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This article proposes an intelligent monitoring and fault warning technology scheme based on multidimensional perception to address the reliability issues of power plant generator outlet circuit breakers (GCBs). A real-time monitoring system is built by combining multiple sources of sensors, including temperature, gas pressure, vibration, and current waveform. The ARM7TDMI microprocessor hardware platform and the μ C/OS-II real-time multitasking operating system work together to enable dynamic acquisition and analysis of circuit breakers’ functioning state. The system adopts a hierarchical architecture design, covering data awareness, edge computing, cloud interaction and other functional modules, and innovatively introduces priority scheduling algorithms to optimize the execution efficiency of self-diagnosis tasks, significantly improving the accuracy of identifying minor and serious hardware failures. The research results indicate that this technology can effectively warn of typical faults such as contact wear and SF6 leakage, reduce unplanned downtime risks through state assessment and alarm mechanisms, and provide theoretical support and engineering practice reference for intelligent operation and maintenance of power systems.

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Research on Intelligent Monitoring and Fault Warning Technology for Power Plant Generator Outlet Circuit Breakers Based on Multidimensional Perception

  • 会议论文

  • 发表日期：

    2026年

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  • Kuiyuan Xie,
  • Xiaodong Li,
  • Yisheng Chen,
  • Weiqin Zhan,
  • Hong Cao

摘要

This article proposes an intelligent monitoring and fault warning technology scheme based on multidimensional perception to address the reliability issues of power plant generator outlet circuit breakers (GCBs). A real-time monitoring system is built by combining multiple sources of sensors, including temperature, gas pressure, vibration, and current waveform. The ARM7TDMI microprocessor hardware platform and the μ C/OS-II real-time multitasking operating system work together to enable dynamic acquisition and analysis of circuit breakers’ functioning state. The system adopts a hierarchical architecture design, covering data awareness, edge computing, cloud interaction and other functional modules, and innovatively introduces priority scheduling algorithms to optimize the execution efficiency of self-diagnosis tasks, significantly improving the accuracy of identifying minor and serious hardware failures. The research results indicate that this technology can effectively warn of typical faults such as contact wear and SF6 leakage, reduce unplanned downtime risks through state assessment and alarm mechanisms, and provide theoretical support and engineering practice reference for intelligent operation and maintenance of power systems.