Open AccessResearch on quality problems management of electric power equipment based on knowledge–data fusion method
Author(s) -
Han Xiao,
Jiang Jun,
Zhang Chaohai,
Wen Zhe,
Chen Guang,
Liu Yang
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.0832
Subject(s) - computer science , switchgear , quality (philosophy) , data mining , electric power system , process (computing) , information flow , reliability engineering , electric power , tracing , data quality , sensor fusion , rough set , smart grid , key (lock) , power (physics) , artificial intelligence , engineering , metric (unit) , operations management , philosophy , physics , linguistics , electrical engineering , epistemology , quantum mechanics , mechanical engineering , computer security , operating system
The quality of electric power equipment directly affects and decides the securable and stable operation of the power grid. Revealing the quality problem causes and influencing factors are considered as the key point to improve and guarantee the quality of power apparatus. However, the data of power supplies quality problems have the features of diversity and complexity. It is of great value to take the full advantages of the multi‐source heterogeneous data, especially the possess flow information tracing time and space, to locate vulnerable processes, problem causes and influencing factors. This study put forward a data source system, which includes general information, quality problem information, process flow information and other supplementary information. Furthermore, an improved neural network model utilising knowledge–data fusion method is proposed. In this way, the efficiency and accuracy of analysis for quality problems is available and enhanced. To verify the validity of the knowledge–data fusion model, a case study with 2084 sample data of gas‐insulated switchgear is carried out, proving help to strengthen the management and control measures of power equipment quality problems.