There are many factors that affect the effect of ore sorting, mainly including the following aspects: 1. Ore properties: The physical properties (such as hardness, density, humidity, particle size distribution) and chemical properties (such as mineral composition, chemical activity) of the ore are the key factors affecting the sorting effect. Different ores require sorting methods suitable for their characteristics. 2. Ore grade: The higher the content of valuable minerals in the ore, the better the quality of the concentrate obtained after sorting. Conversely, low-grade ore may require more complex sorting processes to reach the standard of economic utilization.   3. Sorting equipment: The performance, maintenance and operation level of the equipment directly affect the sorting effect. Efficient and stable equipment can improve sorting accuracy and processing capacity. 4. Process parameters: The setting of parameters such as feed rate, water flow rate, vibration frequency, etc. during the sorting process has a significant impact on the sorting effect. Reasonable process parameters can optimize the sorting effect. 5. Environmental conditions: Environmental factors such as temperature and humidity may also affect the sorting results, especially for minerals that are sensitive to the environment. 6. Complexity of ore: If the ore contains multiple minerals, the interaction between them may make sorting more difficult, and comprehensive sorting technology is needed. 7. Ore uniformity: Ore uniformity affects the stability of the sorting process. Inhomogeneous ore may lead to unstable sorting results. 8. Type and rate of impurities: The type and rate of impurities in the ore will also affect the sorting effect, especially those impurities that interfere with the sorting process. 9. Operator skills: The operator's experience and skills have an important impact on the sorting effect. Skilled operators can better control the sorting process. 10. Pretreatment before sorting: Pretreatment processes such as crushing and grinding have an important influence on the particle size distribution and surface properties of the ore, which in turn affects the sorting effect. MINGDE AI intelligent sorting machine takes the lead in using artificial intelligence means such as deep convolutional neural network (CNN) to analyze and process material images in the field of visible light photoelectric sorting, and automatically extracts multi-dimensional features of materials to establish a database through CNN local connection, weight sharing, multi-convolutional kernel and other methods in the training process, and the sorting effect is far better than that of traditional sorting methods,and it has outstanding performance in ore pretreatment, low-grade ore enrichment, and complex ore sorting.  

Overview Ore foreign body removal robots are an automated equipment that has been widely studied and applied in the mining field in recent years with the development of artificial intelligence and machine vision technology. They are mainly used in the process of ore mining and processing to automatically identify and remove foreign matter mixed in the ore, so as to improve production efficiency and product quality and ensure the stable operation of the production line. Technical Realization The core technologies of ore foreign body removal robots include image recognition, machine learning, deep learning, and robotic arm control. The ore images are captured by a high-resolution camera installed on the conveyor belt, and then image processing technology is used to classify the ore, analyze the particle size, and identify foreign bodies. These robots are usually equipped with artificial intelligence algorithms such as deep convolutional neural networks (CNN), which can automatically extract the multi-dimensional features of the ore, such as texture, color, gloss, shape, etc., and compare them with the pre-trained database to achieve accurate foreign body identification and positioning. Scenes to Be Used The application scenarios of ore foreign body removal robots are very wide. They can play a role in various links of ore mining, crushing, grinding, ore dressing, etc. Especially in the ore transportation link, such as belt conveyor, the robot can monitor and remove foreign bodies in the transportation process in real time, which greatly ensures the continuity and stability of production. The foreign body removal robot launched by MINGDE Optoelectronic uses advanced image recognition algorithms and machine learning technologies, enabling it to continuously learn and optimize recognition models and adapt to complex and changing material conditions. Economic Benefits and Social Value The application of ore foreign body removal robots has brought many economic benefits to enterprises, such as improving production efficiency, reducing costs, reducing safety hazards, etc. At the same time, it has also promoted the development of mining towards intelligence and automation, and helped to achieve green mine construction and sustainable development. Conclusion In summary, the application prospects of ore foreign body removal robots are very optimistic. With the continuous advancement of technology and the growth of market demand, such robots will play a greater role in the mining field and become an important force in promoting the development of intelligent mining. At the same time, its wide application will also have a profound impact on improving production efficiency, reducing production costs, and ensuring mine safety.