Maximum cross-correlated kurtosis-based unsaturated stochastic resonance and its application to bearing fault diagnosis

Considering the random impulses of mechanical noise and the limitations involved while identifying mechanical fault impulse signals via traditional measurement indices of signal-to-noise ratio, which require the characteristic frequency to be known in advance, this study proposes an adaptive unsaturated stochastic resonance method employing maximum cross-correlated kurtosis as the signal detection index. The proposed method combines the features of a cross-correlated coefficient to indicate periodic fault transients and those of spectrum kurtosis to locate these transients in the frequency domain. Actual vibration signals collected from motor and gear bearings subjected to heavy noise are used to demonstrate the effectiveness of the proposed method. Through a coarse tree-based machine learning method, the proposed method is verified to be more suitable for explaining the periodic impulse components of bearing signals, as compared to the ensemble empirical mode decomposition denoising method and unsaturated stochastic resonance using the kurtosis-intercorrelation index.     

Optimal Control of Nonlinear Fractional-Order Systems with Multiple Time-Varying Delays

Journal of Optimization Theory and Applications - This paper considers an optimal control problem governed by nonlinear fractional-order systems with multiple time-varying delays and subject to...     

Research on detection method of multi-frequency weak signal based on stochastic resonance and chaos characteristics of Duffing system

Weak signal detection has been widely used in many fields such as military and national economy. Aiming at the problem that the traditional stochastic resonance (SR) method can’t obtain the signal amplitude when detecting weak signals, the frequency and amplitude of the weak signal are obtained by combining the SR and chaos characteristics of the two-dimensional Duffing system. Firstly, the effects of two-dimensional Duffing system parameters a, b, k, noise intensity D on the Kramers rate and signal-to-noise ratio (SNR) are analyzed under the Gaussian white noise environment. The results show that the damping ratio K can hinder the SR effect of the system to some extent. Secondly, to solve the misjudgment of the state method of the weak signal amplitude in the detection, the Lyapunov exponent is used to assure the threshold's range, and the threshold of the chaotic critical state is found. Finally, the paper gives the processes of frequency and amplitude detection of multiple high-frequency signals, which realizes the effective detection of the frequency and amplitude of multiple high-frequency signals in a Gaussian white noise environment, and successfully applies the method to the accurate detection of boundary voltage amplitude in electrical impedance tomography.     

一类正交空间填充设计的构造

空间填充设计在计算机试验中应用十分广泛,当拟合回归模型时,正交的空间填充设计保证了因子效应估计的独立性.基于广义正交设计,文章给出了构造二阶正交拉丁超立方体设计和列正交设计的方法,新构造的设计不仅满足任意两列之间相互正交,还能保证每一列与任一列元素平方组成的列以及任两列元素相乘组成的列都正交.当某些正交的空间填充设计不存在时,具有较小相关系数的近似正交设计可作为替代设计使用.设计构造的灵活性为计算机试验在实践中的广泛应用提供了必要的支持.     

具有高安全性和有效性的Ⅱ期两阶段临床试验

Ⅱ期临床试验的主要目的是对药物治疗的安全性和有效性进行评估.针对具有高安全性的Ⅱ期两阶段临床试验,给出小样本量下关于安全性和有效性的精确检验方法,并证明最大Ⅰ类错误概率与Ⅱ类错误概率分别在原假设和备择假设的边界处达到.在期望样本量最小原则下,给出最优两阶段设计的构造方法和常用设计表,供实际应用选用.     

Computational method for optimal control of switched systems with input and state constraints

In this paper, we consider an optimal control problem of switched systems with input and state constraints. Since the complexity of such constraint and switching laws, it is difficult to solve the problem using standard optimization techniques. In addition, although conjugate gradient algorithms are very useful for solving nonlinear optimization problem, in practical implementations, the existing Wolfe condition may never be satisfied due to the existence of numerical errors. And the mode insertion technique only leads to suboptimal solutions, due to only certain mode insertions being considered. Thus, based on an improved conjugate gradient algorithm and a discrete filled function method, an improved bi-level algorithm is proposed to solve this optimization problem. Convergence results indicate that the proposed algorithm is globally convergent. Three numerical examples are solved to illustrate the proposed algorithm converges faster and yields a better cost function value than existing bi-level algorithms.     

Effect of clustering on attack vulnerability of interdependent scale-free networks

In order to deeply understand the complex interdependent systems, it is of great concern to take clustering coefficient, which is an important feature of many real-world systems, into account. Previous study mainly focused on the impact of clustering on interdependent networks under random attacks, while we extend the study to the case of the more realistic attacking strategy, targeted attack. A system composed of two interdependent scale-free networks with tunable clustering is provided. The effects of coupling strength and coupling preference on attack vulnerability are explored. Numerical simulation results demonstrate that interdependent links between two networks make the entire system much more fragile to attacks. Also, it is found that clustering significantly increases the vulnerability of interdependent scale-free networks. Moreover, for fully coupled network, disassortative coupling is found to be most vulnerable to random attacks, while the random and assortative coupling have little difference. Additionally, enhancing coupling strength can greatly enhance the fragility of interdependent networks against targeted attacks. These results can not only improve the deep understanding of structural complexity of complex systems, but also provide insights into the guidance of designing resilient infrastructures.     

互逆规划的拓宽和深化及其在结构拓扑优化的应用

本文的工作涉及数学与力学两方面,数学方面:(1) 将数学规划论中新提出的互逆规划,从 s-m 型 (或称为 m-s 型) 发展出 s-s 型和 m-m 型互逆规划 (其中 s 意为单目标,m 意为多目标),从而使互逆规划的定义完备成为 3 种;(2) 从 KKT 条件审视互逆规划的两方面,得到了互逆规划双方求解涉及拟同构和拟同解的 3 个定理,并且予以证明,提供了在求解中对于互逆规划双方在求解中相互借鉴的理论基础;(3) 对一对互逆规划双方皆合理的情况和某一方不合理的情况,皆给出了求解策略和具体解法. 力学方面:(1) 给出结构优化设计模型合理与否的诠释;(2) 在互逆规划对结构拓扑优化的应用中,提出了不合理结构拓扑优化模型的求解策略;(3) 给出了借助 MVCC 模型 (多个柔顺度约束下的体积最小化) 解决 MCVC 模型 (对于给定体积下的多个柔顺度的最小化) 的途径,其中的建模基于 ICM (独立连续映射) 方法. 用 Matlab 编程给出了数值算例. 其中两个数学问题图示了互逆规划的双方关系;其中,结构拓扑优化问题是众多结构拓扑优化中的两个个案;数值结果均支持了本文提出的互逆规划理论.      

Graphene-based mass sensors: Chaotic dynamics analysis using the nonlocal strain gradient model

Nonlinear oscillations of graphene resonators are unavoidable due to enhancing the mass sensitivity of graphene-based mass sensors and the nonlinear behavior of the systems provides the route to chaos. In this paper, the nonlinear and chaotic behavior of the graphene-based mass sensor is investigated. The nano-mechanical sensor includes an electrostatically actuated fully clamped single-graphene sheet as a nano-resonator with an attached concentrated mass. By neglecting the rotary inertia, the equation of motion of the nano- resonator and the attached mass is derived using the nonlocal strain gradient theory of elasticity. The nano-resonator is modeled as a Kirchhoff nano-plate with the von Kármán-type geometric nonlinearity. Applying the Galerkin decomposition method to the partial differential equation of motion leads to the ordinary differential equation. Based on the Melnikov's integral method two analytical criteria are derived which provide necessary conditions that determine the chaotic region of the system. The chaotic dynamics of the system are also scrutinized and verified through plotting the Lyapunov exponent diagram, phase plane trajectories and Poincaré maps.