西方修辞学理论观照下的国际商务信函写作

西方修辞学“以人为本”，在研究和实践中都强调人的作用，以修辞为手段，寻找“最佳”的劝说方法，认为修辞的目的并不是写说者把自己的意志强加于听读者之上，而是进行沟通、合作，达到同一。本文借鉴西方修辞学理论来指导国际商务信函写作，旨在指导写出有效、说服力强的信函，达到有效沟通的目的。     

高速飞行器热结构工作时变模态参数辨识

高速飞行器由于其很高的飞行速度而无可避免地受到气动加热作用的影响,进而引起结构特性的时变。采用理论或有限元方法(FEM)进行数值分析,难以获取反映结构在飞行(工作)状态下的真实模态参数。通过辨识获取高速飞行器热环境下的时变结构模态参数是一项十分具有挑战性的任务。针对此问题,引入参数化时频域的最大似然方法,对气动加热作用下的高速飞行器升力面结构的时变模态参数进行了辨识。通过模拟真实飞行状态的数值算例研究,说明参数化时频域的最大似然方法能够很好地辨识出低信噪比(SNR)情况下的模态频率和模态振型,验证了参数化时频域最大似然方法适用于具有显著时变特征的高速飞行器热结构的时变结构模态参数辨识,可为将来相关的工程研究和应用提供良好的理论支持。     

基于叶尖定时的叶片耦合振动参数辨识与仿真

为了实时掌握叶片振动情况、预防故障发生,目前最常用的非接触振动测量方法是基于单自由度模型的叶尖定时法,但当叶片耦合振动时2个振动峰相隔很近,该方法无法同时识别出其振动参数。采用基于2自由度模型的曲线拟合方法,得到叶片耦合振动2个峰的初始相位等参数,用相位遍历法辨识出叶片的振动阶次和频率。结果表明:采用基于2自由度模型的曲线拟合方法提高了叶片耦合振动参数辨识的精度,辨识了相邻2个峰的振动参数。辨识振动与仿真参数设置基本一致。     

β Cep stars from a spectroscopic point of view

In this review we present the current status of line-profile-variation studies of β Cep stars. Such studies have been performed for 26 bright members of this class of pulsating stars in the past 25 years. We describe all these currently available data and summarize the interpretations based on them in terms of the excited pulsation modes. We emphasize that line-profile variations offer a much more detailed picture of the pulsational behaviour of pulsating stars compared to ground-based photometric data. The latter, however, remain necessary to unravel the often complex frequency pattern and to achieve unambiguous mode identification for multiperiodic β Cep stars and also to derive the pulsational properties of the faint members of the class. We highlight the statistical properties of the sample of 26 stars for which accurate spectroscopic studies are available and point out some future prospects. This revised version was published online in June 2006 with corrections to the Cover Date.     

潜在电路分析中的拓扑模式识别算法研究

在网络树拓扑识别理论的分析方法与算法基础上 ,推导出网络树特定的五种基本拓扑模式识别的工程算法 ,以解决计算机对电路网络树进行自动拓扑识别问题。     

EXPERIMENT RESEARCH ON DYNAMIC LOAD IDENTIFICATION TECHNOLOGY BASED ON GENERALIZED ORTHOGONAL POLYNOMIAL THEORY (GOPT)

Dynamicloadisoneoftheimportantoriginalparametersinstructuraldynamicanalysis.Ithasobviousinfluencestodynamicsdesign,vibrationcontrols,activecontroltechnologyandsoon.Sincel97O,manyresearchitemsinthisfieldhavebeenaccomplishedintheworld-Sometheoriesandexperimentalmethodsofdynamicloadidentificationhadbeencreatedinfrequencydomain[l'2J-Howeverftherearesomedisadvantagesthattheycouldbeadaptedonlytoidenti-fythesteady-stateloadandnottoidentifythetransientload,suchasshockloadwithshortsampling.Forvarious…     

基于CMPSO算法的永磁同步电机转动惯量识别研究

永磁同步电机(PMSM)是一种具有很强非线性的动态系统,在工业驱动应用中发挥着重要作用。实时辨识转动惯量对于高精度PMSM系统控制和稳定性状态监测具有重要意义,但传统转动惯量识别方法精度较低。在传统离散模型参考自适应理论基础之上,用柯西变异粒子群优化(CMPSO)算法代替待辨识参数自适律设计环节,以实现PMSM转动惯量识别。该转动惯量辨识方法充分利用了CMPSO算法的快速高效收敛性,仿真结果和试验结果表明了可行性、正确性和准确性。     

Inverse identification of constitutive parameters of Ti2AlNb intermetallic alloys based on cooperative particle swarm optimization

Ti₂AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.     

A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.     

基于Hilbert-Huang变换的航天器发射段力学环境分析

文章基于Hilbert-Huang变换,对某载人航天器发射过程中整流罩分离期间测量的力学环境参数进行处理分析,利用HHT的基函数自适应性特点,得到振动时间历程信号的时频域Hilbert谱,准确识别出信号主频率及对应时间范围。此应用案例可为地面力学试验条件制定以及运载接口条件确定提供参考。