The online monitoring algorithm for leakage fire of new high voltage switchgear cabinet in substation has the phenomenon of incorrect collection of leakage data during the monitoring process. The completeness of fire information assessment is low

and the algorithm mechanism needs to be adjusted while monitoring

resulting in untimely warning and low monitoring accuracy. In response to this issue

online monitoring of leakage fires in the high voltage switchgear cabinet of the new substation is carried out. Firstly

leakage data is collected based on the leakage situation of the switchgear cabinet

the leakage information is judged based on the residual current

and accurate leakage area data is captured in a timely manner. The D-S evidence theory fusion algorithm is used to online monitor the fire situation of the obtained leakage data

construct an identification framework

extract similarity functions

judge the temperature threshold at which the fire occurs and complete the overall monitoring study. It is known according to the analysis results that the online monitoring method has strong monitoring and warning accuracy. Under the same conditions

the temperature difference of the fire signal collection is 1 ℃

the overall false alarm rate of the system is 0.001% and the residual current is 310 mA. The method can effectively monitor leakage information and fire occurrence and indicate its strong monitoring ability.