155 / 2023-10-19 20:12:38
Research on the Substation Alarm Event Model Based on Natural Language ParsingTechnology
eventalization; Natural language analysis; Neural network; Unsupervised learning; Density clustering
Final Paper
Xiaomeng Li / NARI Technology Development Co. Ltd
Hualiang Zhou / NARI Technology Development Co. Ltd
Zhantao Su / NARI Technology Development Co. Ltd.
Yifeng Wang / Nanrui Technology Co., LTD
Yuxin Chen / Nanrui Technology Co., LTD
Lu Lu / Nanrui Technology Co., LTD
Jing Wang / Nanrui Technology Co., LTD.
In view of the current low efficiency of manual processing of massive monitoring alarm information and the need for deepening the application of power grid intelligence technology, an autonomous identification method of power grid equipment operation and maintenance alarm events based on natural language processing technology is proposed, which integrates neural network and unsupervised learning. The text of substation equipment alarm signal is vectorized based on word2vec algorithm, the time-density correlation between multiple alarm signals is established based on DBSCAN algorithm, and the "eventalization" model of alarm signal sequence is constructed based on TF-IDF algorithm. This paper proposes an application method based on natural language processing technology combining neural network and unsupervised learning algorithm to screen key "eventalization" alarms from a large number of discrete alarms, so as to realize the response efficiency and reliable identification of power grid monitoring alarm events.
Important Date
  • Conference Date

    Dec 08

    2023

    to

    Dec 10

    2023

  • Nov 01 2023

    Draft paper submission deadline

  • Dec 10 2023

    Registration deadline

Sponsored By
IEEE IAS
Organized By
Southwest Jiaotong University (SWJTU)