An insulator micro-damage early warning system and method based on acoustic-electric timing characteristics

Abstract

The application provides an insulator micro-damage early warning system and method based on acoustic-electric timing characteristics, and relates to the technical field of online monitoring of power transmission lines, and comprises the following steps: collecting acoustic signal data and electrical signal data generated by an insulator string during operation in real time and respectively performing adaptive noise filtering processing to obtain denoised acoustic signal data and denoised electrical signal data; performing feature extraction on the denoised acoustic signal data and the denoised electrical signal data to obtain time-domain synchronism features, frequency-domain correlation features and time-frequency domain features and combining the features to form an acoustic-electric joint feature vector; then inputting the time sequence convolution attention network model to obtain the running state of the insulator string and the corresponding probability; and generating a micro-damage early warning signal when the running state is a latent defect and the probability exceeds a preset threshold in a plurality of continuous time windows. The beneficial effect is that the application can accurately distinguish between real insulator defect signals and random environmental noise, and ensure the reliability of signal analysis under complex working conditions.

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