A Study on Non-Contact Multi-Sensor Fusion Online Monitoring of Circuit Breaker Contact Resistance for Operational State Awareness

Zheng Wang, Hua Zhang, Yiyang Zhang (), Haoyong Zhang, Jing Chen, Shuting Feng, Jie Guo and Yanpeng Lv
Additional contact information
Zheng Wang: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Hua Zhang: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Yiyang Zhang: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Haoyong Zhang: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Jing Chen: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Shuting Feng: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Jie Guo: Langfang Power Supply Company, State Grid Jibei Electric Power Company Limited, Langfang 065000, China
Yanpeng Lv: School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450000, China

Energies, 2025, vol. 18, issue 10, 1-19

Abstract: The contact condition of circuit breaker contacts directly affects their operational reliability, while circuit resistance, as a key performance indicator, reflects physical changes such as wear, oxidation, and ablation. Traditional offline measurement methods fail to accurately represent the real-time operating state of equipment due to large errors and high randomness, limiting their effectiveness for state awareness and precision maintenance. To address this, a non-contact multi-sensor fusion method for the online monitoring of circuit breaker circuit resistance is proposed, aimed at enhancing operational state awareness in power systems. The method integrates Hall effect current sensors, infrared temperature sensors, and electric field sensors to extract multiple sensing signals, combined with high-precision signal processing algorithms to enable the real-time identification and evaluation of circuit resistance changes. Experimental validation under various scenarios—including normal load, overload impact, and high-temperature and high-humidity environments—demonstrates excellent system performance, with a fast response time (≤200 ms), low measurement error (<1.5%), and strong anti-interference capability (SNR > 60 dB). In field applications, the system successfully identifies circuit resistance increases caused by contact oxidation and issues early warnings, thereby preventing unplanned outages and demonstrating a strong potential for application in the fault prediction and intelligent maintenance of power grids.

Keywords: non-contact monitoring; circuit breaker resistance; multi-sensor fusion; dynamic temperature compensation; fault prediction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/10/2667/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/10/2667/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:10:p:2667-:d:1661215

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().