Journal of Electrical Engineering and Automation

The ultra-high voltage (UHV) converter valve cooling system is a critical component ensuring normal operation of converter valves. In practical applications, frequent failures occur due to system complexity and environmental factors. This paper improves fault diagnosis methods for UHV converter valve cooling systems by proposing a multi-sensor fusion-based diagnostic solution. By integrating data from temperature, pressure, flow rate, and other sensors, this approach enhances diagnostic accuracy and real-time performance through data mining and pattern recognition techniques. Experimental results demonstrate that the improved method significantly improves system fault detection response speed and recognition precision, providing effective assurance for safe operation of UHV converter valves.

UHV converter valve; Cooling system; Fault diagnosis; Sensor fusion; Data mining