算结果表明: 1) 在不同的参数空间里, 非高斯噪声参数q 能够增强或者削弱ANM, 诱导NNM 和NDM; 2) 当q 较大时, 反常输运现象转化为正常输运; 3) 随着q 逐渐增大, 平均速度- 关联时间特性曲线朝着关联时间较小的方向移动并且其峰值逐渐减小. 关键词： 反常输运 负迁移率 非高斯噪声     

Deviation of 1/f voltage fluctuations from scale-similar Gaussian behavior

Recent measurements on thin metal films suggest a pulse model of resistance fluctuations in which scale similarity and power law spectra are only approximate. We show that such a pulse model is consistent with stationary Gaussian resistance fluctuations. This is to be contrasted with the phenomenological behavior, of fluctuations near phase transitions and in turbulent fluids where the fluctuations are non-Gaussian, but exhibit scale similarity of deep physical origin. We then critically examine other tests of the Gaussian behavior of the fluctuating voltageV(t) across a resistor. These include the relaxation of the conditional mean V(t)¦V(0)=V ₀, and the spectrum ofV ²(t). We consider also the question of time reversal invariance. We further ask under what conditions 1/f noise can be measured through fluctuations of the Johnson noise power with no applied voltage. We emphasize that this possibility, suggested and observed by Voss and Clarke, requires thatV(t) contain a non-Gaussian component.     

Ballistic diffusion induced by non-Gaussian noise

In this letter,we have analyzed the diffusive behavior of a Brownian particle subject to both internal Gaussian thermal and external non-Gaussian noise sources.We discuss two time correlation functions C(t) of the non-Gaussian stochastic process,and find that they depend on the parameter q,indicating the departure of the non-Gaussian noise from Gaussian behavior:for q ≤ 1,C(t) is fitted very well by the first-order exponentially decaying curve and approaches zero in the longtime limit,whereas for q 1,C(t) can be approximated by a second-order exponentially decaying function and converges to a non-zero constant.Due to the properties of C(t),the particle exhibits a normal diffusion for q ≤ 1,while for q 1 the non-Gaussian noise induces a ballistic diffusion,i.e.,the long-time mean square displacement of the free particle reads [x(t)-x(t)]2∝t2.     

Brownian motors: Joint effect of non-Gaussian noise and time asymmetric forcing

Previous works have shown that time asymmetric forcing on the one hand, as well as non-Gaussian noises on the other, can separately enhance the efficiency and current of a Brownian motor. Here, we study the result of subjecting a Brownian motor to both effects simultaneously. Our results have been compared with those obtained for the Gaussian white noise regime in the adiabatic limit. We find that, although the inclusion of the time asymmetry parameter increases the efficiency value up to a certain extent, for the present case this increase is much less appreciable than in the white noise case. We also present a comparative study of the transport coherence in the context of colored noise. Though the efficiency in some cases becomes higher for the non-Gaussian case, the Péclet number is always higher in the Gaussian colored noise case than in the white noise as well as non-Gaussian colored noise cases.     

Effect of the non-gaussianity on the measurement error for the filtered 1/f noise intensity

To study the nature of the 1/f noise phenomenon in conductors, we seek a tool for testing different hypotheses of 1/f noise origin. The method analyzing the noise intensity at the output of a bandpass filter is discussed for the case of non-Gaussian processes. Data on measurement error are presented for the 1/f noise intensity in GaAs films and the Gaussian white noise emulated by a computer. A numerical model of 1/f noise as the superposition of telegraph random processes has been created. This method requires further improvement to check the noise for stationarity. Some ideas of how to do that are proposed. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 42, No. 3, pp. 278–286, March 1999.     

Stochastic properties coupling between of tumor growth with non-Gaussian and Gaussian noise terms

Dynamical behavior of a tumor-growth model with coupling between non-Gaussian and Gaussian noise terms is investigated. The departure from the Gaussian noise can not only reduce the probability of tumor cells in the active state, induce the minimum of the average tumor-cell population to move toward a smaller non-Gaussian noise, but also decrease the mean first-passage time. The increase of white-noise intensity can increase the tumor-cell population and shorten the mean first-passage time, while the coupling strength between noise terms has opposite effects, and the noise correlation time has a very small effect.     

Analysis of noise properties of an optocoupler device

In the paper, localization of a source of random telegraph signal noise (RTS noise) in optocoupler devices of CNY 17 type was defined. The equivalent noise circuit in low frequency noise for these types of optocouplers was proposed.     

Stochastic properties of tumor growth with coupling between non-Gaussian and Gaussian noise terms

Dynamical behavior of tumor-growth model with coupling between non-Gaussian and Gaussian noise terms is investigated. The departure from the Gaussian noise can not only reduce the probability of tumor cells in the active state, induce the minimum of the average tumor-cell population to move toward a smaller non-Gaussian noise, but also decrease the mean first-passage time. The increase of white-noise intensity can increase the tumor-cell population and shorten the mean first-passage time, while the coupling strength between noise terms has opposite effects, and the noise correlation time has a very small effect.     

The study on a stochastic system with non-Gaussian noise and Gaussian colored noise

In this paper, a stochastic system with correlation between non-Gaussian noise and Gaussian colored noise is investigated. We carry out the functional methods to derive the approximate Fokker-Planck equation, and the expressions of stationary probability density function and mean first-passage time are presented. Also we explore the effects of correlation between non-Gaussian and Gaussian noise for the mean first-passage time.     

关联高斯与非高斯噪声激励的FHN神经元系统的稳态分析

本文主要研究了关联乘性非高斯噪声和加性高斯白噪声共同激励的FHN(Fitz Hugh-Nagumo)神经元系统.利用路径积分法和统一色噪声近似,推导出该系统的定态概率密度函数表达式.通过研究发现,乘性噪声强度D、加性噪声强度Q、噪声自关联时间τ以及互关联系数λ均可以诱导系统产生非平衡相变现象,而非高斯参数q却不可以诱导系统产生非平衡相变现象.此外,我们还发现参数D和λ的增大有利于神经元系统从激发态向静息态转换,Q和τ的增大有利于神经元系统从静息态向激发态转换,q的增大会使得神经元系统停留在静息态的概率增加.     

Mean First-Passage Time of an Asymmetric Kinetic Model Driven by Two Different Kinds of Colored Noises

The mean first-passage time （MFPT） of an asymmetric bistable system between multiplicative non-Gaussian noise and additive Gaussian white noise with nonzero cross-correlation time is investigated. Firstly, the non-Markov process is reduced to the Markov process through a path-integral approach; Secondly, the approximate Fokker Planck equation is obtained by applying the unified colored noise approximation and the.Novikov Theorem. The steady-state probability distribution （SPD） is also obtained. The basal functional analysis and simplification are employed to obtain the approximate expressions of MFPT T^±. The effects of the asymmetry parameter β, the non-Gaussian parameter （measures deviation from Gaussian character） r, the noise correlation times τ and τ2, the coupling coefficient A, the intensities D and a of noise on the MFPT are discussed. It is found that the asymmetry parameter β, the non-Gaussian parameter r and the coupling coefficient A can induce phase transition. Moreover, the main findings are that the effect of self-existent parameters （D, α, and τ） of noise and cross-correlation parameters （A, 7-2） between noises on MFPT T^± is different.     

Entropic Resonant Activation and StochasticResonance Driven by Non-Gaussian Noise

The transition rate and stochastic resonance (SR) of a Brownian particle moving in a confined system under the presence of entropic barriers are investigated when the system is driven by non-Gaussian noise. The explicit expressions of the transition rate and the spectral power amplification (SPA) are obtained, respectively. The effects of the parameter q indicating the departure from the Gaussian noise and the correlation timeτ of the non-Gaussian noise on the transition rate and the SPA are discussed. Research results show that: (i) The transition rate as a function of the noise strength exhibits a maximum. This maximum for transition rate identifies the phenomenon of entropic resonant activation (ERA), the parameter q and the noise correlation timeτ weaken the ERA of the system; (ii) The curves of SPA appear a transition from one peak to double-peak, and then to one peak again as the noise correlation timeτ of non-Gaussian noise increases.