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Equipped with AI-powered RGB/MSI smart camera combination, the machine performs multi-dimensional defect identification by analyzing sunflower seeds in terms of color, size, shape and texture. The self-developed deep learning algorithm enables continuous optimization of defect recognition with new sample data.
Specifications
Model
Chute
Air Nozzle
Air Pressure (MPa)
Air Consumption (L/min)
Power (kW)
Voltage
Dimension (LWH)(mm)
Weight*(kg)
VG1
1
64
0.6~0.8
<1000
0.9
220V~ 50/60Hz
1255*2199*2076
680
VG4
4
256
0.6~0.8
<2000
2.9
220V~ 50/60Hz
2170*2199*2076
1150
VG6
6
384
0.6~0.8
<3000
4.4
220V~ 50/60Hz
2800*2199*2076
1480
VG8
8
512
0.6~0.8
<4000
5.9
220V~ 50/60Hz
3430*2199*2076
1840
VG10
10
640
0.6~0.8
<5000
7.3
220V~ 50/60Hz
4070*2199*2076
2180
VG12
12
768
0.6~0.8
<6000
8.8
220V~ 50/60Hz
4835*2199*2076
2550
Technical Features
Customized Optical Sorting Solution for Sunflower Seeds
The high-efficiency vibrating feeder ensures single-layer and even distribution of sunflower seeds to minimize overlapping.
Fully enclosed sorting chamber and electrical cabinet with industrial-grade dustproof design, suitable for high-dust working environments.
Mature and reliable integrated dust removal system guarantees long-term stable operation.
Modular structure with optional chute configurations: 1/4/6/8/10/12 lanes, flexibly matching different production capacities.
AI-empowered 4-in-1 Intelligent Optical Sorting System
Independently developed AI deep learning algorithm for ongoing recognition performance improvement via new samples.
High-resolution RGB color imaging system to capture subtle defects accurately.
High-brightness LED lighting system delivers clear and stable imaging.
Optional NIR camera or InGaAs-SWIR camera available.
Boasting industry-leading detection accuracy, it identifies various defects and foreign materials based on color, size, shape and texture:
