Asset maintenance prediction using infrared and regular images

A method for predicting a time to a failure condition of an asset includes a first model, trained to reconstruct input image pairs to resemble a healthy condition asset. Similarity coefficients are generated for respective historical image pairs that include a visible-light and infrared light image...

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Bibliographic Details
Main Authors Tiago Bertoni Scarton, Tarcisio Pereira, Eduardo Dias Felicio Junior, Thiago Bianchi
Format Patent
LanguageEnglish
Published 29.05.2024
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Summary:A method for predicting a time to a failure condition of an asset includes a first model, trained to reconstruct input image pairs to resemble a healthy condition asset. Similarity coefficients are generated for respective historical image pairs that include a visible-light and infrared light image by use of the reconstructed image pair by the first model as a similarity base and the respective historical image pairs include a timestamp of image capture. A second model is trained to predict a time to a failure condition of the asset based on similarity coefficients and timestamps of real-time image pair capture, timestamps of an asset failure condition, and similarity coefficients of the respective historical images. Responsive to receipt of a first real-time image pair, the method computes a predicted time to the failure condition of the asset.
Bibliography:Application Number: GB20230016185