In time series modeling, the residuals are often checked for white noise and normality. In practice, the useful tests are Ljung Box test. Mcleod Li test and Lin Mudholkar test. In this paper, we present a nonparame...In time series modeling, the residuals are often checked for white noise and normality. In practice, the useful tests are Ljung Box test. Mcleod Li test and Lin Mudholkar test. In this paper, we present a nonparametric approach for checking the residuals of time series models. This approach is based on the maximal correlation coefficient ρ 2 * between the residuals and time t . The basic idea is to use the bootstrap to form the null distribution of the statistic ρ 2 * under the null hypothesis H 0:ρ 2 * =0. For calculating ρ 2 * , we proposes a ρ algorithm, analogous to ACE procedure. Power study shows this approach is more powerful than Ljung Box test. Meanwhile, some numerical results and two examples are reported in this paper.展开更多
Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white nois...Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white noise and non-white noise signals. The cross-correlation function of response signal is decomposed into mode functions and residue by EMD method. The identification technique of the modal parameters of single freedom degree is applied to each mode function to obtain natural frequencies, damping ratios and mode shapes. The results of identification of the five-degree freedom linear system demonstrate that the proposed method is effective in identifying the parameters of linear structures under non-stationary ambient excitation.展开更多
We present a model of non-uniform granular gases in one-dimensional case, whose granularity distribution has the fractal characteristic. We have studied the nonequilibrium properties of the system by means of Monte Ca...We present a model of non-uniform granular gases in one-dimensional case, whose granularity distribution has the fractal characteristic. We have studied the nonequilibrium properties of the system by means of Monte Carlo method. When the typical relaxation time T of the Brownian process is greater than the mean collision time To, the energy evolution of the system exponentially decays, with a tendency to achieve a stable asymptotic value, and the system finally reaches a nonequilibrium steady state in which the velocity distribution strongly deviates from the Gaussian one. Three other aspects have also been studied for the steady state： the visualized change of the particle density, the entropy of the system and the correlations in the velocity of particles. And the results of simulations indicate that the system has strong spatial clustering; Furthermore, the influence of the inelasticity and inhomogeneity on dynamic behaviors have also been extensively investigated, especially the dependence of the entropy and the correlations in the velocity of particles on the restitute coefficient e and the fractal dimension D.展开更多
It is generally known that the solutions of deterministic and stochastic differential equations （SDEs） usually grow linearly at such a rate that they may become unbounded after a small lapse of time and may eventual...It is generally known that the solutions of deterministic and stochastic differential equations （SDEs） usually grow linearly at such a rate that they may become unbounded after a small lapse of time and may eventually blow up or explode in finite time. If the drift and diffusion functions are globally Lipschitz, linear growth may still be experienced, as well as a possible blow-up of solutions in finite time. In this paper, a nonlinear scalar delay differential equation with a constant time lag is perturbed by a multiplicative Ito-type time - space white noise to form a stochastic Fokker-Planck delay differential equation. It is established that no explosion is possible in the presence of any intrinsically slow time - space white noise of Ito - type as manifested in the resulting stochastic Fokker- Planck delay differential equation. Time - space white noise has a role to play since the solution of the classical nonlinear equation without it still exhibits explosion.展开更多
为实现基于振动传递比函数的工作模态分析方法能够在任一荷载工况下识别结构模态参数,引入参考响应思路,构建响应功率谱传递比(Power Spectral Density Transmissibility, PSDT)函数。首先利用比例函数的极限定理,揭示PSDT在系统极点处...为实现基于振动传递比函数的工作模态分析方法能够在任一荷载工况下识别结构模态参数,引入参考响应思路,构建响应功率谱传递比(Power Spectral Density Transmissibility, PSDT)函数。首先利用比例函数的极限定理,揭示PSDT在系统极点处的重要特性,进而根据这一特性建立PSDT驱动的峰值法;同时为解决传统传递比方法无法识别结构阻尼的问题,建立基于PSDT驱动的最小二乘复频域法(LSCF),通过参数化拟合思路识别频率、振型和阻尼比,并运用稳定图辅助剔除虚假模态。通过10层剪切型框架结构数值算例,对比研究外部激励性质对PSDT法及传统频域法(峰值法、频域分解法)识别结果的影响。最后,运用PSDT法对环境激励下的人行桥进行工作模态分析,并与传统响应传递比方法及随机子空间法(SSI)结果进行对比。研究结果表明:在同一工况下不同参考响应的PSDT函数在系统极点与外部激励性质无关,且等价于振型比值;PSDT法相比于传统频域法对外部激励具有更为良好的鲁棒性,能够降低识别谐波激励引起的虚假模态的风险;不同于传统响应传递比方法,在任一工况下基于PSDT法能够识别人行桥的包括阻尼比在内的工作模态参数,并产生更为清晰的峰值和稳定图,具有更好的可操作性;该方法识别结果与SSI结果吻合较好,验证了其在任一荷载工况下分析实际桥梁结构工作模态特性的可行性。展开更多
文摘In time series modeling, the residuals are often checked for white noise and normality. In practice, the useful tests are Ljung Box test. Mcleod Li test and Lin Mudholkar test. In this paper, we present a nonparametric approach for checking the residuals of time series models. This approach is based on the maximal correlation coefficient ρ 2 * between the residuals and time t . The basic idea is to use the bootstrap to form the null distribution of the statistic ρ 2 * under the null hypothesis H 0:ρ 2 * =0. For calculating ρ 2 * , we proposes a ρ algorithm, analogous to ACE procedure. Power study shows this approach is more powerful than Ljung Box test. Meanwhile, some numerical results and two examples are reported in this paper.
基金National Natural Science Foundation(No.19972016)for partly supporting this work
文摘Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white noise and non-white noise signals. The cross-correlation function of response signal is decomposed into mode functions and residue by EMD method. The identification technique of the modal parameters of single freedom degree is applied to each mode function to obtain natural frequencies, damping ratios and mode shapes. The results of identification of the five-degree freedom linear system demonstrate that the proposed method is effective in identifying the parameters of linear structures under non-stationary ambient excitation.
基金The project supported by National Natural Science of China under Grant No. 10675408 and Natural Science Foundation of Xianning College under Grant No. KZ0627
文摘We present a model of non-uniform granular gases in one-dimensional case, whose granularity distribution has the fractal characteristic. We have studied the nonequilibrium properties of the system by means of Monte Carlo method. When the typical relaxation time T of the Brownian process is greater than the mean collision time To, the energy evolution of the system exponentially decays, with a tendency to achieve a stable asymptotic value, and the system finally reaches a nonequilibrium steady state in which the velocity distribution strongly deviates from the Gaussian one. Three other aspects have also been studied for the steady state： the visualized change of the particle density, the entropy of the system and the correlations in the velocity of particles. And the results of simulations indicate that the system has strong spatial clustering; Furthermore, the influence of the inelasticity and inhomogeneity on dynamic behaviors have also been extensively investigated, especially the dependence of the entropy and the correlations in the velocity of particles on the restitute coefficient e and the fractal dimension D.
文摘It is generally known that the solutions of deterministic and stochastic differential equations （SDEs） usually grow linearly at such a rate that they may become unbounded after a small lapse of time and may eventually blow up or explode in finite time. If the drift and diffusion functions are globally Lipschitz, linear growth may still be experienced, as well as a possible blow-up of solutions in finite time. In this paper, a nonlinear scalar delay differential equation with a constant time lag is perturbed by a multiplicative Ito-type time - space white noise to form a stochastic Fokker-Planck delay differential equation. It is established that no explosion is possible in the presence of any intrinsically slow time - space white noise of Ito - type as manifested in the resulting stochastic Fokker- Planck delay differential equation. Time - space white noise has a role to play since the solution of the classical nonlinear equation without it still exhibits explosion.
文摘为实现基于振动传递比函数的工作模态分析方法能够在任一荷载工况下识别结构模态参数,引入参考响应思路,构建响应功率谱传递比(Power Spectral Density Transmissibility, PSDT)函数。首先利用比例函数的极限定理,揭示PSDT在系统极点处的重要特性,进而根据这一特性建立PSDT驱动的峰值法;同时为解决传统传递比方法无法识别结构阻尼的问题,建立基于PSDT驱动的最小二乘复频域法(LSCF),通过参数化拟合思路识别频率、振型和阻尼比,并运用稳定图辅助剔除虚假模态。通过10层剪切型框架结构数值算例,对比研究外部激励性质对PSDT法及传统频域法(峰值法、频域分解法)识别结果的影响。最后,运用PSDT法对环境激励下的人行桥进行工作模态分析,并与传统响应传递比方法及随机子空间法(SSI)结果进行对比。研究结果表明:在同一工况下不同参考响应的PSDT函数在系统极点与外部激励性质无关,且等价于振型比值;PSDT法相比于传统频域法对外部激励具有更为良好的鲁棒性,能够降低识别谐波激励引起的虚假模态的风险;不同于传统响应传递比方法,在任一工况下基于PSDT法能够识别人行桥的包括阻尼比在内的工作模态参数,并产生更为清晰的峰值和稳定图,具有更好的可操作性;该方法识别结果与SSI结果吻合较好,验证了其在任一荷载工况下分析实际桥梁结构工作模态特性的可行性。
