基于图像检测的茶叶含水率检测烘干系统

The image-based tea moisture content detection and drying system utilizes a dual-model architecture of YOLOv5 and an interpretable surrogate model to achieve real-time and accurate detection and temperature control of tea moisture content. This solves the problems of unstable tea drying quality and high equipment costs in small and medium-sized tea gardens, and reduces equipment investment and maintenance difficulty.

CN122408429APending Publication Date: 2026-07-17DONGGUAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
DONGGUAN UNIV OF TECH
Filing Date
2026-04-28
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing tea drying technology relies on manual experience and lacks real-time and objectivity, resulting in inaccurate detection of tea moisture content. Furthermore, fixed temperature modes cannot adapt to the differentiated drying needs at different moisture content stages, leading to unstable tea quality. This is especially problematic in small and medium-sized tea gardens where equipment costs are high or maintenance is complex.

Method used

A tea moisture content detection and drying system based on image detection is adopted, including a visual acquisition module, a depth recognition module, a data platform module, and a drying intelligent control module. The system uses a YOLOv5 object detection-classification joint model and an interpretable surrogate model to detect the moisture content of tea. Images are acquired in real time through industrial cameras, and a dual-model architecture of basic classification network and interpretable surrogate model is constructed to achieve accurate detection of tea moisture content and temperature control.

Benefits of technology

It enables real-time and accurate detection of tea moisture content and temperature control, reduces equipment costs, adapts to the actual budget and operation and maintenance capabilities of small and medium-sized tea garden production lines, provides interpretable prediction results, facilitates process optimization and quality traceability, and avoids over-drying or under-drying.

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Abstract

本发明公开了一种基于图像检测的茶叶含水率检测烘干系统及方法，属于图像检测技术领域。系统包括智能终端，通信连接有视觉采集模块、深度识别模块、数据中台模块和烘干智控模块。深度识别模块内置基础分类网络与可解释代理模型：基础分类网络采用YOLOv5目标检测‑分类联合模型，对茶叶图像进行感兴趣区域定位并输出含水率整数百分等级；可解释代理模型基于四项核心视觉特征，通过二次多项式显式公式输出连续含水率预测值。视觉采集模块安装于出料端输送带上方，实时采集烘干后茶叶图像；烘干智控模块根据预测值与目标含水率区间的偏差，通过PID控制算法动态调节烘干温度，含水率不合格的茶叶经返工回路回送至进料端进行二次烘干。
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Citation Information

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