In the coal, metal mines, metallurgy, building materials and other industrial fields, the conveyor belt is the "artery" of material transportation, and its safety and efficiency directly affect the stability of the production chain. However, foreign objects on the conveyor belt (such as iron pieces, wood blocks, barrel sealing cloth, plastic products, mining tool residues, etc.) may cause serious accidents such as equipment jamming, belt tearing and even fire. The traditional manual inspection mode has problems such as low efficiency, high misjudgment rate and great safety hazards. With the breakthrough of industrial intelligent technology, the foreign object removal system based on AI visual recognition and robot collaboration is reshaping the operation mode of material sorting in mine tunnels.

1. System technical architecture and core principles

The foreign object removal robot system consists of a three-level architecture of perception layer, decision layer and execution layer to form a closed-loop control:

Perception layer (visual system): combined with the acquisition module and the recognition module.

Acquisition module: uses a high-precision 3D industrial camera (structured light mode) and a combined light source to collect 3D point cloud data and high-definition images of the conveyor belt surface in real time (such as a comparison of wood and ore, with recognition accuracy at the pixel level). The AI ​​algorithm uses transfer learning technology to build a feature library covering more than 300 types of foreign objects, and achieves centimeter-level recognition of ironware (recognition accuracy > 99.2% in magnetite interference scenarios), wood, rubber products, etc.

Identification module: Equipped with the self-developed CRM-CNN algorithm, relying on the large database of mineral foreign objects accumulated by MINGDER Optoelectronics for deep learning, accurately locate the three-dimensional coordinates (depth, direction, posture) of foreign objects, and the recognition and exclusion rate of foreign objects with a length of > 50cm is ≥ 95%.

Decision layer (early warning system): The edge computing unit analyzes foreign object information in real time, completes foreign object classification and coordinate positioning within 2ms, and dynamically plans the grasping path in combination with the material flow rate. The independently developed trajectory prediction algorithm can compensate for the coordinate offset caused by conveyor belt vibration (error < ± 3mm). According to the size and weight of the foreign object, the grasping mode is dynamically selected (automatic grasping, early warning shutdown + remote operation, manual intervention).

Execution layer (robotic arm system): The modularly designed six-axis collaborative robot is equipped with an electromagnetic-vacuum dual-mode end effector. Iron foreign objects use magnetic suction devices, and non-metallic foreign objects are switched to vacuum suction cups. The average response time of the execution unit is <0.8 seconds, and the single grab cycle is <2.5 seconds. Foreign objects are transferred to the recovery device without stopping. In the early warning mode, the conveyor belt is stopped by the IO signal, and the sound and light alarm prompts manual intervention.

2. Typical industrial scenario application practice

1. Coal power industry (coal transportation system)

Pain points: Metal objects such as detonator residues and anchor fragments can easily cause the crusher to jam, and wooden debris can cause abnormal belt friction coefficient

Solution: Deploy a double-station robot system in front of the coal crusher, equipped with a detection module to identify metal parts in the coal flow. Data from a 2×1000MW power plant shows that there are 2,175 dangerous objects per year. If the system intercepts them, the equipment failure rate can be reduced by 73%.

2. Alumina plant (ore pretreatment)

Challenge: Steel filter mesh fragments (size 5-30cm) mixed in red mud can easily cause damage to the high-pressure diaphragm pump

Innovative application: Deploy a foreign object sorting robot at the outlet of the vibrating screen, and cooperate with detection technology to capture non-magnetic stainless steel fragments. For an annual production of 800,000 tons of alumina, the cost of spare parts replacement can be reduced by more than 2 million yuan per year.

3. Cement industry (raw material transportation)

Special needs: It is necessary to distinguish between normal agglomerated clinker (allowed to pass) and foreign objects

Technological breakthrough: Develop a classification model based on the feature recognition of agglomerated clinker and foreign objects, and judge the agglomeration properties by the surface characteristics of the material. The misgrab rate can be reduced from 15% to 1.8%.

4. Iron ore, copper ore, lead and zinc ore (tunnel transportation)

Compound scenario: mixed metal and non-metallic foreign objects, iron parts are easily disturbed by ore, and work in a high dust environment

Engineering practice: The robot arm is equipped with a dust cover, and the visual system is integrated with an air curtain cleaning module. The equipment is isolated and protected, the foreign object recognition rate is ≥92%, 4,000+ iron parts are intercepted annually, and belt tearing accidents are reduced by 70%.

3. Technical and economic analysis

Take a coal mine with a capacity of 10 million tons as an example:

Benefit calculation:

Avoid belt tearing accidents: save 800,000 to 1.5 million yuan in maintenance costs annually

Reduce labor costs: replace 6 inspection posts, save 600,000 yuan in labor costs annually

4. Safety and environmental protection

Equipment safety:

Multiple alarm mechanisms (self-inspection, abnormal shutdown), failure rate ≤1%;

Dynamic obstacle avoidance in the movement trajectory of the robotic arm to prevent misoperation.

Safety management system:

Pre-job training for operators to strengthen risk source identification and emergency response capabilities;

Regular inspections by full-time safety officers to form a closed-loop management system.

Environmental protection:

Zero pollution emissions throughout the entire process (no wastewater, waste gas, or waste residue);

Equipment materials comply with RoHS standards and are green manufacturing.

MINGDER Foreign Objects Removal Robot System promotes the transformation of mine sorting from "passive disposal" to "active prevention and control" through the promotion and application of deep integration of AI + robots. Its technical solution is perfectly applicable to multiple industries such as coal power, metallurgy, and building materials, with both high efficiency and economy. With the popularization of 5G+TSN (time-sensitive network) technology, the system response delay is expected to be compressed to milliseconds in the future, and an intelligent protection network covering the entire process of ore mining, processing and transportation will be built. This technological innovation not only brings significant economic benefits, but also sets a new benchmark for the process industry in terms of intrinsic safety.