The application discloses a
discharge detection device and method for a general high-
low voltage switch cabinet for mines, and belongs to the technical field of switch cabinet detection. The device comprises a modularized sensor
assembly, a
signal acquisition unit, an
edge computing node unit and an upper monitoring platform, and adopts a UHF sensor, an
ultrasonic sensor and a transient ground
voltage sensor for cooperative detection. The method comprises multi-source
signal synchronous acquisition,
adaptive denoising based on a
sparrow search algorithm optimization, double-domain
feature extraction,
discharge type identification based on an attention-enhanced
convolutional neural network, and multi-sensor
information fusion and hierarchical early warning based on evidence theory. The application compensates for the blind area of a single detection method through
cooperative work of multiple types of sensors, improves the denoising effect through adaptive parameter optimization, enhances the recognition accuracy through double-domain features and an attention mechanism, and improves the diagnosis reliability through multi-
sensor fusion, so that accurate detection and intelligent diagnosis of local
discharge of a mine switch cabinet are realized.