Research on self‑test and fault diagnosis mechanism of wireless intelligent pressure plate monitoring system

To address the issues of traditional substation pressure plates, such as reliance on manual inspection, delayed fault detection, and insufficient reliability, this paper proposes a wireless intelligent pressure plate monitoring system integrated with self-inspection and intelligent fault diagnosis mechanisms. Centered on non-intrusive sensing technology, the system constructs a distributed monitoring architecture by integrating wireless communication modules, enabling real-time collection of the switching state and connection reliability of pressure plates. The self-inspection mechanism ensures the accuracy of monitoring data and the stability of system operation through hardware circuit self-verification, communication link integrity detection, and data consistency check. The fault diagnosis mechanism combines an improved random forest algorithm with a multi-feature fusion strategy. By extracting key influencing factors including voltage level, load importance, and pressure plate type, it achieves hierarchical identification and early warning of faults such as loose connections, incorrect switching, and communication interruptions of pressure plates. Experimental verification shows that the system's self-inspection coverage rate reaches 100%, and the fault diagnosis accuracy exceeds97%, which can effectively shorten the fault response time, improve the intelligence level of operation and maintenance for secondary equipment in substations, and provide technical support for the safe and stable operation of power grids.