Partial discharge voiceprint multi-mode detection method

Abstract

The invention discloses a partial discharge voiceprint multi-mode detection method, which comprises the following steps that voiceprint matrix detection nodes are set, on-site multi-mode signals are collected, and the voiceprint matrix detection nodes comprise an ultrasonic sensor, an infrared thermal imager, a temperature and humidity sensor and a camera; preprocessing the signal, extracting voiceprint features, and constructing a multi-modal feature vector; calculating three-dimensional coordinates of a partial discharge source, and performing spatial mapping verification by combining video imaging; and fusing the features and carrying out classification identification, and outputting a partial discharge type and a risk level. Through voiceprint matrix arrangement, temperature, humidity and video imaging data are combined, and the sensitivity and the anti-interference capability of partial discharge detection are remarkably improved. A noise reduction algorithm and a voiceprint feature fusion technology are adopted, so that complex environmental noise and real discharge signals can be effectively distinguished; the multi-modal data collaborative analysis can evaluate the insulation state of the equipment in real time, the false alarm rate is reduced to below 2%, and unmanned intelligent inspection of the transformer substation is supported.

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