Patent ID: 11874317
Assignee: SCHNEIDER ELECTRIC INDUSTRIES SAS
Field: Electrical machinery, apparatus, energy (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 3:
4. The ground fault directivity detection method of claim 1, wherein
the ground fault directionality detection neural network is a trained neural network, and the training includes the following steps:
step 1, acquiring a ground fault current signal training sample set for training the ground fault directionality detection neural network;
step 2, providing a training sample in the ground fault current signal training sample set as an input to the ground fault directionality detection neural network;
step 3, calculating a label vector corresponding to the training sample by the ground fault directionality detection neural network;
step 4, determining a processing loss of the ground fault directionality detection neural network based on the label vector of the training sample;
step 5: if the processing loss is greater than or equal to a preset processing loss threshold, updating a parameter of the ground fault directionality detection neural network and performing steps 2 to 5 based on the updated ground fault directionality detection neural network, and if the processing loss is less than or equal to the preset processing loss threshold, stopping the training.