变压器智能化远程监控仪

本文主要介绍一种变压器智能化远程监控设备,该设备通过三相电力采集芯片采集变压器的实时电力参数并对这些电力参数进行实时的分析;数据的传输采用无线的GSM数据服务和短消息业务来实现,具有适合各种地理状况下的变压器监控等突出的优点.     

基于双基区晶体管结构的光控振荡器

采用DUBAT(双基区晶体管)和光电二极管构成新型无电感光控振荡器,并对其等效电路进行了模拟,分析了工作原理.实验数据证明了该光控振荡器频率与光强成正比,可实现光的模数转化.由于DU BAT结构简单,与集成电路工艺兼容,成本低廉,为光控振荡器与功能电路的集成应用提供了新的实现方式     

Al/SiO_2/Si表面Al_2O_3纳米图形的AFM阳极氧化制备方法

采用AFM阳极氧化方法,在控制AFM探针尖端电压和扫描方式的条件下,在Al/SiO2/Si表面制备了Al2O3纳米图形,图形最小尺寸为70nm.研究了表面吸附水层存在下AFM阳极氧化机理.实验结果表明AFM阳极氧化是制备金属氧化物半导体纳米器件的较好方法     

含柔性滑移伸展单元飞行器动力学建模及仿真研究

分析了伸展单元的几何结构及动力学特点,引入与伸展运动有关的广义伸展坐标,提出滑移伸展单元的运动学描述方法,基于Ｌａｇｒａｎｇｅ原理,建立了这类飞行器的动力学模型,最后仿真研究了这类系统独特的动力学行为。     

仿真模型有效性定量确认方法

仿真模型有效性评估是当今国际仿真界研究的一个热点问题。它主要包括模型确认和模型验证两部分内容。本文综述了仿真模型确认方法,重点介绍了在工程上适用的仿真模型有效性评估的定量化确认的统计检验方法。最后用实例说明方法的使用情况。     

基于映射法的曲面自适应网格生成

板壳成形数值模拟过程中用自适应网格不仅可以实现以尽可能少的计算量获得指定精度要求的解,更重要的是可以提高解的精度。而曲面自适应网格自动生成技术国内外都刚开始研究,目前没有很好的方法。本文首次基于映射法在参数区域生成自适应网格,然后映射到空间,用空间曲面的曲率及有限元计算误差估计来控制参数区域中的自适应网格生成。数值例子验证了本算法的正确性及可靠性。     

Gain-enhanced compact broadband microstrip antenna

With the loading of a high-permittivity superstrate layer and a 1 Ω chip resistor, a compact rectangular microstrip antenna with enhanced gain and wider bandwidth can be implemented. With the antenna size reduced to be ~6% that of a conventional patch antenna, the proposed structure can have an operating bandwidth of more than six times that of a conventional patch antenna, with an almost equal antenna gain level. Details of the experimental results are presented and discussed     

High-brightness AlGaInP 573-nm light-emitting diode with a chirpedmultiquantum barrier

A novel chirped multiquantum barrier (CMQB) structure was used for AlGaInP light-emitting devices. We have theoretically studied the blocking efficiency of the CMQB structure and found that the CMQB structure is more effective in blocking the electron wave than the conventional uniform multiquantum barrier (UMQB) structure. AlGaInP light emitting diodes (LEDs) with the CMQB structure and the UMQB structure were both fabricated and compared. It was found that the luminescence intensity of the AlGaInP CMQB LED is larger and the intensity distribution of the AlGaInP CMQB LED is more uniform than the AlGaInP UMQB LED. The intensity-current measurement also shows that the electroluminescence intensity of the AlGaInP CMQB LED starts to saturate at a higher injection current     

A 3.3-V/5-V low power TTL-to-CMOS input buffer

A separately self-biased transistor-transistor logic (TTL)-to-CMOS input buffer (SSIB) is proposed. Its logic threshold voltage is kept at 1.4 V when supply voltage is changed from 3.3 V to 5 V, making it suitable for 3.3-V/5-V dual voltage applications. It has low power dissipation, high operating speed, and a logic threshold voltage less sensitive to process and supply voltage variations. The proposed SSIB input buffer was realized in a 0.8-μm single-polysilicon double-metal (SPDM) CMOS technology, The measured logic threshold voltage variations due to process variations are ±24 mV for 5 V supply and ±16 mV for 3.3 V supply, respectively. Its logic threshold voltage variations due to supply voltage variation from 3.3 V to 5 V are within 10 mV. In ring oscillator configuration, the measured delay and power dissipation are 0.45 ns and 0.37 mW for 5-V supply and 0.51 ns and 0.14 mW for 3.3-V supply, respectively     

A spatiotemporal neural network for recognizing partially occludedobjects

In this paper, a spatiotemporal neural network for partially occluded object recognition is presented. The system consists of two major components: a feature extraction process and a spatiotemporal modular neural network. The former is made up of a sequence of preprocessing techniques including thresholding, boundary extraction, Gaussian filtering, and a split-and-merge algorithm to generate features that will represent the objects to be recognized. These acquired features are invariant to rotation, translation, and scaling and can serve as input to the spatiotemporal network that utilizes the concept of tap delay to account for spatial correlation between consecutive input features. A shape perceiver is designed into the network to extract continued parts of an object as well as to enable the inclusion of each object's unique characteristics into the system. Traditional neural network approaches for recognizing partially occluded objects have encountered significant problems because of the incomplete boundaries of the objects. In our approach, by creatively installing tap delays, the system can escape this limitation. Experimental results show that the proposed system can produce satisfactory results in efficiently and effectively recognizing partially occluded objects. Furthermore, intrinsic to this system is the ease by which it can be realized through parallel implementation, thus minimizing the tremendous time spent in matching object contours stored in a model database, as is the case in conventional recognition systems