Ai Deep Learning Shellfish Optical Sorter-Track-Type, For Seafood.
| Model | Cameras | Air Pressure | Power(KW) | Voltage | Weight (kgs) | Carryover | Dimension (mm) |
| ZLD30-C2L1 | 2 | 0.6~0.8 Mpa | 2.5 | 220V/50Hz | 470 | ≥30:1 | 2952*900*1632 |
| ZLD60-C4L1 | 4 | 0.6~0.8 Mpa | 3 | 220V/50Hz | 780 | ≥30:1 | 2864*1200*1632 |
| ZLD60-C8L2 | 8 | 0.6~0.8 Mpa | 5 | 220V/50Hz | 980 | ≥100:1 | 3618*1332*2495 |
| ZLD120-C8L1 | 8 | 0.6~0.8 Mpa | 3.5 | 220V/50Hz | 1200 | ≥30:1 | 3750*1750*1950 |
| ZLD120-C16L2 | 16 | 0.6~0.8 Mpa | 7.5 | 220V/50Hz | 1500 | ≥100:1 | 3900*2205*2500 |
| ZLD180-C12L1 | 12 | 0.6~0.8 Mpa | 5.5 | 220V/50Hz | 1400 | ≥30:1 | 3500*2650*2200 |
| ZLD180-C24L2 | 24 | 0.6~0.8 Mpa | 10.9 | 220V/50Hz | 1900 | ≥100:1 | 4000*2650*3200 |
Application: Specifically designed for sorting shelled or dehulled products such as snail meat, shellfish meat, and other seafood meats.
Core Technology: Utilizes AI deep learning combined with high-resolution cameras to distinguish quality products from impurities based on color, shape, and texture.
Primary Functions: Effectively removes shell fragments, foreign materials (stones, wood chips), deteriorated meat, substandard products, and other defects.
Material Adaptability: Engineered for complex materials that are irregular in shape, fragile, and surface-moist. The track-type conveyor system ensures stable material flow, preventing tumbling and overlapping, thereby guaranteeing consistent and reliable identification performance.
High-Precision Identification: Equipped with AI deep learning algorithms capable of establishing dedicated sorting models to accurately identify subtle defects in color, texture, and other quality parameters.
Application Fields: Widely used in snail noodle processing, deep processing of aquatic products, prepared seafood dishes, and other food processing industries.
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