Patent ID: 11860216
Assignee: QINGDAO TOPSCOMM COMMUNICATION CO., LTD
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 0:
1. A method for detecting a fault arc signal by using a convolutional neural network, comprising:
S1, filtering, by using three band-pass filters with different pass-bands, a sampled current signal to extract time-frequency eigenvectors;
S2, constructing a three-dimensional matrix based on the time-frequency eigenvectors;
S3, constructing a two-dimensional convolutional neural network model, and training the two-dimensional convolutional neural network model;
S4, performing, by using the trained two-dimensional convolutional neural network model, an online determination on the three-dimensional matrix to obtain an arc detection result, wherein an arc detection result of 0 indicates that no arcing occurs, and an arc detection result of 1 indicates that an arcing occurs;
S5, counting the number of fault half-waves in an observation time period ΔT based on the arc detection result; and
S6, comparing the number of the fault half-waves in the observation time period ΔT with a threshold, performing a tripping operation in a case that the number of the fault half-waves exceeds the threshold, and performing no operation in a case that the number of the fault half-waves does not exceed the threshold.