Product Details

Product Description

Mingde Optoelectronics Artificial Intelligence Sorting equipemnt take the lead in introducing artificial intelligence methods such as deep convolutional neural networks(CNN) in the field of visible light photoelectic sorting to analyze and process material images,and through CNN partial connection,weight sharing,multiple cpnvolution kernels and other methods,during the training process, the multi-dimensional features of materials are automatically extracted to establish a database,whose sorting effect is far better than traditional photoelectric methods.

Model	Mineral particle size (cm)	Capacity (T/H)	Air pressure (Mpa)	Sorting accuracy	Optimized Carryover ratio	Power(kW)	Dimension(mm)	Weight(kg)
MAI-D4	3≤6	30~45	0.55	96	10:1	4.5	400026501760	2100
	1≤3	10~12	0.55
	0.5≤d≤1	6~8	0.5
MAI-D5	3≤6	38~52	0.55	96	10:1	5.0	400031601760	2250
	1≤3	12.5~15	0.55
	0.5≤d≤1	8~10	0.5
MAI-D6	3≤6	45~68	0.55	96	10:1	5.5	400036701760	2350
	1≤3	15~18	0.55
	0.5≤d≤1	9~12	0.5
MAI-S4	3≤6	35~50	0.55	99.8	20:1	6.0	485026502750	3000
	1≤3	12~14	0.55
	0.5≤d≤1	7~9	0.5
MAI-S5	3≤6	44~60	0.55	99.8	20:1	6.5	485031602750	3250
	1≤3	13.5~16	0.55
	0.5≤d≤1	9~11	0.5
MAI-S6	3≤6	48~75	0.55	99.8	20:1	7.0	485036702750	3500
	1≤3	17.5~21	0.55
	0.5≤d≤1	10.5~14	0.5

The above index is based on 15% impurity content quartz as an example,The specific index varies with the material and impurity content.

Product feature of AI sorting machine

1,it’s the first to introduce artificial intelligence means of neural network in the field of sorting,which solves the problem that color sorting machine can only separate according to simple criteria.

2, The sorting mode is established according to users’ sorting requirements to meet users’ diversified and personalized sorting requirements.

3,We own the self-developed software system and closed machine structure, the main internal components are all imported,which can adapt to the harsh environment requirements like high dust,high pollution, and high corrosion in the industry and mining area.It has a wider application range and longer life.

4,Flexible track-type material conveying system,with samll drop,large output,and suitable for the sorting of more materials.

5,The vibrating feeding part and the main part of the equipment adopt a split structure to avoid the impact of vibration generated during the feeding process on the host and make the equipment operation more stable.

6, the sorting effect can be continuously improved by learning mode, and the deep learning mode can be developed.

7,High intelligence,remote debugging,smart monitoring,remote service and software upgrading.

Sortable ores

Applicable sorting ore materials

Talc, wollastonite ,calcite, quartzite

Fluorite, Potassium feldspar, Magnesite, Lithium pyroxene

Phosphate ore, Gold ore, High crystal silicon, oxide copper ore

Barite, bauxite ,lead-zinc ore and fluorite, barite lead-zinc ore

Not limited to the above ores, eye visible distinctions are applicable to AI sorting machines!