The loop resistance characteristic of gas-insulated metal-enclosed switchgear is an important indicator for evaluating its safe operation. However

traditional DC resistance detection methods require power-off operations on power equipment

which leads to reduced power supply reliability

high operation and maintenance costs

and the inability to obtain equipment operation health data.The existing online monitoring technology is difficult to accurately strip inductive interference. To this end

it collects the AC time-domain waveforms of the equipment operation

uses the adaptive quantile weighted least squares method to equivalentially calculate the results highly consistent with the DC resistance values

and integrates the geometric cascade forest algorithm to achieve the judgment of the equipment status trend and fault early warning. Ultimately

it realizes the precise assessment and predictive maintenance of the power equipment status without interrupting the power supply.