Large-scale pre-training method, device and equipment for multi-modal data of power transformation main equipment
The invention discloses a large-scale pre-training method, device and equipment for multi-modal data of power transformation main equipment, and the method comprises the steps: obtaining initial multi-modal data, carrying out the preprocessing of the initial multi-modal data, obtaining the multi-mod...
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creator | LUO MU ZHANG PENG HAN JINSI JIANG GUANGXIN LI ZHONGPENG XIA WEISHANG GAN JINRUI LIU HAO |
description | The invention discloses a large-scale pre-training method, device and equipment for multi-modal data of power transformation main equipment, and the method comprises the steps: obtaining initial multi-modal data, carrying out the preprocessing of the initial multi-modal data, obtaining the multi-modal data, and enabling the multi-modal data to comprise the online monitoring data and voiceprint data of the power transformation main equipment; respectively carrying out hidden layer feature extraction on the online monitoring quantity data and the voiceprint data, and determining a first hidden layer feature of the online monitoring quantity data and a second hidden layer feature of the voiceprint data; performing enhancement processing on the first hidden layer feature and the second hidden layer feature, and performing splicing processing to obtain a target feature; and performing multi-modal interaction processing based on the target features, constructing a loss function based on a multi-modal interaction pr |
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XIA WEISHANG ; GAN JINRUI ; LIU HAO</creatorcontrib><description>The invention discloses a large-scale pre-training method, device and equipment for multi-modal data of power transformation main equipment, and the method comprises the steps: obtaining initial multi-modal data, carrying out the preprocessing of the initial multi-modal data, obtaining the multi-modal data, and enabling the multi-modal data to comprise the online monitoring data and voiceprint data of the power transformation main equipment; respectively carrying out hidden layer feature extraction on the online monitoring quantity data and the voiceprint data, and determining a first hidden layer feature of the online monitoring quantity data and a second hidden layer feature of the voiceprint data; performing enhancement processing on the first hidden layer feature and the second hidden layer feature, and performing splicing processing to obtain a target feature; and performing multi-modal interaction processing based on the target features, constructing a loss function based on a multi-modal interaction pr</description><language>chi ; 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respectively carrying out hidden layer feature extraction on the online monitoring quantity data and the voiceprint data, and determining a first hidden layer feature of the online monitoring quantity data and a second hidden layer feature of the voiceprint data; performing enhancement processing on the first hidden layer feature and the second hidden layer feature, and performing splicing processing to obtain a target feature; and performing multi-modal interaction processing based on the target features, constructing a loss function based on a multi-modal interaction pr</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
title | Large-scale pre-training method, device and equipment for multi-modal data of power transformation main equipment |
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