金属掺杂对In2O3薄膜光学性质的影响

研究了射频溅射法制备的金属／半导体类型颗粒膜的光学特性。通过样品透射谱分析，发现金属Fe的掺杂使半导体In2O3的带间跌迁由直接跃迁变为间接跃迁；随Fe所占体积份数的增加，局域态尾变宽，带隙变窄。这是由于掺入Fe颗粒后。母体材料与金属颗粒的界面处表面态增多，以及母体材料的非晶化引起的。     

小型PLC在300 MW机组输灰系统干燥器控制中的应用

介绍了火力发电厂小型PLC在300 MW机组干式输灰系统干燥器控制上的应用。以德国西门子公司的S7-200可编程控制器(PLC)为控制主机,实现了吸附式干燥器自动控制的功能。介绍了该控制系统在现场的实际应用状况。     

5H-20新型谷物烘干机的研制与开发

介绍了采用多级顺流干燥工艺开发研制的5H-20新型谷物干燥机，经生产和实际使用证明，该机具有降水幅度大，耗能低，对粮食无污染，可以烘干多种谷物等特点。     

GSX600型闪蒸干燥机在干燥高粘度膨润土中的应用

根据GSX600型闪蒸干燥机干燥膨润土的运行情况,介绍了GSX600型闪蒸干燥机的操作方法及操作时应注意的一些问题,根据膨润土高粘度的特性和设备的具体情况对系统做了一些调整和改进,对干燥产品的粒度和水分进行了测试。     

粮食烘干塔智能预测控制系统软件的开发

根据粮食烘干过程多变量、大滞后和非线性的特点，提出了粮食烘干塔智能预测控制方法，介绍了控制原理和系统软件关键技术的实现方法，该系统在实际应用中获得了良好的控制效果。     

并流喷雾干燥塔的计算机辅助设计研究

喷雾干燥广泛应用于众多工业品的生产。图解积分法是目前求喷雾干燥塔塔径和塔高常用的方法，但是图解积分法计算过程繁琐，误差大且无法编程计算。因此将喷雾干燥塔中雾滴运动的阻力系数与雷诺数之间的关系用误差极小的多项式取代图解积分法中使用的误差较大的Allen公式，并给出了喷雾干燥塔塔径和塔高的积分式，利用四阶复化高斯～勒让德数值积分法计算喷雾干燥塔塔径和塔高，有效地提高了设计精度，利用可视化语言Visual Basic6．0开发计算机辅助设计软件。算例表明：计算机辅助设计方便、结果精确，为进一步实现并流喷雾干燥塔的优化设计提供了一个有效的设计方法与手段。同时建立以年总费用为目标函数的并流喷雾干燥塔经济评价模型，对并流喷雾干燥塔的设计参数如空气进出口温度、空气进口湿度等参数进行经济评价与分析，探讨其对并流喷雾干燥塔运行费用与年总投资的影响，对实现并流喷雾干燥塔的优化设计，降低能耗，节省投资具有一定的参考价值。     

基于Matlab无刷电动机模型参考自适应控制的研究与实现

本文在分析无刷电动机数学模型的基础上,建立了控制系统的仿真模型,提出了直流无刷电机调速系统模型参考自适应控制的新方法.在双闭环调速系统中,电流环采用电流滞环控制,转速环采用间接参考模型自适应控制,控制器参数估算采用最小二乘算法.仿真结果表明:这种新型的间接模型参考自适应控制方法响应快、无超调、鲁棒性强、抗干扰能力好,较传统PI控制具有更好的动、静态特性.     

The value for innovation of inter-firm networks and forming alliances: A meta-analytic model of indirect effects

In the past few decades, we have seen strong growth in the number of publications on the role of alliances and networking on innovative performance and, more generally, firm performance. The empirical results of these studies are, however, often debated, and there seems to be little consensus in the academic literature. We therefore focus our meta-analytical model test on the accumulated direction and magnitude of the indirect relationships reported in the literature between innovation, networking, alliances, and firm performance. Our meta-analysis is based on 517 correlations, 156 studies, and a total sample size of 93,048 firms. We compare the findings of our meta-analysis to the results of a bootstrapping analysis. Our results corroborate the bulk of studies, which suggests that networks and alliance experience play an important role in generating rents from innovation resources through both direct and indirect effects. The practical implication is that firms need to engage in networks and also develop strong alliance management capabilities to be able to increase the contribution innovation resources can make to their performance.     

Reaching phase free adaptive fuzzy synergetic power system stabilizer

In this paper, an adaptive fuzzy power system stabilizer is developed based on robust synergetic control theory and terminal attractor techniques. The main contribution consists in making the dynamic system insensitive to parameters variation. This aim is achieved using a new synergetic controller design such that power system states start, evolve and remain on a designer chosen attractor toward the equilibrium point therefore avoiding transient mode. Rendering the design more robust, fuzzy logic systems are used to approximate the unknown power system dynamic functions without calling upon usual model linearization and simplifications. Based on an indirect adaptive scheme and Lyapunov theory, adaptation laws are developed to make the controller handle parameters variations due to the different operating conditions occurring on the power system and to guarantee stability. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results show the effectiveness and robustness of the proposed stabilizer in damping power system oscillations under various disturbances and better overall performance than classical PSS and some other types of power stabilizers.     

Indirect model for roughness in rough honing processes based on artificial neural networks

In the present paper an indirect model based on neural networks is presented for modelling the rough honing process. It allows obtaining values to be set for different process variables (linear speed, tangential speed, pressure of abrasive stones, grain size of abrasive and density of abrasive) as a function of required average roughness Ra. A multilayer perceptron (feedforward) with a backpropagation (BP) training system was used for defining neural networks. Several configurations were tested with different number of layers, number of neurons and type of transfer function. Best configuration for the network was searched by means of two different methods, trial and error and Taguchi design of experiments (DOE). Once best configuration was found, a network was defined by means of trial and error method for roughness parameters related to Abbott–Firestone curve, Rk, Rpk and Rvk.