A warning method for low‑voltage electrical safety hazard based on multi‑dimensional features and random forests

doi:10.19781/j.issn.1673-9140.2024.02.016

Home > Archive>Volume 39, Issue 2, 2024 >143-151. DOI:10.19781/j.issn.1673-9140.2024.02.016

A warning method for low‑voltage electrical safety hazard based on multi‑dimensional features and random forests
DOI:
                        10.19781/j.issn.1673-9140.2024.02.016
                    
CSTR:
                        [cstr]
                    
Author:
                        XIAO Xiangqi1,2XIAO Xiangqi
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
HU Junhua1,2HU Junhua
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
YE Zhi1,2YE Zhi
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
WU Wenxian1,2WU Wenxian
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
LUO Yujian1,2LUO Yujian
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
ZOU Sheng1,2ZOU Sheng
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
LUO Chen3LUO Chen
School of Electrical ＆ Information Engineering,Changsha University of Science ＆ Technology, Changsha 410114, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site

                    
Affiliation:(1.State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China; 2. Key Laboratory of Intelligent Electrical Measurement and Application Technology in Hunan Province, Changsha 410004, China; 3.School of Electrical ＆ Information Engineering,Changsha University of Science ＆ Technology, Changsha 410114, China)
Clc Number:TM501；TP183
Fund Project:

Article

Figures

Metrics

Reference

Cited by

Materials

Comments

Abstract:

As a common safety hazard in low-voltage electricity use, fault arcs are difficult to perceive effectively on the eve of failure due to their concealment and randomness. Existing protection methods usually take measures after the occurrence of faults, which can easily cause electrical fires. To address these issues, a warning method for low-voltage electrical safety hazard is proposed on basis of multi-dimensional features and random forests. Next, a random forest model is built and hyper-parameters are optimized, with the goal of minimizing node information entropy to complete model training, so that enhances the overall performance and learning efficiency of the model. Finally, experimental verification shows that the proposed method achieves a prediction accuracy of over 99.4% with different loads, and its prediction accuracy is higher than that of four traditional classification prediction models.

Key words:low-voltage electricity safety;fault arc;random forest algorithm;characteristic engineering

Get Citation

肖湘奇,胡军华,叶志,吴文娴,罗宇剑,邹晟,罗晨.基于多维特征与随机森林的低压用电安全隐患预警方法[J].电力科学与技术学报英文版,2024,39(2):143-151. XIAO Xiangqi, HU Junhua, YE Zhi, WU Wenxian, LUO Yujian, ZOU Sheng, LUO Chen. A warning method for low‑voltage electrical safety hazard based on multi‑dimensional features and random forests[J]. Journal of Electric Power Science and Technology,2024,39(2):143-151.

Copy

Article Metrics

Abstract:
PDF:
HTML:
Cited by:

History

Received:
Revised:
Adopted:
Online: May 29,2024
Published:

Get Citation

Related Videos

Share

Article Metrics

History

Article QR Code