摘要
[目的]提高食品生产线黄桃自动分级方法的准确率和效率。[方法]在黄桃自动分级系统(机器视觉和高光谱技术)的基础上,提出一种融合改进YOLOv11与改进极限学习机的黄桃品质自动检测方法。外部品质图像通过CMOS传感器相机进行采集,通过改进YOLOv11模型识别缺陷,并结合果型指数与色泽判定外部品质。内部品质则通过高光谱仪采集,经特征筛选后,输入改进灰狼算法优化的极限学习机模型中检测可溶性固形物和硬度指标判定内部品质。结合外部品质和内部品质对黄桃进行分级。通过试验对其性能进行验证。[结果]试验方法可以实现食品生产线黄桃内外品质的有效检测,综合内部品质具有较高的分级准确率和效率,分级准确率大于95.00%,平均分级时间小于0.3 s。[结论]将机器视觉、高光谱技术以及智能算法相结合,可实现食品品质的快速无损检测。
[Objective]To improve the accuracy and efficiency of the automatic grading method for yellow peaches on the food production line[Methods]Based on the yellow peach automatic grading system(machine vision and hyperspectral technology),a new method for automatic detection of yellow peach quality is proposed,which integrates an improved YOLOv11 and an improved extreme learning machine(ELM).External quality images are captured by a CMOS sensor camera,and defects are identified using the improved YOLOv11 model.The external quality is determined by the fruit shape index and color.Internal quality is detected using a hyperspectral instrument,and after feature selection,the data is input into an ELM model optimized by an improved grey wolf algorithm to detect soluble solids and hardness as internal quality indicators.The yellow peach is graded based on both external and internal qualities.The performance of the method is verified through experiments.[Results]The experimental method effectively detects both the internal and external qualities of yellow peaches on the food production line,with a high grading accuracy and efficiency,achieving a grading accuracy greater than 95.00%and an average grading time of less than 0.3 seconds.[Conclusion]By combining machine vision,hyperspectral technology,and intelligent algorithms,rapid and non-destructive detection of food quality can be achieved.
作者
彭永杰
赵良军
龙绪明
PENG Yongjie;ZHAO Liangjun;LONG Xuming(Yibin Vocational and Technical College,Yibin,Sichuan 644001,China;Sichuan University of Science&Engineering,Yibin,Sichuan 644001,China;Southwest Jiaotong University,Chengdu,Sichuan 610016,China)
出处
《食品与机械》
北大核心
2025年第5期89-97,共9页
Food and Machinery
基金
四川省中央引导地方科技发展专项项目(编号:2024ZYD0300)
宜宾市科技计划项目(编号:2021ZYY001)。
关键词
食品生产线
黄桃
自动分级
机器视觉
高光谱技术
YOLOv11
极限学习机
food production line
yellow peach
automatic grading
machine vision
hyperspectral technology
YOLOv11
extreme learning machine
