煤层顶板硬岩大直径定向钻孔施工关键技术

根据顶板高位定向钻孔快速钻进成孔与工作面卸压瓦斯高效抽采治理需要，针对现有螺杆马达定向钻进技术与分级扩孔方法存在的问题，开展了顶板硬岩定向钻进与大直径扩孔钻进关键技术研究，开发了冲击回转定向钻进技术、扭冲回转定向钻进技术、扭冲旋转扩孔技术以及双级双速扩孔技术等钻孔提速新技术，研制了冲击螺杆马达、矿用小直径扭力冲击器、双级双速螺杆马达、组合式扩孔钻头等配套钻具。综合试验结果表明，硬岩定向钻孔平均机械钻进效率达到8.34 m/h，最高达到13.6 m/h，较常规螺杆马达定向钻进技术提升20%~30%；硬岩大直径扩孔终孔直径达到200 mm，机械钻进效率平均达到5.6 m/h以上，最高达到10.5 m/h。该技术提升了顶板硬岩定向钻进效率与大直径扩孔钻进效率，缩短了顶板高位定向钻孔的综合施工周期，为大直径高位定向长钻孔快速成孔与高效抽采治理回采工作面卸压瓦斯提供了可靠的技术手段。     

采煤工作面煤层注水工艺优化与应用

针对目前煤层注水存在的施工钻孔效率低、钻孔深度达不到要求、注水钻孔封孔不严、封孔器回收困难等问题，研究注水工艺的改进优化，对钻机、钻具及封孔器进行重新设计选型，形成了一整套的注水装备。该装备的应用提高了施工效率，为降低工作面粉尘危害、抑制工作面瓦斯涌出、防治煤炭自然发火等危害探索出了更加高效的途径和方法。现场应用表明，煤层注水有效地改善了工作面作业环境，为工作面实现高产高效奠定了基础。     

滚动轴承振动加速度信号积分测试技术研究

滚动轴承出厂时需要根据国家标准进行振动检测。对滚动轴承的振动进行测量的方法主要是采用速度型测振和加速度型测振。由于速度型测振仪和加速度型测振仪所采用的传感器不同,两者的测量结果有相关性,但测量结果并不一致。传统的轴承测振仪采用模拟电路,对加速度信号进行准确积分,难度较大;随着计算机测量技术的迅速发展,运用数字量测试和积分技术,可以采用对加速度信号进行积分得到速度的方法进行测试。通过对轴承的加速度信号进行积分,进行振动速度测量,可以在同样的测试条件下对轴承的振动加速度和振动速度进行比较,具有实际应用价值。本文采用数字量测试技术,以深沟球轴承为研究对象,对加速度积分算法进行研究,利用MATLAB和Lab VIEW软件编写了数字滤波器和时域积分算法,减去了时域积分产生的趋势项,降低了趋势项误差。通过实际测量实验,所得结果与轴承行业所用的标准精密模拟积分器所得结果具有较好的一致性,可以满足轴承振动速度测量的需要。     

基于LCOE最优的数字化风电场及其关键技术研究

数字化风电场是风电场综合利用数字化技术的新阶段。在分析风电场建设管理所面临的挑战的基础上，讨论了平准化度电成本（LCOE）的计算公式和内涵，给出了数字化风电场的定义，阐述了基于LCOE最优的数字化风电场的“风、机、场、网、环”五大特征以及数字化技术在降低LCOE中的作用。最后，总结了实现数字化风电场的风资源、大数据平台、数据分析建模、数字孪生和数据安全五大关键技术。     

一种基于双重ddPCR的肉制品中牛源性成分的定量分析方法

将低价肉类原料掺入高价肉制品是一种典型的肉类掺假方式，为准确鉴别牛肉及牛肉制品的真伪，建立一种基于双重微滴式数字聚合酶链式反应（droplet digital polymerase chain reaction，ddPCR）的牛源性成分定量分析方法。通过对14 种动物的Beta-actin单拷贝基因序列进行分析，设计牛源性特异性引物、探针与动物源性成分通用引物、探针并建立双重ddPCR体系，推导出牛源性成分质量与其特异性扩增拷贝数之间的计算公式，对牛源性成分进行定量检测该方法得到牛源性成分质量M牛（mg）与其特异性扩增拷贝数浓度C牛（copies/μL）之间的计算公式为M牛=0.033C牛＋2.37，对已知牛肉质量的混合肉样品与不同部位的牛肉样品进行检测，结果显示牛肉定量检测值与实际质量基本一致。同时拷贝数相对含量可辅助判断肉制品中是否存在非牛源性的其他动物源性成分掺假。对市售样品的检测发现，存在目标肉样含量不达标以及不同程度的动物源性成分等掺假现象，说明该检测方法可为牛肉制品掺假量化判定和混合源性产品分级鉴定提供技术支撑。     

Extrinsic parameter's adjustment and potential implications in Plasmodium falciparum malaria diagnosis

Malaria is a major public health concern, affecting over 3.2 billion people in 91 countries. The advent of digital microscopy and Machine learning with the aim of automating Plasmodium falciparum diagnosis extensively depends on the extracted image features. The color of the cells, plasma, and stained artifacts influence the topological, geometrical, and statistical parameters being used to extract image features. During microscopic image acquisition, custom adjustments to the condenser and color temperature controls often have an influence on the extracted statistical features. But, our human visual system sub-consciously adjusts the color and retains the originality in a different lighting environment. Despite the use of appropriate image preprocessing, findings from the literature indicate that statistical feature variations exist, allowing the risk of P. falciparum misinterpretation. In order to eliminate this pervasive variation, the current work focuses on preprocessing the extracted statistical features rather than the prepossessing of the source image. It begins with the augmentation of series images for a microscopic field by inducing illumination variations during the microscopic image acquisition stage. A set of such image series is analyzed using a Nonlinear Regression Model to generalize the relationship between microscopic images acquired with variable ambient brightness and a specific feature. The projection point of the centroid feature onto the brightness parameter is identified in the model and it is denoted as the optimum brightness factor (OBF). Using the model, the feature correction factor (CF) is calculated from the rate of change of feature values over the interval OBF, and the brightness of the test image is processed. The present work has investigated OBF for selected image textural features, namely Contrast, Homogeneity, Entropy, Energy, and Correlation individually from its co-occurrence matrices. For performance analysis, the best state-of-the-art method uses selected texture as a subset feature to evaluate the effectiveness of P. falciparum malaria classification. Then, the impact of proposed feature processing is evaluated on 274 blood smear images with and without Feature Correction (FC). As a result, the “p” value is less than .05, which leads to the result that it is highly significant and the classification accuracy and F-score of P. falciparum malaria are increased.     

Structural integrity assessment of nuclear containment through fracture characterization

The paper deals with the study of structural response of partially cracked nuclear containment model structure in over pressurized condition with the simulated experiments conducted under severe accidents analysis program for Indian nuclear containment structures. In this research, the fracture characterization of concrete containment structure is also investigated through the over pressure experiments on the BARC Containment (BARCOM) test model structure, which represents 1:4 scale of the prototype 540 MWe Tarapur pre‐stressed nuclear containment structure. In addition to the surface‐type electrical resistance, strain gauges conventionally and commonly deployed for containment proof‐test and ultimate load capacity evaluation of containment models, embedded vibratory wire strain gauges (VWSGs), the digital image correlation (DIC) technique, and soap bubble tests are employed in this study. For fracture characterization, an optical crack profile (OCP) technique is developed through DIC full‐field experiment conducted at the identified critical locations with conventional strain gauges to evaluate the fracture energy and the characteristics of the fracture process zone of concrete containment model structure subjected to the over‐pressure condition for its performance assessment in the case of the beyond design basis accidents. The combination of conventional sensors and full‐field DIC deployed for the first time on the largest scale containment model along with the associated analysis is shown to be effective in fracture characterization and improved structural integrity assessment of the containment model.     

数字花卉植物的全息可视化与交互实现

花卉植物形态、结构与生长过程的数字化和可视化是现代林业科研的重要研究内 容，数字花卉植物在科普、教育、展示等方面都有着广泛的应用与需求。全息影像技术是一种 新兴的前沿技术，其原理源自佩珀尔幻象，通常用于生成立体感强的影像，实现数字幻象与真 实世界的融合，拥有良好的观赏性，用户接受度较高。将全息影像技术与数字花卉植物相关研 究进行结合，可以加强数字花卉植物的可视化效果，从而实现更好的科普、教育、展示效果。 因此在现有的研究基础之上，考虑实现数字花卉植物的全息可视化，并在可视基础上增加了用 户交互实现，设计出一套兼具展示性和交互性的流程，力求总结出一种具有完整可行性的方案， 从而对数字花卉植物的新型表现形式进行深入研究，以期对数字植物研究与应用的进一步发展 提供参考。     

Digitising Teaching and Learning – Additional Perspectives for Chemistry Education

Chemistry requires and combines both observable and mental representations. Still we know that learners often struggle in combining these perspectives successfully, especially when experimental observations contradict the model‐based explanations, e. g. in interpreting the chemical equilibrium as dynamic processes while observing a static system without any visible changes. Digital media offer potentials that might not have been accessible to this degree until now. However, we do not know enough with regard to the degree and effects these media tools have in supporting learning processes but perhaps also in hindering them. This article presents four approaches on how to potentially make use of digital media in learning processes based on theoretical considerations and empirical investigations. The projects will explore applications of media as visualization, learning and investigation tools in chemistry education, embracing techniques from virtual realities to eye‐tracking.     

原始钻孔轨迹模型的建立及模拟方法的精度对比

建立原始钻孔轨迹模型,可以为各种轨迹模拟方法计算精度分析及误差因素量化分析提供数据基础。测点要素间的关系可以看作顶角、方位关于深度的函数关系,将这种函数关系模型化,可获得模型曲线的切向量关于深度的函数关系。以此为基础,用微分方法得到曲线三维坐标关于深度的导函数,再用积分方法即可得到原始钻孔轨迹模型曲线。该模型提供了不同弯曲强度条件下的原始钻孔测点要素和三维坐标,对全角半距法和最小曲率法2种模拟方法进行误差计算、对比和分析,验证了在计算精度上最小曲率法优于全角半距法。根据计算结果得出了2种方法在计算误差上的差异,并针对勘查钻孔和定向钻孔2种实际应用条件得出相应的计算精度。