实芯焊丝拉拔过程中的热处理工艺介绍

叙述了低碳合金结构钢、不锈钢、镍基合金实芯焊丝拉拔过程中的热处理工艺选择;讨论了焊丝的热处理缺陷及防止措施。     

PWM激励下异步电机铁耗等值电阻模型

通过分析PWM激励下异步电机铁耗变化的特点,提出了一种综合考虑电机运行工况和PWM波形特性的铁耗等值电阻模型。基于铁耗分离原理,使用三个电阻分别等效电机铁耗的磁滞分量、经典涡流分量和异常涡流分量,并推导了正弦激励下各个电阻分量的表达式;进而通过分析PWM激励与正弦激励下铁耗间关系,对正弦激励下铁耗模型进行修正,获得PWM激励下铁耗模型;最后提出了确定该模型参数的实验方案。所建模型中各个电阻分量随电机运行频率和PWM波形的调制系数变化而变化,且变化规律各不相同,提高了电机铁耗计算的准确性。仿真和实验验证了该模型的正确性和有效性。     

覆冰复合绝缘子电位分布有限元仿真

国内外对覆冰复合绝缘子电位电场分布研究甚少,研究覆冰复合绝缘子电位分布与选择合理均压环参数,对覆冰地区复合绝缘子设计运行维护具有重要的参考价值。本文利用Ansys12.0软件,采用准静态场有限元法开展了覆冰形态对220kV复合绝缘子电位畸变影响研究。建立220kV复合绝缘子二维轴对称模型,研究了大伞桥接前后冰棱长度,覆冰厚度对复合绝缘子电位影响,对比分析了干冰湿冰情况下沿面电位分布,同时,探讨了均压环几何参数对覆冰复合绝缘子电位分布影响规律。结果表明:桥接前,随冰棱长度增加,冰棱间等电位分布线愈密集;桥接后,全部大伞被冰棱桥接时电位分布畸变最严重;复合绝缘子湿冰电位分布比干冰更不均匀,干冰受冰厚影响比湿冰更明显;最后提出改善覆冰复合绝缘子电位分布的均压环几何参数。     

Reversible data hiding based on hybrid prediction and interleaving histogram modification with single seed pixel recovery

This paper proposes a reversible data hiding scheme for natural images. A hybrid prediction mechanism is utilized in order to produce prediction errors as many as possible. The cover image excluding a seed pixel is partitioned into four non-overlapping segments, and four predictors are tailored for each of them. As a result, most prediction errors concentrate around zero in prediction error histogram. Besides, an interleaving histogram modification mechanism is presented such that the capacity is enhanced and easier to be finely tuned in contrast to some previous approaches. Third, a single seed pixel recovery strategy is introduced. Experimental results show the effectiveness of the proposed method.     

Triple‐Shape Polymeric Composites (TSPCs)

In this paper, the fabrication and characterization of triple‐shape polymeric composites (TSPCs) that, unlike traditional shape memory polymers (SMPs), are capable of fixing two temporary shapes and recovering sequentially from the first temporary shape (shape 1) to the second temporary shape (shape 2), and eventually to the permanent shape (shape 3) upon heating, are reported. This is technically achieved by incorporating non‐woven thermoplastic fibers (average diameter ～760 nm) of a low‐T_m semicrystalline polymer into a T_g‐based SMP matrix. The resulting composites display two well‐separated transitions, one from the glass transition of the matrix and the other from the melting of the fibers, which are subsequently used for the fixing/recovery of two temporary shapes. Three thermomechanical programming processes with different shape fixing protocols are proposed and explored. The intrinsic versatility of this composite approach enables an unprecedented large degree of design flexibility for functional triple‐shape polymers and systems.     

基于调频连续波信号的圆弧式合成孔径雷达成像方法

圆弧式合成孔径雷达是一种对特定地区持续监测的新模式雷达, 具有分辨率高, 观测范围广, 重访周期短等特点, 适合对特定地区的形变监测以及对塌方、滑坡等灾害的预警。针对圆弧式合成孔径雷达特殊的运动形式, 该文提出了一种新的用于调频连续波体制Arc-SAR成像的2维频域算法。首先推导了Arc-SAR的信号模型, 然后提出了在满足转动机械臂长远小于目标最短斜距的情况下使用2维频域算法来聚焦信号, 之后分析了算法误差。该算法可以在假设条件下对目标准确聚焦, 并具有计算速度快等优点。最后使用仿真和实测数据验证了算法的有效性。      

冗余磁盘阵列的故障容错分析

本文在介绍冗余磁盘阵列(RAID)的故障容错机理之后,着重研究了设备故障对RAID系统可靠性的影响.其平均持续正常工作时间和系统在线修复设备故障容许的平均间隔时间的计算结果表明,只要在一定的容许时间内替换或修复故障磁盘,系统可保持持续正常工作状态.     

UTRAN结构演进的研究

本文介绍了基于无线功能新实现点、基于分离RNC(radio network controller)控制面和用户面、基于智能Node B/RAN(radio access network)服务器的三种演进的UTRAN结构,分析和比较了各种UTRAN结构为系统性能、系统部署和无线接口带来的潜在优势和不利影响,旨在为UTRAN的演进提供合理的方案.     

A blockchain-based online language learning system

To check students’ daily language learning tasks and give students corresponding reasonable scores based on their daily behavior is hard for teachers. The existing online language learning systems are vulnerable and easy to be modified by teachers or system managers. Blockchain can provide immutable and trusted storage service and automatic calculation service. Therefore, a blockchain-based online language learning system is proposed in this paper to monitor students’ daily study and automatically evaluate their behavior so as to save teachers from tedious and complex homework verification workload and provide trusted and reliable evaluation on students’ behavior. This paper first introduces the current situation of language learning in universities and the related works on blockchain-based online language learning system. Then the system is detailed in its structure and smart contracts. At last, we implement this system and do the analysis and summary.

     

Patchwise scaling method for content-aware image resizing

Image resizing becomes more and more important in content-aware image displaying. This paper proposes a patchwise scaling method to resize an image to emphasize the important areas and preserve the globally visual effect (smoothness, coherence and integrity). This method for resizing image is based on optimizing the image distance presented in this paper. The image distance is defined based on so-called local bidirectional similarity measurement and smoothness measurement to quantify the quality of resizing outputs. The original image is divided into small important patches and unimportant patches based on an important map. The important map is generated automatically using a novel combination of image edge and saliency measurement. A scaling factor is computed for each small patch. The resized image is produced by iteratively optimizing, which is based on our image distance, the scaling factor for each small patch. Experiments of different type images demonstrate that our method can be effectively used in image processing applications to locally shrink and enlarge important areas while preserving image quality.