AI Recognition Based Coal Conveying Bridge Unmanned Inspection System

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AI Recognition Based Coal Conveying Bridge Unmanned Inspection System

Intelligent IoT technologies such as video, infrared, vision, and gas analysis are employed to achieve monitoring, identification, and early warning functions. The system platform provides analysis, diagnosis, and interlocking control functions for issues in the coal conveying system, including belt misalignment/slippage, coal dust leakage, powder accumulation spontaneous combustion, localized dust generation, and analysis of decomposition gases from overheating.

Product Details

Key Technologies

◆Video surveillance monitors the operational status of field equipment to determine whether the conveyor belt trestle is misaligned or experiencing abnormalities; infrared monitoring of the coal conveyor belt trestle enables the diagnosis and alarm of heat sources; it also identifies and provides early warnings for accumulated coal dust and the presence of large foreign objects falling near the conveyor belt. ◆Multi-sensor fusion: Yes CO, H2S Such as harmful gases and PM10 Dust over-limit alarm; Realize the identification and early warning of temperature and humidity in the on-site environment and abnormal sounds from coal conveying equipment.

: Expected effect

◆Effectively detect early fire situations, accurately activate the sprinkler system, and prevent fire accidents on the coal conveying trestle. ◆The dry fog dust suppression system effectively eliminates dust and powder accumulation at chutes, coal drop points, and return belts, enhancing the comprehensive safety of the coal conveying trestle system.