车轮多边形磨耗统计规律及关键影响因素分析

针对列车车轮多边形磨耗问题广泛存在于轨道交通运输领域,会导致车辆/轨道系统产生高频的振动冲击,严重影响车辆和轨道系统零部件的使用寿命,危及行车安全这一问题,调查了大量车轮的多边形磨耗情况并进行统计分析,掌握了高速列车车轮多边形磨耗问题的现状和特点。以18～20阶多边形磨耗车辆为例,通过理论研究和试验分析(试验分析包括车辆系统振动特性测试和转向架模态特性测试),对车轮多边形磨耗的根本原因及诱导因素进行研究。研究发现,轮轨系统在580 Hz频率附近存在固有模态是导致车辆发生18～20阶多边形磨耗的根本原因,轮轨表面的各种不平顺能激发或者加剧轮轨系统在580 Hz频率附近的模态共振,从而诱发车轮多边形磨耗的产生。该结果可为高速列车车轮多边形磨耗问题的防止和进一步研究提供参考。     

Relations between asphaltene content,viscosity reduction rate of heavy oil and ultrasonic parameters

Ultrasonic treatment could decrease the viscosity of heavy oil and previous study on had focused on one heavy oil sample and involved less on the influence of asphaltene content. This study examined the effect of asphaltene content on viscosity reduction rate by ultrasonication. A comparison on samples with various asphaltene content and vibration parameter was made. The results showed that the optimal vibration frequency might decrease as the asphaltene content increased, whereas the optimal vibration intensity and the optimal treatment time were suggested to be enlarged. A semi-quantitative correlation was matched, which helped for numerical simulation about ultrasonic treatment.     

基于改进关联规则算法的警情数据分析

针对传统Apriori算法挖掘警情数据的缺点，提出一种改进的Apriori算法。该算法首先在关联规则发现阶段引入权值参数，设计支持度阈值函数，以挖掘不常发生的重大案情发生规律；然后提出一种压缩矩阵优化算法，将数据压缩存储在只有0或1的矩阵中，并用2个数组来记录矩阵中每一行及每一列1的总数，可多次压缩矩阵，提升挖掘效率；最后将改进的算法用于实际的警情数据挖掘分析，给出关联规则挖掘结果。实验表明，改进算法不仅执行效率较传统算法有所提升，且针对警情数据的挖掘结果准确性也有所提高。     

孤网模式下水轮机调节系统参数敏感性分析

鉴于参数敏感性分析是水轮机调节系统稳定性研究的重要内容,以XLD电站中某机组的孤网运行模式为例,基于轨迹灵敏度指标,在机组负载扰动和参数摄动条件下研究了系统主要变量对参数变化的敏感程度。结果表明,孤网模式下不同参数变化对不同变量的影响不同,系统变量对发电机参数的敏感性要大于对随动系统参数的敏感性。     

Disturbance observer-based adaptive boundary iterative learning control for a rigid-flexible manipulator with input backlash and endpoint constraint

In this article, an observer-based adaptive boundary iterative learning control law is developed for a class of two-link rigid-flexible manipulator with input backlash, the unknown external disturbance, and the endpoint constraint. To tackle the backlash nonlinearities and ensure the vibration suppression, the disturbance observers based upon the iterative learning conception are considered in the adaptive boundary control design. A barrier Lyapunov function is incorporated with boundary control law to restrict the endpoint state. Based on the defined barrier composite energy function, the tracking angle error convergence of the rigid part is guaranteed, and the vibrations of the flexible part are suppressed through the rigorous analysis. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed control.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

A stiffness parameter and truncation error criterion for adaptive path following in structural mechanics

We explore a truncation error criterion to steer adaptive step length refinement and coarsening in incremental-iterative path following procedures, applied to problems in large-deformation structural mechanics. Elaborating on ideas proposed by Bergan and collaborators in the 1970s, we first describe an easily computable scalar stiffness parameter whose sign and rate of change provide reliable information on the local behavior and complexity of the equilibrium path. We then derive a simple scaling law that adaptively adjusts the length of the next step based on the rate of change of the stiffness parameter at previous points on the path. We show that this scaling is equivalent to keeping a local truncation error constant in each step. We demonstrate with numerical examples that our adaptive method follows a path with a significantly reduced number of points compared to an analysis with uniform step length of the same fidelity level. A comparison with Abaqus illustrates that the truncation error criterion effectively concentrates points around the smallest-scale features of the path, which is generally not possible with automatic incrementation solely based on local convergence properties.     

宽带数字接收机IQ不平衡估计与自适应补偿算法

针对宽带调制解调技术中广泛存在的IQ不平衡问题,在IQ不平衡模型及补偿原理的分析基础上提出了一种宽带数字接收机IQ不平衡估计与自适应补偿算法。首先利用解调数据对IQ不平衡参数进行实时估计,然后利用估计参数对接收信号进行自适应补偿。实验结果表明,所提算法可以有效解决宽带调制解调系统中普遍存在的IQ不平衡问题,提升系统误码性能。     

Estimating epidemic coupling between populations from the time to invasion

Identifying the mechanisms by which diseases spread among populations is important for understanding and forecasting patterns of epidemics and pandemics. Estimating transmission coupling among populations is challenging because transmission events are difficult to observe in practice, and connectivity among populations is often obscured by local disease dynamics. We consider the common situation in which an epidemic is seeded in one population and later spreads to a second population. We present a method for estimating transmission coupling between the two populations, assuming they can be modelled as susceptible–infected–removed (SIR) systems. We show that the strength of coupling between the two populations can be estimated from the time taken for the disease to invade the second population. Confidence in the estimate is low if only a single invasion event has been observed, but is substantially improved if numerous independent invasion events are observed. Our analysis of this simplest, idealized scenario represents a first step toward developing and verifying methods for estimating epidemic coupling among populations in an ever-more-connected global human population.     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.