Carrier roller fault monitoring method and system based on optical fiber auscultation

By combining a fiber optic enhanced detector array and a fiber optic auscultation host with a deep learning model, the system collects and analyzes the sound signals of idler roller operation in real time. This solves the problems of insufficient signal sensitivity and limited recognition accuracy of existing fiber optic auscultation systems in idler roller fault monitoring, and achieves efficient and accurate idler roller fault monitoring and early warning.

CN121493540APending Publication Date: 2026-02-10HUANENG POWER INTERNATIONAL INC SHANGHAI SHIDONGKOU FIRST POWER PLANT
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Patent Information

Application Number
CN202511736257.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-25
Publication Date
2026-02-10

AI Technical Summary

Technical Problem

Existing fiber optic auscultation systems suffer from insufficient signal sensitivity, limited recognition accuracy, system dispersion, insufficient adaptability, and complex deployment in idler roller fault monitoring, making it impossible to achieve continuous monitoring and efficient fault location.

Method used

By employing an optical fiber enhanced detector array and an auscultation optical fiber host, combined with a deep learning model, the system collects the sound signals of idler roller operation in real time, extracts three types of complementary acoustic features, performs feature fusion and classification, realizes the probability distribution output of idler roller operation status, and issues anomaly alarms on the platform.

Benefits of technology

It enables continuous acoustic monitoring over long distances and at multiple points, improving the response sensitivity and positioning accuracy to local abnormal noises, significantly reducing the workload of manual inspections, providing early warning of idler roller failures, and possessing high integration and high identification accuracy.

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Abstract

The invention relates to a carrier roller fault monitoring method based on optical fiber auscultation, and the method comprises the steps: collecting and preprocessing a carrier roller operation sound signal in real time, and extracting three types of complementary acoustic features in the preprocessed sound signal in parallel to obtain three types of feature maps; performing normalization and size unification on the three types of feature maps, and then performing fusion to form a three-channel fusion image; inputting the three-channel fusion image into a pre-constructed deep learning model, performing feature learning and classification, and outputting probability distribution of the running state of the carrier roller; and according to the probability distribution of the running state of the carrier roller, abnormal alarm information is output, and the position of the carrier roller is marked. Compared with the prior art, the system has the advantages of being high in system integration degree and high in practicability.
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