中国实型铸造的现状与发展前景

实型（消失模）铸造在我国虽已有３３年历史，但真正获得较快发展的是８０年代末中国铸造协会实型铸造专业委员会成立（当时仅１８家会员单位）后，尤其是近几年发展更为迅速。据不完全统计，现今在我国从事这项新技术研究和应用的约有１１０余家单位，是１９８８年中国铸造协会实型铸造专业委员会成立时的６倍。其中：研究院所和高等院校有１４家，消失模铸造原辅材料和专用设备生产厂点有１５家。１９９７年中国实型（消失模）铸件产量近２５８００ｔ，比１９９５年产量增加１倍（其中９８％是黑色金属铸件），但仅占现有生产能力的１６％；可见，中国消失模铸造的发展前景是十分可观的。     

A novel multi-agent approach to identify faults in line connected three-phase induction motors

Three-phase induction motors (TIMs) are the key elements of electromechanical energy conversion in a variety of productive sectors. Identifying a defect in a running motor, before a failure occurs, can provide greater security in the decision-making processes for machine maintenance, reduced costs and increased machine operation availability. This paper proposes a new approach for identifying faults and improving performance in three-phase induction motors by means of a multi-agent system (MAS) with distinct behavior classifiers. The faults observed are related to faulty bearings, breakages in squirrel-cage rotor bars, and short-circuits between the coils of the stator winding. By analyzing the amplitudes of the current signals in the time domain, experimental results are obtained through the different methods of pattern classification under various sinusoidal power and mechanical load conditions for TIMs. The use of an MAS to classify induction motor faults allows the agents to work in conjunction in order to perform a specific set of tasks and achieve the goals. This technique proved its effectiveness in the evaluated situations with 1 and 2 hp motors, providing an alternative tool to traditional methods to identify bearing faults, broken rotor bars and stator short-circuit faults in TIMs.     

An orthogonal regularized CCA learning algorithm for feature fusion

Canonical correlation analysis (CCA) aims at extracting statistically uncorrelated features via conjugate orthonormalization constraints of the projection directions. However, the formulated directions under conjugate orthonormalization are not reliable when the training samples are few and the covariance matrix has not been exactly estimated. Additionally, this widely pursued property is focused on data representation rather than task discrimination. It is not suitable for classification problems when the samples that belong to different classes do not share the same distribution type. In this paper, an orthogonal regularized CCA (ORCCA) is proposed to avoid the above questions and extract more discriminative features via orthogonal constraints and regularized parameters. Experimental results on both handwritten numerals and face databases demonstrate that our proposed method significantly improves the recognition performance.     

高速板材阶梯槽图形板制作研究

针对采用松下RX板材设计的高速板材阶梯槽图形板的制作进行研究。此板设计有槽底通孔、背钻孔、NPTH孔、整板的PTH阶梯孔、POFV孔。样板层数高,制作工艺复杂,难度大,对准度、阻抗以及可靠性要求高。     

Visual stress, its treatment with spectral filters, and its relationship to visually induced motion sickness

We review the concept of visual stress and its relation to neurological disease. Visual stress can occur from the observation of images with unnatural spatial structure and an excess of contrast energy at spatial frequencies to which the visual system is generally most sensitive. Visual stress can often be reduced using spectral filters, provided the colour is selected with precision to suit each individual. The use of such filters and their effects on reading speed are reviewed. The filters have been shown to benefit patients with a variety of neurological conditions other than reading difficulty, all associated with an increased risk of seizures.     

LCD电极显露的量化、分析与克服

通过提出参量K和重建LCD光路模型来量化和分析液晶显示屏的电极显露 ,成功地解释了有关现象 ,提出相应的解决方法 ,并已获得验证     

张力减径机双电机集中传动方式的比较

认真比较张力减径机双电机集中传动中各种形式齿轮配置的拖动原理,有利于选择最佳传动方案.     

综合值贴近和形贴近的新的统计量的研究

通过对传统模糊聚类分析方法中常用的相似程度统计量—距离系数与相似系数的结合。提出了一种既能考虑样本之间的值贴近程度，又能考虑样本之间的形贴近程度的新的统计量—相似度。并将其应用到实际样本数据的聚类分析中，实践表明将该统计量应用于传统模糊聚类分析中是有效的。     

“同构”模具CAD系统中工艺设计的探讨

从“同构”模具的实际情况出发，探讨了“同构”模具ＣＡＤ 系统中工艺设计部分通用化的可能性，并给出了使得工艺设计部分开发能够顺利进行的五条对策。     

Data mining technique for fast retrieval of similar waveforms in Fusion massive databases

Fusion measurement systems generate similar waveforms for reproducible behavior. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behaviour, i.e. discharges with “similar” waveforms. Here we introduce a new technique for rapid searching and retrieval of “similar” signals. The approach consists of building a classification system that avoids traversing the whole database looking for similarities. The classification system diminishes the problem dimensionality (by means of waveform feature extraction) and reduces the searching space to just the most probable “similar” waveforms (clustering techniques). In the searching procedure, the input waveform is classified in any of the existing clusters. Then, a similarity measure is computed between the input signal and all cluster elements in order to identify the most similar waveforms. The inner product of normalized vectors is used as the similarity measure as it allows the searching process to be independent of signal gain and polarity. This development has been applied recently to TJ-II stellarator databases and has been integrated into its remote participation system.