基于知识图谱的二次设备缺陷智能诊断与识别应用研究及实现

Research and Implementation of Intelligent Diagnosis and Recognition of Secondary Equipment Defects Based on Knowledge Graph

为了进一步规范缺陷信息录入并且提升消缺处置的效率,文章基于知识图谱的二次设备缺陷智能诊断与识别方法,通过利用历史消缺记录构建缺陷知识图谱,完成了缺陷信息自动填报、缺陷智能诊断及缺陷处置辅助决策功能,实现了对故障处置全过程的支撑。采用的技术实际应用效果一定程度上依赖于原始文本数据的质量,在后续应用时,需要持续迭代优化算法模型,以不断提高对二次设备功能缺陷智能诊断与辅助决策的建议采纳率。

In order to further standardize the defect information input and improve the efficiency of defect elimination and disposal,an intelligent diagnosis and identification method of secondary equipment defect based on knowledge graph is introduced.The defect knowledge graph is constructed by using historical defect elimination records,and the functions of automatic filling in defect information,intelligent diagnosis of defect and auxiliary decision of defect disposal are completed,and the support of the whole process of fault disposal is realized.The practical application effect of the adopted technology depends to some extent on the quality of the original text data.In the subsequent application,it is necessary to continuously iteratively optimize the algorithm model to continuously improve the acceptance rate of intelligent diagnosis and auxiliary decision of secondary equipment functional defects.