Metallurgical enterprises use belt conveyors as the main equipment for ore transportation on site, but there are faults such as scratches, tears, and foreign objects during production and use. Causing a huge impact on safety production.
     The current solution is to manually inspect and add various sensors for prevention, but the results vary greatly, with occasional major accidents occurring. Not only is it difficult to detect or prevent major accidents with belts, but it is also difficult to timely avoid situations such as tearing and blocking of materials, and on-site operations by inspection personnel pose significant personal safety hazards. How to reduce and eliminate the occurrence of major belt accidents is an urgent need to be addressed in safety production. Through the core artificial intelligence algorithm and application algorithm, combined with the industry-leading edge computing AI neural network chip hardware solution, our company will thoroughly solve the transportation accidents such as belt conveyor tearing by classifying data, establishing research and development models, and in-depth training learning through scientific and technological means and excellent technology for the operation structure of belt conveyor in the metallurgical industry.

“Deep learning+machine vision”

    By utilizing the two major branch technologies of "deep learning" and "machine vision" in artificial intelligence, and using machine vision software with rich functions, the system can continuously optimize internally, achieving a virtuous cycle of "template learning → detection → template enrichment → detection more accurate → template enrichment → detection more accurate". Utilize objective big data to adjust front-end processes and improve production efficiency.

Introduction to Al Intelligent Analysis Terminal

     The AI intelligent analysis terminal is the core equipment of this system. This device can learn and master the characteristics of things through AI for on-site detection and analysis.

     ● High definition image acquisition function, real-time playback, and historical playback;
     ● AI intelligent image analysis combined with neural networks. Through deep learning, various belt tearing conditions (tearing, deviation, loopholes, etc.) can be detected
     ● Can learn and improve the fault model again
     ● Can define historical alarm conditions, and do not alarm for tolerable vulnerabilities and tears;
     ● Customized alarm levels and graded alarms;
     ● Linkage signal output for convenient linkage with other equipment;
     ● Equipped with automatic detection and recognition. Automatic alarm. Once the conveyor belt tears, it will immediately sound and light an alarm and send out a linkage control signal;
     ● At the same time as the alarm, capture and save images of the tearing of the conveyor belt in a fixed folder for easy viewing by users. Analyze specific issues and fix them (keep historical records for more than 3 months).

Pictures for on-site use

device