知识图谱构建技术在电力变压器设备智能运行检测领域的研究与应用

Boyi Zhang, Xinghua Liu, S. Ji, Xuejie Yang, Tongping Xie, Yang Yu, Fei Li
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引用次数: 0

摘要

基于知识图谱的问答方法已成为自然语言处理领域的一个研究热点,并逐渐在电力领域得到应用。为了解决电力运维人员在进行变压器设备巡检过程中存在的非结构化文本数据使用难、设备知识应用深度浅等问题,本文提出了变压器设备知识图谱的技术框架,采用结构化文本的智能识别与提取方法,并建立了装备语义相似度的计算模型。在此基础上,验证了变压器设备状态评估报告自动审计、辅助诊断和设备故障知识识别的功能。实验结果表明,基于知识图谱的故障缺陷文本识别方法提高了故障缺陷文本识别的准确性,为提高现场设备的运维效率提供了新的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research and application of knowledge graph construction technology in the field of intelligent operation inspection of power transformer equipment
The question answering method based on knowledge atlas has become a hot research field in natural language processing, and has been gradually applied in the field of electric power. In order to solve the problems such as the difficulty of using unstructured text data and the shallow application depth of equipment knowledge, which exist in the process of power operation and maintenance personnel carrying out transformer equipment inspection, this paper puts forward the technical framework of transformer equipment knowledge map, adopts the intelligent identification and extraction method of structured text, and establishes the calculation model of equipment semantic similarity. On this basis, this paper verifies the functions of automatic audit of transformer equipment status evaluation report, auxiliary diagnosis and recognition of equipment fault knowledge. The experimental results show that the recognition method based on knowledge atlas improves the accuracy of fault defect text recognition, and provides a new idea for improving the operation and maintenance efficiency of field equipment.
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