Consistency check of power fault multi-source heterogeneous big data under common factor structure

Yong Shi; ZhengXiong Mao; Yan Xu Jin; Yan Shi; Mei Zhang

doi:10.1117/12.2690152

7 September 2023 Consistency check of power fault multi-source heterogeneous big data under common factor structure

Yong Shi, ZhengXiong Mao, Yan Xu Jin, Yan Shi, Mei Zhang

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 1279049 (2023) https://doi.org/10.1117/12.2690152
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

The current method of power data consistency test based on gray correlation analysis verifies the consistency of data by measuring the shape and distance between data sequences, which leads to low accuracy of the test due to high data redundancy. In this regard, the consistency check of power fault multi-source heterogeneous big data under common factor structure is proposed. The Kalman filter algorithm is used to reduce the redundancy of power fault data, and the consistency discriminant criterion is established to realize the consistency test of power fault multi-source heterogeneous data by discriminating the cofactor relationship between the data. In the experiments, the proposed method is verified for testing accuracy. The analysis of the experimental results shows that the proposed method is used to test the consistency of power fault data, and its test error is low and has a high test accuracy.

Citation Download Citation

Yong Shi, ZhengXiong Mao, Yan Xu Jin, Yan Shi, and Mei Zhang "Consistency check of power fault multi-source heterogeneous big data under common factor structure", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 1279049 (7 September 2023); https://doi.org/10.1117/12.2690152

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available