变频器综合实践 第2讲： 变频器在总线控制系统中的综合实践

现场总线是将自动化最底层的现场控制器和现场智能仪表设备等互连的实时控制通讯网络,而变频总线控制系统的特点,就是通过总线可以控制和监控变频器。变频总线控制系统既可联动控制也可单独控制,能充分满足传动系统的可靠性、实时性、实用性的要求,并为实现传动系统的＂无人值班＂运行提供技术准备。     

A method for diagnosis of current faults in antenna arrays using neural networks

A method for detection of faulty elements in antenna arrays from far‐field radiation pattern is presented. The proposed technique finds variation of current from correct values in the faulty elements. A step wise approach is proposed to determine magnitude and phase of current excitation and location of faulty element using neural networks. The results with radial basis function neural network and probabilistic neural network are compared. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

锰红柱石中Mn~（3＋）谱的分析

本文利用锰红柱石的吸收光谱,考虑到锰红柱石中Ｍｎ３＋处于一种Ｃ２ｖ（Ｃ２＇＇）的低对称晶位,采用一简化的强场方案,把单电子晶场矩阵元用自旋允许吸收带代替,克服了多参数的困难．计算出了锰红柱石中处于八面体配位的Ｍｎ３＋的电子能谱,对锰红柱石的分析首次获得了较为理想的理论计算结果,并对Ｍｎ３＋和Ｆｅ３＋谱带的识别提出了新的看法．     

Reconstructing design parameters of a rectangular resonator via peak signal-to-noise ratio and global optimization algorithms

This article proposes an approach for reconstructing physical parameters of a sample in a rectangular resonator during microwave radiation, knowing a priori, its electric field distribution. The inverse problem was solved using two global optimization algorithms and the peak signal-to-noise ratio (PSNR) criterion. First, the Self-regulated Fretwidth Harmony Search algorithm (SFHS) identified suitable resonant frequencies for a given configuration. Next, the unified Particle Swarm Optimization (UPSO) optimized said configuration. Together, they became a maximization strategy of the PSNR through a dual optimization process. Results showed the ability of the approach for estimating the height of each sample block and the resonating frequency of the cavity. This process takes longer to finish as a higher PSNR is demanded (mainly due to the aforementioned dual optimization). Even so, it allows for more similar electric field distributions between both, the direct and inverse problems.     

强磁场对硅锰铸钢于A_1点附近等温珠光体相变的影响

通过开展12 T强磁下硅锰铸钢(50Si_2Mn_3)于A_1点温度附近不同等温时间的热处理试验,并对比强磁场与无磁场条件下等温珠光体相变试验结果,研究了磁场对珠光体转变量及组织形貌的影响。研究表明,对于50Si_2Mn_3在A1点以下较高温度范围内,强磁场可缩短珠光体相变的孕育期,促进硅锰铸钢珠光体转变,使其转变量明显增加;强磁场能够提高珠光体转变临界点,使50Si_2Mn_3在A1点以上等温过程中能够发生珠光体相变。     

Action categorization with modified hidden conditional random field

In this paper, we present a method for action categorization with a modified hidden conditional random field (HCRF). Specifically, effective silhouette-based action features are extracted using motion moments and spectrum of chain code. We formulate a modified HCRF (mHCRF) to have a guaranteed global optimum in the modelling of the temporal action dependencies after the HMM pathing stage. Experimental results on action categorization using this model are compared favorably against several existing model-based methods including GMM, SVM, Logistic Regression, HMM, CRF and HCRF.     

Gröbner basis of the alternating galoisian ideal

This article proposes an efficient and simple algebraic method of computation of a Gröbner basis generating the alternating galoisian ideal of a univariate separable polynomial. We named this method “the descent of the Vandermonde determinants”.     

Identification and quantification of different vapours using a single polymer chemoresistor and the novel dual transient temperature modulation technique

This paper presents a novel signal processing technique for a square wave temperature modulated carbon black/polymer composite sensor. The technique consists of only two mathematical operations: summing the off- and on-transients of the conductance signals, and subtracting the steady-state conductance signal. The technique has been verified through its application to a carbon black/polyvinylpyrrolidone composite chemoresistor. Identification of water, methanol and ethanol vapours was successfully demonstrated using the peak time of the resultant curves. Furthermore, quantification of those vapours was found to be possible using the height of the peak heights, which was linearly proportional to concentration. The technique does not require zero-gas calibration and thus is superior to previously reported techniques.     

Frequency domain regularization of d-dimensional structure tensor-based directional fields

The present work is intended to address two of the major difficulties that can be found when tackling the estimation of the local orientation of the data in a scene, a task which is usually accomplished by means of the computation of the structure tensor-based directional field. On one hand, the orientation information only exists in the non-homogeneous regions of the dataset, while it is zero in the areas where the gradient (i.e. the first-order intensity variation) remains constant. Due to this lack of information, there are many cases in which the overall shape of the represented objects cannot be precisely inferred from the directional field. On the other hand, the orientation estimation is highly dependent on the particular choice of the averaging window used for its computation (since a collection of neighboring gradient vectors is needed to obtain a dominant orientation), typically resulting in vector fields which vary from very irregular (thus yielding a noisy estimation) to very uniform (but at the expense of a loss of angular resolution). The proposed solution to both drawbacks is the regularization of the directional field; this process extends smoothly the previously computed vectors to the whole dataset while preserving the angular information of relevant structures. With this purpose, the paper introduces a suitable mathematical framework and deals with the d-dimensional variational formulation which is derived from it. The proposed formulation is finally translated into the frequency domain in order to obtain an increase of insight on the regularization problem, which can be understood as a low-pass filtering of the directional field. The frequency domain point of view also allows for an efficient implementation of the resulting iterative algorithm. Simulation experiments involving datasets of different dimensionality prove the validity of the theoretical approach.