连轧机用人字轮齿轴断裂失效分析

用宏观断口分析、化学检验、力学性能测定、低倍检查、金相组织及夹杂物评定鉴别、受力分析及强度寿命定量估算的方法，对人字轮被动齿轴端断裂失效原因进行分析，并提出改进措施。     

O—O数据模型中实体联系的表达方法

具有对实体和实体间联系的描述能力，是数据库的基本，吼是对数据库进逻辑设计的基本出发点。Ｏ－Ｏ数据模型不具备显式描术这实体联系的手段。且优于关系模型。     

外购粗铅检验准确性测试

通过对外购粗铅的整体熔化，测试出外购粗铅中金、银的含量，以验证外购粗铅检验的准确性，确保铅冶炼金银平衡。     

用潜坝对抚州市南区水厂取水口淤沙进行治理

多沙河流中的水厂取水口，枯水期经常存在淤沙，影响抽水。以往的治理方法多是采用丁坝群束水冲沙，但坝田淤高有碍行洪，对城市防洪不利．南区水厂采用潜坝方案，兼顾防洪．通航等要求，缩小治理范围，用十分简易的方法获得成功，且投资更省，值得在类似工程中推广运用．     

Failure analysis and wear mechanism study of a heavily loaded gear

Failure analysis and a study of the wear mechanism were performed on a heavily loaded carburized gear with some unusual features. The analysis showed that the different failure forms on the tooth surface of the gear were dependent on the sub-surface shearing stress, the lubrication conditions and the surface roughness. Delaminations formed on the addendum surface were the main reason for the gear failure. A suggestion for improvement has been tried, and a desirable result has been obtained.     

CoGCN: Combining co‐attention with graph convolutional network for entity linking with knowledge graphs

Entity linking is a fundamental task in natural language processing. The task of entity linking with knowledge graphs aims at linking mentions in text to their correct entities in a knowledge graph like DBpedia or YAGO2. Most of existing methods rely on hand‐designed features to model the contexts of mentions and entities, which are sparse and hard to calibrate. In this paper, we present a neural model that first combines co‐attention mechanism with graph convolutional network for entity linking with knowledge graphs, which extracts features of mentions and entities from their contexts automatically. Specifically, given the context of a mention and one of its candidate entities' context, we introduce the co‐attention mechanism to learn the relatedness between the mention context and the candidate entity context, and build the mention representation in consideration of such relatedness. Moreover, we propose a context‐aware graph convolutional network for entity representation, which takes both the graph structure of the candidate entity and its relatedness with the mention context into consideration. Experimental results show that our model consistently outperforms the baseline methods on five widely used datasets.     

电网故障处置预案文本中的命名实体识别研究

电网故障处置预案是电网故障处置的重要参考,对电网故障处置预案文本中各类电力设备、名称编号等细粒度的关键实体信息进行抽取,是实现计算机学习理解预案内容并进一步支撑故障处置智能化的重要基础。文中提出一种基于深度学习的电网故障处置预案文本命名实体识别技术,首先采用字向量表征预案文本,然后将注意力机制以及双向长短期记忆网络相结合,有所侧重地提取实体词深层字符特征,最后采用条件随机场求解最优序列化的标注。算例表明:文中所提预案文本命名实体识别模型不依赖人工特征,能够自动高效地提取文本特征,准确识别预案文本中细粒度的实体词,满足预案文本中关键实体信息精确定位和识别的要求。     

液压-齿轮-齿条圆弧分型抽芯压铸模设计

给出了龙头体液压-齿轮-齿条圆弧分型抽芯压铸模实用结构，论述了模具的浇铸系统、结构特点和工作原理。该模具采用扇形龄轮-齿条机构实现龙头体铸件的侧向圆弧分型抽芯，同时通过相应的两套斜销滑块机构分别实现龙头体铸件另外两个方向的侧向分型抽芯。     

直齿圆柱齿轮温挤压成形的数值模拟

用优化后的凹模结构对直齿圆柱齿轮的温挤压成形进行了数值模拟 ,结果表明 ,以入模角为 180°、挤压筒内径等于直齿轮齿顶圆直径 ,且在齿根圆处不倒角为特点的凹模形式对齿形成形效果良好 ,此种凹模形式能够解决齿形角隅充不满的难题 ,非常适合直齿圆柱齿轮的挤压精密成形     

齿轮精密成形精整毛坯设计

根据被整形工件的大小,提出优化的冷整形量,据此来确定冷整形前坯料的大小和温热成形时模具的参数。