一种用于长距离输送的托辊故障定位方法、装置及设备
By establishing an acoustic scenario model and a fault detection model for roller abnormalities in a long-distance conveyor system at high altitudes, and combining deep learning and microphone array signal processing, precise location and data storage of roller faults were achieved. This solved the problems of inspection robots being unable to locate faults accurately and wireless networks losing data, thus improving the efficiency and accuracy of fault diagnosis.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUADIAN HEAVY IND CO LTD
- Filing Date
- 2025-09-03
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, inspection robots cannot accurately locate faulty rollers in long-distance conveyor systems at high altitudes, and wireless network failures lead to data loss, affecting the efficiency and accuracy of fault diagnosis.
By collecting vibration and acoustic signals from the idler rollers, an abnormal acoustic scenario model and a fault detection model for the idler rollers are established. Combining deep learning and microphone array signal processing positioning algorithms, the positioning information returned by the robot is used to achieve preliminary positioning and data storage of the faulty idler rollers.
It improves the accuracy and efficiency of idler roller fault location, avoids the need for manual diagnosis, solves the problem of inspection robots being unable to locate faults when they leave the fault location, and ensures data integrity when the wireless network fails.
Smart Images
Figure CN121180665B_ABST