浅谈不同给液方式在铜电解车间的应用

不同给液方式对铜电解过程中有重要的影响,不同的循环方式会影响槽内温度分布、电解液成分及阳极泥沉降等,因此,根据铜电解生产不同情况的需要,分析对比了多种给液方式在贵冶电解车间的应用,总结了这几种给液方式的优缺点和适用条件。     

A novel fast distance relay for series compensated transmission lines

This paper presents a fast distance relay for series compensated transmission lines based on the R–L differential-equation algorithm using the theory of equal transfer process of transmission lines. The measuring distances based on the proposed algorithm can fast approach the actual value of fault distance when a fault occurs in front of the series capacitor. When a fault occurs behind of the series capacitor, the fault loop, including the series capacitor, does not match the R–L transmission line model, so the measuring distances fluctuate severely. Based on this, the relative position of the fault with respect to the series capacitor can be judged effectively according to the fluctuation range of the measuring distances, and the accurate fault location can be obtained fast. A variety of PSCAD/EMTDC simulation tests show that the new relay has fast operating speed and high accuracy when applied to the long series compensated transmission lines.     

多先验融合的图像显著性目标检测算法

为了更加准确地检测出图像中的显著性目标，提出了多先验融合的显著性目标检测算法。针对传统中心先验对偏离图像中心的显著性目标会出现检测失效的情况，提出在多颜色空间下求显著性目标的最小凸包交集来确定目标的大致位置，以凸包区域中心计算中心先验。同时通过融合策略将凸包区域中心先验、颜色对比先验和背景先验融合并集成到特征矩阵中。最后通过低秩矩阵恢复模型生成结果显著图。在公开数据集MSRA1000和ESSCD上的仿真实验结果表明，MPLRR能够得到清晰高亮的显著性目标视觉效果图，同时F，AUC，MAE等评价指标也比现有的许多方法有明显提升。     

脉冲电沉积镍-铜合金

采用脉冲电沉积技术在304不锈钢表面制备Ni-Cu合金镀层,镀液组成和工艺条件为:NiSO4ꞏ6H2O 200g/L,CuSO4ꞏ5H2O 10 g/L,十二烷基硫酸钠0.2 g/L,柠檬酸钠80 g/L,糖精0.2 g/L,pH 4.0,温度25°C,搅拌速率30 r/min,平均电流密度40~120 mA/cm2,脉冲频率0~100 Hz,占空比20%~90%,时间30 min。研究了平均电流密度、脉冲频率和占空比对Ni-Cu合金镀层的元素组成、表面形貌和显微硬度的影响,得到较优的工艺参数为:平均电流密度40 mA/cm2,脉冲频率50 Hz,占空比60%。该条件下所得Ni-Cu合金镀层由质量分数分别为56.53%和43.47%的Ni和Cu组成,呈“菜花”状形貌,结晶细致、均匀,显微硬度为614.4 HV。     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

门架式堆取料机在铜冶炼中的生产实践

针对铜冶炼工艺的特点,从门架式堆取料机对前后工序衔接、结构、原理出发,介绍了其在熔炼炉系统和吹炼炉系统中的应用情况。经过试生产期的生产实践证明,门架式堆取料机具有场地利用率高、取料量大,自动化程度高和安全环保等优点。     

柠条的纤维特性及其双螺杆CMP制浆性能研究

以柠条为原料，分析了其化学组分和纤维形态，并探讨了柠条双螺杆CMP法的制浆工艺以及浆料的纤维形态和成纸的物理性能。研究结果表明：与针、阔叶木相比，柠条原料中纤维素和综纤维素质量分数较低，苯醇抽出物和热水抽出物质量分数较高，柠条纤维长度总体偏短，木质部和皮部的纤维质量平均长度分别为0.621和0.819 mm，还存在部分杂细胞。采用3.5% Na₂SO₃和1.5% NaOH常温预浸12 h、90℃汽蒸1 h后再用双螺杆挤浆机在质量分数35%下进行搓丝，并结合高浓盘磨机磨浆，所得CMP浆得率可达73%。柠条CMP浆基本保持了纤维原有的长度，质量平均长度达0.650 mm，长宽比为32.7，纤维解离较好，但分丝帚化情况不理想，含有部分纤维束和杂细胞。当加拿大游离度为300 mL时，柠条CMP浆成纸的环压强度指数和松厚度较高，分别为8.67（N·m）/g和2.56 cm³/g，抗张指数为19.6（N·m）/g，本色浆白度较高，达50%（ISO）。柠条CMP浆适合配抄瓦楞原纸等包装用纸，漂白后可配抄新闻纸和白板纸。     

Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

This research proposes ACARDS (Augmented-Context bAsed RecommenDation Service) framework that is able to utilize knowledge over the Linked Open Data (LOD) cloud to recommend context-based services to users. To improve the level of user satisfaction with the result of the recommendation, the ACARDS framework implements a novel recommendation algorithm that can utilize the knowledge over the LOD cloud. In addition, the noble algorithm is able to use new concepts like the enriched tags and the augmented tags that originate from the hashtags on the SNSs materials. These tags are utilized to recommend the most appropriate services in the user’s context, which can change dynamically. Last but not least, the ACARDS framework implements the context-based reshaping algorithm on the augmented tag cloud. In the reshaping process, the ACARDS framework can recommend the highly receptive services in the users’ context and their preferences. To evaluate the performance of the ACARDS framework, we conduct four kinds of experiments using the Instagram materials and the LOD cloud. As a result, we proved that the ACARDS framework contributes to increasing the query efficiency by reducing the search space and improving the user satisfaction on the recommended services.