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基于依存句法分析的电力设备缺陷文本信息精确辨识方法
作者:
作者单位:

1.浙江大学电气工程学院,浙江省杭州市310027;2.浙江华云信息科技有限公司,浙江省杭州市310012

作者简介:

邵冠宇(1994—),男,硕士研究生,主要研究方向:电网文本挖掘、电力系统自然语言处理。
王慧芳(1974—),女,通信作者,博士,副教授,主要研究方向:智能电网多模态数据挖掘、电网状态检修、继电保护与控制等。E-mail:huifangwang@zju.edu.cn
吴向宏(1980—),男,助理工程师,主要研究方向:电力系统软件开发。

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Precise Information Identification Method of Power Equipment Defect Text Based on Dependency Parsing
Author:
Affiliation:

1.College of Electrical Engineering, Zhejiang University, Hangzhou310027, China;2.Zhejiang Huayun Information Technology Co., Ltd., Hangzhou310012, China

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    摘要:

    电力设备缺陷文本包含大量设备缺陷历史信息,从文本中精确辨识缺陷信息,可提供对于设备的故障率建模和健康状态评价问题的有效指导。引入依存句法分析技术,提出“左贪心”出栈规则和基于神经网络的依存关系状态转移分析模型,实现了电力设备实际缺陷文本和缺陷分类标准文本的依存句法树构建,并结合缺陷文本特点提出了电力设备依存句法树的剪枝、切分和重构方法。同时,提出了基于依存关系的树匹配算法,实现实际缺陷和标准缺陷依存句法树的匹配。以主变压器缺陷文本为例,研究了基于依存句法分析的缺陷信息辨识方法的可行性和有效性。结果表明,所提方法相比于其他树匹配算法和语义相似度计算方法在效率和准确性上有明显提升。

    Abstract:

    Power equipment defect text contains a lot of historical defect information of the equipment. The accurate information identification from defect text can provide effective guidance for equipment failure rate modeling and health status evaluation. By introducing dependency parsing technology, “left-greedy” out stack rule and neural network based dependency state transition analysis model are proposed. This paper implements the dependency-syntax-tree construction of actual defect text and defect classification standard text of power equipment, and proposes a method of pruning, segmentation and reconstruction of power equipment dependency syntax tree using the characteristics of the defect text. Meanwhile, dependency relationship based tree matching algorithm is proposed to match actual defects with standard defect dependency syntax trees. The feasibility and effectiveness of defect information identification method based on dependency syntax analysis is illustrated with the example of main transformer defect text. The results show that the efficiency and accuracy of the proposed method are improved substantially compared with other tree matching algorithms and semantic similarity computation methods.

    表 1 状态转移框架下依存句法分析模型处理具体缺陷文本过程Table 1 Handling process of specific defect text based on dependency parsing model in state transition framework
    表 6 Table 6
    表 2 实际历史缺陷文本缺陷信息辨识准确性统计Table 2 Statistics of defect information extraction accuracy for actual historical defect text
    表 3 Table 3
    表 5 Table 5
    表 4 Table 4
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引用本文

邵冠宇,王慧芳,吴向宏,等.基于依存句法分析的电力设备缺陷文本信息精确辨识方法[J].电力系统自动化,2020,44(12):178-185. DOI:10.7500/AEPS20190401001.
SHAO Guanyu,WANG Huifang,WU Xianghong,et al.Precise Information Identification Method of Power Equipment Defect Text Based on Dependency Parsing[J].Automation of Electric Power Systems,2020,44(12):178-185. DOI:10.7500/AEPS20190401001.

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历史
  • 收稿日期:2019-04-01
  • 最后修改日期:2020-03-11
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  • 在线发布日期: 2020-06-18
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