The development of an intelligent comprehensive detection instrument for circuit breakers in power systems and its key technologies - Weimin Guan; Han Hu; Chao Sun; Jie Ji (Energy Informatics)
Abstract To improve the accuracy and reliability of circuit breaker detection in power systems, this study proposes an intelligent detection instrument. The instrument addresses key issues found in traditional methods, such as limited real-time performance, inadequate data integration capabilities, and poor environmental adaptability. The instrument integrates multimodal data fusion technology to comprehensively analyze electrical parameters, mechanical characteristics, and environmental factors, enabling full awareness of the circuit breaker’s status. Additionally, this study optimizes the fault diagnosis algorithm, enhancing detection stability and robustness. By improving the model architecture, the computational burden is reduced, making the system more suitable for real-time monitoring and resource-constrained environments. Experimental results demonstrate that the intelligent detection instrument outperforms existing methods in terms of accuracy, detection efficiency, and anti-interference capabilities. It can more effectively identify the operational status of circuit breakers while maintaining high detection performance under complex operating conditions. Compared to traditional methods, the proposed solution shows significant advantages in reducing false alarms, optimizing detection speed, and improving environmental adaptability. Therefore, the study provides efficient and stable technical support for intelligent circuit breaker detection in power systems, laying a solid foundation for the development of smart grids.