烟道流量计量标准装置

为了解决我国烟道流量计的量值溯源问题,中国计量科学研究院建立了烟道流量计量标准装置。装置使用可溯源至标准转盘的激光多普勒测速仪作为原级标准器,采用激光多普勒流速剖面扫描和超声流量计波动修正的方式测量标准流量,经校准的8声道超声流量计为工作级标准表,具备了908~104840m3/h的测量能力,扩展不确定度为0.62%(k=2),可对最大口径为1m的流量计进行校准。装置下游测试段包括圆形管段和矩形管段,能够开展烟道流量计测量性能的研究。     

“任务驱动”教学法在可编程控制器课程教学中的实践与分析

以可编程控制器课程为例,介绍"任务驱动"教学法在教学过程中的具体应用,并探讨了实施过程中存在的问题与解决方法。     

落葵浆果天然染料提取及对羊毛织物的染色性能

文章主要研究用水浸法提取落葵浆果天然染料及研究浸提液对羊毛织物的染色性能。以水为提取剂提取落葵浆果天然染料,探讨提取工艺中料液比、提取温度及时间等因素对落葵浆果天然染料提取效果的影响。研究结果表明,落葵浆果水浸提法优化工艺为:料液比1∶20、提取温度70℃、提取时间30 min。落葵浆果天然染料可以对羊毛织物进行染色,媒染染色与直接染色相比,染色深度深且会呈现不同的颜色。由于媒染剂的络合作用,媒染染色色牢度比直接染色普遍高1~2级。     

9000m顶部驱动钻井装置结构选型研究

为大幅提高钻井效率,针对9 000 m钻井深度对顶驱的设计要求,通过比较顶驱装置关键部分几种典型的结构,提出适合该型号顶部驱动钻井装置的最优结构形式,为后续9 000 m钻井深度顶部驱动钻井装置的研究提供指导和借鉴。     

新2级能效低噪音节能环保变压器的研发设计

随着电力变压器新版能效标准于2021年6月1日起正式实施,如何降低变压器的损耗成为各生产厂家面临的主要课题.研发中首次使用宝武钢铁公司生产的低损耗B20R065硅钢片,通过电磁计算、结构设计、工艺制造等一系列的保障措施,试制出SB20-M-2500/10.5新2级能效低噪音节能环保叠铁心变压器,并通过型式试验验证了技术方案的可行性.     

500 kV 开关弹簧机构支架螺栓断裂的原因分析及处理

HPL500B2型弹簧机构支架(BA)螺栓断裂可能导致开关分合闸失败,对其原因进行分析,发现BA螺栓由于预紧固力矩过大,接近其扭断力矩,使得作用在BA螺栓上的力偏高,BA螺栓安全系数仅为12%,安全系数较低。列出BA螺栓更换步骤及注意事项,并详细介绍分闸、合闸弹簧调整步骤,为类似事件的处理提供参考。     

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.