苹果在线分级系统设计与试验  

Design and experiment of an online grading system for apple

作　　者：张庆怡[1] 顾宝兴[1] 姬长英[1] 方会敏 郭俊[1] 沈文龙[1] 

机构地区：[1]南京农业大学工学院,江苏南京210031 [2]山东省农业机械科学研究院,山东济南250100

出　　处：《华南农业大学学报》2017年第4期117-124,共8页Journal of South China Agricultural University

基　　金：江苏省自然科学基金(BK20140720);中央高校基本科研业务费专项(KYZ201325)

摘　　要：【目的】根据苹果采摘机器人结构和作业特点设计与其配套的在线分级系统,满足实时分级需求。【方法】通过预分级机构剔除果径在等级外的苹果,减少视觉分级的无用功;利用力传感器获取苹果质量信息并确定质量等级;通过机器视觉技术实现苹果大小和腐烂面积的检测;借助Matlab和VS2008开发图像处理算法和界面控制程序;构建基于CAN总线的分布式控制网络。对苹果进行综合分级试验。【结果】苹果实际直径与检测直径的决定系数为0.990 3,实际质量与检测质量的决定系数为0.999 6,实际腐烂面积与检测腐烂面积的决定系数为0.985 5,综合分级成功率可以达到89.71%,连续分级时单果平均分级时间为2.89 s。【结论】该分级系统工作稳定,方便扩展,有较高的分级效率和分级精度,可以满足采摘机器人的实时分级需求。【Objective】 To design a matched online grading system based on the structure and working behavior of the apple harvesting robot,and meet the needs of grading apples in real time. 【Method】The pre grading principle was proposed to eliminate apples with diameters below standard which could improve the grading efficiency. Apple weight was measured by a force sensor and the weight grade was determinated. Apple size and rot area were detected using the machine vision technology. The image processing algorithm and interface control program were developed using Matlab and VS2008. The distributed control network was constructed based on CAN bus. Comprehensive grading tests on apples were performed. 【Result】The determination coefficient of apple actual diameter and detected diameter was 0.990 3, the determination coefficient of the actual weight and test weight was 0.999 6, the determination coefficient of actual rotting area and detected rotting area was 0.985 5. The success rate of comprehensive grading reached 89.71%, and the average grading time per apple was 2.89 s during continuous grading.【Conclusion】The apple grading system is stable, easy to expand, highly efficient and accurate, and can meet the real-time grading needs of the apple harvesting robot.

关 键 词：采摘机器人 预分级 在线实时分级 机器视觉 图像处理算法 综合分级 

分 类 号：S233.74[农业科学—农业机械化工程]