轴向运动屈曲梁非线性振动研究

为解决屈曲梁在不同的激励条件下产生共振问题,基于哈密顿原理建立屈曲梁的振动模型以及非线性偏微分振动方程和边界条件,通过数值模拟分析了屈曲梁在相平面的动态特性.采用多模态伽辽金离散法预测静态弯曲参数,通过局部分析获得某一个弯曲附近处的非线性近似响应,并得出有效的非线性表达式和频率响应曲线.     

A fuzzy model for predicting burns in surface grinding of steel

Existing analytical thermal models for predicting surface burns due to grinding have limited use because of their reliance on parameters that are not readily obtainable in practice. This paper presents a practical and consistent fuzzy rule-based model for estimating the grinding conditions at which “burn limits” occur. The model consists of 37 absolute and eight relative rules. It has a wide range of applications over many types of steels, Alundum wheels, and grinding conditions. It is also simple to implement, from a rule-chart mode to an intelligent on-line adaptive control mode.     

Design of a robust observer‐based memoryless H∞ control for internet congestion

This work is concerned with the transmission control protocol(TCP)‐based active queue management for alleviating Internet congestion. To achieve the objective, a novel robust observer‐based H_∞ control scheme is proposed to stabilize the data queue length of the router to a given target. The robust observer is advocated to reconstruct a substitution state of the TCP window size under uncertain Internet environments, wherein the TCP window size is almost impossible to be explicitly measured in practise. Meanwhile, a memoryless H_∞ controller is employed to guarantee the system asymptotical stability and further enhance the robustness. With the assistance of a unique nonlinear decoupling method, a feasible controller design method is presented in terms of linear matrix inequality. Compared with the existing literatures, the proposed control principle is more practical, and it can be conveniently implemented into the Internet routers while introduces less computational burden. Finally, the proposed result is embedded into Network Simulator 2 and compared with the other schemes in the literature. Numerical experiments illustrate the effectiveness of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

Mining fuzzy temporal association rules by item lifespans

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach.     

Smooth trajectory planning for a parallel manipulator with joint friction and jerk constraints

In order to achieve better tracking accuracy effectively, a new smooth and near time-optimal trajectory planning approach is proposed for a parallel manipulator subject to kinematic and dynamic constraints. The complete dynamic model is constructed with consideration of all joint frictions. The presented planning problem can be solved efficiently by formulating a new limitation curve for dynamic constraints and a reduced form for jerk constraints. The motion trajectory is planned with quartic and quintic polynomial splines in Cartesian space and septuple polynomial splines in joint space. Experimental results show that smaller tracking error can be obtained. The developed method can be applied to any robots with analytical inverse kinematic and dynamic solutions.     

Sensitivity analysis for biometric systems: A methodology based on orthogonal experiment designs

The purpose of this paper is to introduce an effective and structured methodology for carrying out a biometric system sensitivity analysis. The goal of sensitivity analysis is to provide the researcher/developer with insight and understanding of the key factors—algorithmic, subject-based, procedural, image quality, environmental, among others—that affect the matching performance of the biometric system under study. This proposed methodology consists of two steps: (1) the design and execution of orthogonal fractional factorial experiment designs which allow the scientist to efficiently investigate the effect of a large number of factors—and interactions—simultaneously, and (2) the use of a select set of statistical data analysis graphical procedures which are fine-tuned to unambiguously highlight important factors, important interactions, and locally-optimal settings. We illustrate this methodology by application to a study of VASIR (Video-based Automated System for Iris Recognition)—NIST iris-based biometric system. In particular, we investigated k = 8 algorithmic factors from the VASIR system by constructing a (2^6?1 × 3¹  × 4¹) orthogonal fractional factorial design, generating the corresponding performance data, and applying an appropriate set of analysis graphics to determine the relative importance of the eight factors, the relative importance of the 28 two-term interactions, and the local best settings of the eight algorithms. The results showed that VASIR’s performance was primarily driven by six factors out of the eight, along with four two-term interactions. A virtue of our two-step methodology is that it is systematic and general, and hence may be applied with equal rigor and effectiveness to other biometric systems, such as fingerprints, face, voice, and DNA.     

Improved concentration and separation of particles in a 3D dielectrophoretic chip integrating focusing, aligning and trapping

This article presents a dielectrophoresis (DEP)-based microfluidic device with the three-dimensional (3D) microelectrode configuration for concentrating and separating particles in a continuous throughflow. The 3D electrode structure, where microelectrode array are patterned on both the top and bottom surfaces of the microchannel, is composed of three units: focusing, aligning and trapping. As particles flowing through the microfluidic channel, they are firstly focused and aligned by the funnel-shaped and parallel electrode array, respectively, before being captured at the trapping unit due to negative DEP force. For a mixture of two particle populations of different sizes or dielectric properties, with a careful selection of suspending medium and applied field, the population exhibits stronger negative DEP manipulated by the microelectrode array and, therefore, separated from the other population which is easily carried away toward the outlet due to hydrodynamic force. The functionality of the proposed microdevice was verified by concentrating different-sized polystyrene (PS) microparticles and yeast cells dynamically flowing in the microchannel. Moreover, separation based on size and dielectric properties was achieved by sorting PS microparticles, and isolating 5 μm PS particles from yeast cells, respectively. The performance of the proposed micro-concentrator and separator was also studied, including the threshold voltage at which particles begin to be trapped, variation of cell-trapping efficiency with respect to the applied voltage and flow rate, and the efficiency of separation experiments. The proposed microdevice has various advantages, including multi-functionality, improved manipulation efficiency and throughput, easy fabrication and operation, etc., which shows a great potential for biological, chemical and medical applications.     

A novel method to construct 3D electrodes at the sidewall of microfluidic channel

We report a simple, low-cost and novel method for constructing three-dimensional (3D) microelectrodes in microfluidic system by utilizing low melting point metal alloy. Three-dimensional electrodes have unique properties in application of cell lysis, electro-osmosis, electroporation and dielectrophoresis. The fabrication process involves conventional photolithography and sputtering techniques to fabricate planar electrodes, positioning bismuth (Bi) alloy microspheres at the sidewall of PDMS channel, plasma bonding and low temperature annealing to improve electrical connection between metal microspheres and planar electrodes. Compared to other fabrication methods for 3D electrodes, the presented one does not require rigorous experimental conditions, cumbersome processes and expensive equipments. Numerical analysis on electric field distribution with different electrode configurations was presented to verify the unique field distribution of arc-shaped electrodes. The application of 3D electrode configuration with high-conductive alloy microspheres was confirmed by particle manipulation based on dielectrophoresis. The proposed technique offers alternatives to construct 3D electrodes from 2D electrodes. More importantly, the simplicity of the fabrication process provides easy ways to fabricate electrodes fast with arc-shaped geometry at the sidewall of microchannel.     

A Comparative study on multiobjective reliable and robust optimization for crashworthiness design of vehicle structure

Design optimization without considering uncertainties of system variables and parameters can be problematic in real life. In order to take into account the effect of uncertainties, reliable and robust design schemes have proven effective, but limited studies have been reported to compare their difference in a multiobjective framework. This paper takes a typical vehicle structure subject to offset frontal crashing scenario as an example to compare reliable and robust designs with their deterministic counterpart. The thicknesses of some key components of vehicle frontal structures were selected as design variables, the vehicle weight and energy absorption as the objectives, deceleration and firewall intrusion as the constraints. The deterministic multiobjective optimization problem was first solved by adopting Design of Experimental (DOE), metamodels and Non-dominated Sorting Genetic Algorithm II (NSGA-II). Take into account the uncertainties, a Monte Carlo Simulation (MCS) is adopted to generate random distributions of the objective and constraint functions for each design. For the reliability-based optimization the desired reliabilities of 90 %, 95 % and 99 % are considered, respectively. For the robustness-based optimization, two different formulation strategies are adopted. The optimization showed that the reliable and robust Pareto fronts are shifted away from their deterministic counterpart due to uncertainties. The different Pareto fronts yielded from the deterministic, reliable and robust designs are compared to provide some quantitative insights into how to apply these different design schemes for resolving uncertainty problems. It is shown that, compared with the baseline design, the optimizations enhance the crashworthiness of vehicle, though more conservative solutions could have been generated from the reliable and robust optimizations.