飞秒激光加工单晶金刚石制备正前角磨削工具

目的制造一种磨粒有序排布、具有正前角的无结合剂端面金刚石磨削工具。方法采用波长为1030 nm、脉宽为250 fs的钛蓝宝石飞秒激光对单晶金刚石(SCD)进行烧蚀加工,首先研究加工工艺参数(特别是烧蚀轨迹间距)对金刚石加工效率及表面质量的影响。采用预先设计的激光扫描路径,基于优化后的工艺参数在SCD表面加工出微磨粒阵列结构,各磨粒呈方锥台形结构,其顶部倾斜角约为100°。在此基础上,对微磨粒阵列进行烧蚀加工,将所有微磨粒顶部的倾斜角减小至小于90°。结果当激光烧蚀轨迹间距为10.0μm时,烧蚀加工表面RMS粗糙度最小。确定了一种微磨粒边缘倾斜角小于90°且磨粒有序排布的新型无结合剂金刚石端面磨削工具的激光制备方法和工艺,采用该工艺加工的磨削工具表面质量好,轮廓精度高,磨粒平均正前角约为9.80°。结论采用飞秒激光可以高质量、高效率地制备出磨粒有序排布的新型正前角无结合剂金刚石端面磨削工具,该工具有望在硬脆材料磨削中减小磨削力,提高材料表面完整性。     

抗仿射变换图像局部特征检测与匹配算法研究

针对SIFT局部特征在图像发生大视角变化时匹配失效的问题,提出了一种基于仿射变换模型的图像局部特征检测和匹配算法。通过建立图像仿射变换模型,对相机光轴视角变换的纬度角θ和经度角Φ进行模拟,并采用SIFT算法进行特征检测,基于最邻近法进行特征匹配,使算法除了具有SIFT本身的抗图像缩放、旋转和亮度变化等特点外,还具有较强的抗仿射变换能力。试验结果表明:当图像发生相对斜率较大的仿射变换时,该图像特征检测和匹配算法仍有较强的抵抗能力。算法可用于图像末端寻的制导弹丸和空中侦察设备拍摄的图像进行有效匹配。     

Low-Power Design of Ethernet Data Transmission

For the reliability and power consumption issues of Ethernet data transmission based on the field programmable gate array （FPGA）, a low-power consumption design method is proposed, which is suitable for FPGA implementation. To reduce the dynamic power consumption of integrated circuit （IC） design, the proposed method adopts the dynamic control of the clock frequency. For most of the time, when the port is in the idle state or lower-rate state, users can reduce or even turn off the reading clock frequency and reduce the clock flip frequency in order to reduce the dynamic power consumption. When the receiving rate is high, the reading clock frequency will be improved timely to ensure that no data will lost. Simulated and verified by Modelsim, the proposed method can dynamically control the clock frequency, including the dynamic switching of high-speed and low-speed clock flip rates, or stop of the clock flip.     

帆板驱动微振动对卫星的影响与对策

基于帆板驱动机构精确建模，对帆板及其驱动带来的影响进行分析；在分析帆板驱动特性的基础上，给出了微振动测试数据及其分析结果；并以某卫星为例给出了帆板驱动控制时微振动对姿态的影响，提出了频率约束和振动主动抑制控制相结合的解决措施及验证结果。     

Two-Level Designs to Estimate All Main Effects and Two-Factor Interactions

We study the design of two-level experiments with N runs and n factors large enough to estimate the interaction model, which contains all the main effects and all the two-factor interactions. Yet, an effect hierarchy assumption suggests that main effect estimation should be given more prominence than the estimation of two-factor interactions. Orthogonal arrays (OAs) favor main effect estimation. However, complete enumeration becomes infeasible for cases relevant for practitioners. We develop a partial enumeration procedure for these cases and we establish upper bounds on the D-efficiency for the interaction model based on arrays that have not been generated by the partial enumeration. We also propose an optimal design procedure that favors main effect estimation. Designs created with this procedure have smaller D-efficiencies for the interaction model than D-optimal designs, but standard errors for the main effects in this model are improved. Generated OAs for 7–10 factors and 32–72 runs are smaller or have a higher D-efficiency than the smallest OAs from the literature. Designs obtained with the new optimal design procedure or strength-3 OAs (which have main effects that are not correlated with two-factor interactions) are recommended if main effects unbiased by possible two-factor interactions are of primary interest. D-optimal designs are recommended if interactions are of primary interest. Supplementary materials for this article are available online.     

Evaluation of chicken freshness using a low-cost colorimetric sensor array with AdaBoost–OLDA classification algorithm

This paper attempted to evaluate chicken freshness using a low-cost colorimetric sensor array with the help of a classification algorithm. We fabricated a novel and low-cost colorimetric sensors array, with a specific colorific fingerprint to volatile compounds, using printing chemically responsive dyes on a C2 reverse silica-gel flat plate. In addition, we proposed a novel classification algorithm for sensors data classification – orthogonal linear discriminant analysis (OLDA) and adaptive boosting (AdaBoost) algorithm, namely AdaBoost–OLDA. And we compared it with two classical classification algorithms – linear discriminant analysis (LDA) and back propagation artificial neural network (BP-ANN). Experimental results showed classification results by AdaBoost–OLDA algorithm is superior to BP-ANN and LDA algorithms, the classification results by which are both 100% in the calibration and prediction sets. This study sufficiently demonstrated that the colorimetric sensors array with a classification algorithm has a high potential in evaluating chicken freshness, and AdaBoost–OLDA algorithm has a strong performance in solution to a complex data classification.     

Studies on thin film based flexible gold electrode arrays for resistivity imaging in electrical impedance tomography

Practical phantoms are essential to assess the electrical impedance tomography (EIT) systems for their validation, calibration and comparison purposes. Metal surface electrodes are generally used in practical phantoms which reduce the SNR of the boundary data due to their design and development errors. Novel flexible and biocompatible gold electrode arrays of high geometric precision are proposed to improve the boundary data quality in EIT. The flexible gold electrode arrays are developed on flexible FR4 sheets using thin film technology and practical gold electrode phantoms are developed with different configurations. Injecting a constant current to the phantom boundary the surface potentials are measured by a LabVIEW based data acquisition system and the resistivity images are reconstructed in EIDORS. Boundary data profile and the resistivity images obtained from the gold electrode phantoms are compared with identical phantoms developed with stainless steel electrodes. Surface profilometry, microscopy and the impedance spectroscopy show that the gold electrode arrays are smooth, geometrically precised and less resistive. Results show that the boundary data accuracy and image quality are improved with gold electrode arrays. Results show that the diametric resistivity plot (DRP), contrast to noise ratio (CNR), percentage of contrast recovery (PCR) and coefficient of contrast (COC) of reconstructed images are improved in gold electrode phantoms.     

Target tracking with fast adaptive revisit time based on steady state IMM filter

Time is a valuable resource in phased-array radar and proper use of it enables the radar to track more targets simultaneously. Appropriate usage of time in the tracking means the radar can minimize the revisit rate of the tracked targets while the accuracy of targets position estimation is still acceptable. In this paper, a new method for determination of target revisiting time is proposed which has relatively low computational cost and uses steady state filters with Interactive Multiple Models structure. The proposed algorithm allows the radar designer to determine the filter parameters by some criteria such as the desired accuracy and targets maneuver. The performance of the proposed method is compared with the conventional filters for standard maneuverable flying targets. Simulations show the better accuracy and reliability of the proposed method beside its less target revisit time and computational load.