水果智能分拣产线的现状与发展趋势

Status and Development Trend of Fruit Intelligent Sorting Production Line

针对果实分拣中存在识别精度低、单个果实信息处理时间长的问题,对国内外的水果智能分拣生产线进行研讨和分析。根据水果分拣产线的工作原理,结合工业机器人和视觉分拣技术,提出利用卷积神经网络(convolutional neural network,CNN)和使用光谱技术分析水果的化学性质等方法,对水果瑕疵检测和成熟度分拣进行分析,并分别对CNN和光谱分析技术在水果分拣中的应用发展趋势进行阐述。分析结果表明,该研究对提高水果瑕疵检测和分拣精度研究具有一定的实用价值。

Aiming at the problems of low recognition accuracy and long processing time of individual fruit information in the fruit sorting process,this study analyzes and forecasts the current fruit sorting production lines at home and abroad.According to the working principle,combining with the industrial robots and visual sorting systems,methods such as the use of convolutional neural network(CNN)and the use of spectroscopic techniques to analyze the chemical properties of fruits are carried out to conduct research on fruit defect detection and maturity sorting.Convolutional neural network and spectral analysis technology in fruit sorting application development trends are described separately.The results show that the research has certain practical value for improving the research of fruit defect detection and sorting accuracy.