Abstract: In order to improve the oyster automatic processing level, an oyster weight grading control system based on STM32 microcontroller was designed in this paper. The control system was comprised with varieties of functional modules, such as data acquisition module, grading control module, driver module and humancomputer interaction module. Oyster weight was used as the grading standard, while the weight and position information of the weighing tray acted as the primary control conditions. The dynamic weighing model of genetic algorithm optimizing neural network (GA-BP) and dynamic tracking and positioning method were adopted to accurately obtain oyster weight and weighing tray position, and humancomputer interaction was carried out by using touch screen, which could realize weighing and grading integration. The test results showed that the maximum weighing error of the control system was 0.8 g, and the grading accuracy reached 95% under the maximum operation speed, which could better realize the rapid weighing and grading of oysters.

Key words: oyster, weight grading, GA-BP algorithm, dynamic weighing, control system

摘要： 为提高牡蛎自动化加工水平，基于STM32单片机设计牡蛎重量分级控制系统。该控制系统由数据采集模块、分级控制模块、驱动模块和人机交互模块组成，以牡蛎重量为分级标准，称重托盘重量和位置信息为主要控制条件，采用遗传算法优化神经网络(GA-BP)动态称重模型和动态追踪定位方式，准确获得牡蛎重量和称重托盘位置，使用触摸屏进行人机交互，可实现称重分级一体化。试验结果表明，该控制系统的称重误差最大为0.8g，在最大运行速度下，分级准确率达到95%，较好地实现牡蛎快速称重分级。

关键词: 牡蛎, 重量分级, GA-BP算法, 动态称重, 控制系统