Online Detection And Classification System Integration And Experiments Of Kiwi-fruit

Fruit detection and classification technology plays a key role in many processes.It can make different levels of fruit sold in different prices which can highly increase the price of fruit,improve the income of farmers.In order to realize the online non-destructive testing and classification of kiwifruit quality,the integration and experimental study on the detection and classification system for the size and sugar content of kiwifruit were carried out based on machine vision and Visible/Near Infrared spectroscopy technology.The specific research contents and results are as follows:(1)On line measuring mechanism design of kiwi fruit size and sugar.First of all,the functional requirements of the online detection mechanism were determined according to the analysis of the research status at home and abroad.Through the comparison of different programs,overall scheme of the online detection mechanism was determined.The machine vision system mainly included the camera,camera mounting bracket,light source and position sensor.LED patch strip was selected as the light source of the image acquisition through the comparison of several different light sources.The adjustable angle camera mounting bracket was designed for the inclined conveying platform.And the support angle could be adjusted in the range of 120 degrees.The spectrum detection was mainly composed of spectrometer,halogen light source,fiber optic moving mechanism,distance measuring sensor and so on.In order to realize the adjustment of the detection distance of the spectrum,a linear guide rail slide mechanism was designed,which was driven by a single chip microcomputer to control the motor up and down.And the stroke of the linear guide rail is 100 mm.(2)Control system design for on line detection and classification system.According to the working process and the performance requirements of the control system,the overall scheme of the control system was defined.The methods of image and spectrum acquisition and processing were selected and the relevant program was compiled.The hardware and software of the whole detection and grading device were integrated,and the software debugging of the system was completed.Finally,the control requirements of the system were achieved.The operation interface of the system software was designed.The whole control system of the testing and grading device was mainly composed of various types of sensors,motor driver,MCU and PC relay,etc.When the system running,sensors transmitted signals to the MCU through the I/O port.The MCU and host computer achieved real-time communication through the serial port and the classification results were intuitively displayed through the software operate interface.(3)Condition optimization experiment of online detection and classification system.Firstly,through the comparison of the correlation between long axis,short axis,image rectangle,contour pixel area and the existing main classification index weight of kiwifruits,grading of fruit appearance size basis for image pixel area was determined.Experiments were conducted to obtain the pixel area of kiwifruit under different speeds.Results shows that the best transmission speed for kiwifruit appearance size detection is 800 r/min.Based on the analyzed of modeling between the data obtained from the spectral and the actual value of the sugar,the best spectral detection distance of kiwifruit is 3 mm.Similarly based on the analysis of modeling with different delivery speed,the best transportation speed of the conveyor belt for kiwifruit sugar detection was 900 r/min.The correlation coefficient of the model is Rc=0.93,Rp=0.86 at the speed of 900 r/min and the spectral detection distance is 3mm.Considering the appearance size detection and sugar detection speed test results,choosing the 900 r/min as the conveying speed in classification according to the two integrated information.(4)Grading index determination and system comprehensive validation test.Reference to the existing national standard,relevant tests were designed to determine the grading index for kiwifruit under different factors.Comprehensive performance evaluation test for the online detection and classification system in the best working condition was conducted.The results indicated that the average accuracy rate of appearance size classification is 94.2%,sugar contents 88.4% and fusion level index 92.5% in this grading system.The design of the kiwifruit grading system provides foundation and basis for the fusion and classification of multi features.