The product models of existing companies are mainly stored in a neutral geometry model file
format. However, the neutral geometry model lacks assembly feature semantics crucial for …

The conventional knowledge graph can only deal with binary relations, while knowledge of
bridge crane faults contains a large number of multi-nary relations of “multiple phenomena …

Equipment spot-inspection records are essential information sources supporting fault reason
analysis. However, there is a lack of effective mining of root cause information in equipment …

The Operations Knowledge Base provides integrated services for operations knowledge
from different cloud service providers, including troubleshooting experience, configuration …

In order to tackle the challenge of inadequate comprehension by cooperative robots during
assembly tasks, we present an innovative algorithm that leverages Graph Convolutional …

常规的知识图谱仅能够处理二元关系, 而故障知识包含大量“多现象-多原因-多方法”
的多元耦合关系, 如果**制转化将会破坏关系的完整性, 造成严重的信息失真. 对此 …

A graph convolutional network (GCN) is proposed to solve the problems such as complex
target attributes and unstructured data during target threat assessment of air combat and …

现有企业的产品模型主要以中性几何模型文件格式储存. 由于中性几何模型是以点, 线,
面等几何语义形式来储存信息, 在实际装配过程中, 中性几何模型不具有装配特征语义 …

设备点检记录是支撑故障原因分析与处理的重要信息来源, 目前亟需对设备点检故障中的根因
信息进行有效挖掘, 以提升设备预防性维护的可靠性. 鉴于此, 首次将因果科学论引入制造领域 …

为研究解决空战目标威胁评估问题时目标属性复杂, 数据非结构化等问题, 提高评估效率,
提出图卷积网络(graph convolutional network, GCN) 的解决方法, 并引入改进的指标相关性 …