In the traditional production of black tea, the sorting process plays a pivotal role in determining product quality and economic efficiency. With the integration of artificial intelligence (AI), the AD120 Primary Sorter and AT120 Precision Grader have emerged as a groundbreaking duo, redefining the workflow of black tea sorting. This article details how these two machines collaborate to transform raw tea leaves into premium-grade products through a seamless, automated process.

Stage 1: Preprocessing and Primary Sorting (AD120)

Objective: Remove stems, deteriorated leaves, and foreign materials to prepare for precision grading.

1. Preprocessing Phase

- Mechanical Kneading: Dried black tea leaves undergo mechanical kneading to break apart clumps, ensuring uniform dispersion for subsequent sorting.

- Preliminary Screening: Fine particles (<1mm) and non-tea impurities (e.g., sand, fibers) are simultaneously removed using vibration sieves.

2. AD120 Primary Sorting

- AI-Driven Recognition: Equipped with high-resolution cameras and Convolutional Neural Networks (CNN), the AD120 captures real-time images of tea leaves.

- Shallow Layers: Detect color variations (e.g., identifying brown, deteriorated leaves).

- Deep Layers: Analyze texture features (e.g., distinguishing stems from leaf connectors).

- Dynamic Ejection: High-speed pneumatic nozzles precisely eject stems (accounting for 10%-15% of raw material) and discolored leaves while preserving intact tea leaves.

- Return Material Characteristics: Post-sorting, the residual material contains≥60% stem-leaf connectors, which can be reprocessed or customized based on client requirements.

Stage 2: Precision Grading (AT120)

Objective: Classify tea leaves by size, shape, and quality to meet diverse market demands.

1. Input Material

- The pre-sorted tea from the AD120 is fed into the AT120 system.

2. AT120 Precision Grading

- Multi-Dimensional Analysis: Leveraging deep learning algorithms and advanced sensors, the AT120 evaluates:

- Size: Using optical sensors to measure leaf dimensions.

- Shape: Identifying round, semi-circular, or oval forms (classified as PEKO grade).

- Texture: Detecting subtle defects (e.g., cracks, uneven edges).

- Reinforcement Learning Optimization: The system continuously refines its sorting strategy based on real-time feedback, adapting to variations in leaf morphology (e.g., half-stem, half-leaf mixes).

- Output Grades:

- OP: Medium leaves (1-3mm).

- OPA: Wider leaves (≥3mm).

- OP1: Slender leaves (~1mm).

- PEKO: Round, semi-circular, or oval leaves.

3. Control and Stability

- Fuzzy PID Algorithm: Adjusts conveyor belt speed dynamically (fluctuation <±0.05m/s) to ensure uniform passage through the detection zone.

- Motion Compensation: Eliminates vibration errors during high-speed operation, achieving a positioning accuracy of±0.1mm.

Synergistic Advantages of the AD120-AT120 System

1. Enhanced Quality

- Minimizes leaf breakage and color degradation (reducing "black-to-dark-gray" shifts), preserving the tea’s original aroma and appearance.

- Removes 99% of residual stems and impurities, significantly boosting product purity.

2. Operational Flexibility

- Customizable deep learning models cater to diverse tea varieties (e.g., Keemun, Dianhong) and client-specific grading criteria.

- Handles complex materials (e.g., mixed stems and leaves) with adaptive sorting strategies.

3. Economic Efficiency

- Reduces labor costs by 30% through full automation.

- Cuts raw material waste by 20% via efficient impurity removal, directly enhancing market value.

The Future of Black Tea Production

The AD120 and AT120 color sorters exemplify how AI-driven technologies are revolutionizing traditional industries. By combining precision, adaptability, and efficiency, this dual-system workflow not only elevates black tea quality but also bridges the gap between heritage and innovation.

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