This system utilizes AI image algorithms to analyze the temperature field and multi‑spectral images of the conveyor belt, accurately identifying longitudinal tears and abnormal wear, and enabling two‑level alarms with automatic interlock shutdown.
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The system supports automatic calibration and self-cleaning, helping maintain stable detection performance with reduced manual intervention.
The non-working surface is monitored through both thermal imaging and visible light, improving detection reliability under different operating conditions.
A variety of parameters and algorithms are used for monitoring, enabling more accurate identification and analysis of abnormal features.
The system can automatically monitor, identify, and trigger alarms. It also supports access to the main control system and can realize linkage shutdown when required.
Tear images and videos are automatically saved, allowing users to review abnormal events and inspection records at any time.
| Category | Parameters | Category | Parameters |
|---|---|---|---|
| Applicable belt speed | 0-10m/s | Working temperature | -30 - 60℃（low-temperature version -50 - 60℃) |
| Applicable belt width | 650-3000mm | Storage temperature | -40 - 80℃（low-temperature version -50 - 80℃) |
| Atmospheric pressure | 80-106Kpa | Relative humidity | ≤ 95%RH（without condensation） |
| Working power supply | 85-264VAC（customized） | Continuous working time | 7×24h |
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