苹果内外品质在线无损检测分级系统设计与试验

目前苹果品质检测分级机械存在结构复杂、价格昂贵以及不能兼顾内外品质的缺点。苹果的内部品质和外部品质都是决定苹果价值的关键因素,故该研究根据静态条件下的试验分析,设计了苹果内外品质在线无损检测分级系统。该系统主要由哑铃式滚子、机器视觉外观品质检测系统模块、近红外内部品质检测系统模块、分级模块以及控制系统组成。在机器视觉外部品质检测模块设计中,为了增大苹果有碰伤部位和无碰伤部位之间的对比度,通过采集有碰伤部位和无碰伤部位的反射率光谱,确定在730 nm处两者的反射率差异最大,并以此选用波长为730 nm的红色LED光源作为机器视觉模块的光源。为获得苹果整个表面信息,苹果在向前运动的过程中完成自转,并利用算法将单个苹果3个运动状态下的图像进行提取和合成,随后对图像进行高斯滤波,大津法二值化以及轮廓提取处理,当该苹果判断为有碰伤时,直接发送剔除指令,当判断为无碰伤,对轮廓提取后图像进行圆拟合处理,并利用拟合圆直径得到该苹果的大小。近红外内部品质检测系统模块设计中,对比2种近红外检测结构,并以试验确定了将探头和光源布置在下的设计方式。最终,通过试验验证得到了系统的在线检测性能,系统对于苹果有无碰伤检测总体正确率为94%,大小检测的相关系数为0.964 6,均方根误差为2.28 1 mm,苹果内部可溶性固形物含量所建立模型的校正集相关系数为0.950 8,校正集均方根误差为0.342 6%,预测集相关系数为0.949 2,预测集均方根误差为0.448 7%。单个苹果的检测时间为0.71 s。整机具有体积小、结构简单、成本较低的优点,适用于农户和中小型企业。

Design and experiment on grading system for online non-destructive detection of internal and external quality of apple

Abstract: At present, grading machinery for quality inspection of apple has the disadvantages of complex structure, expensive price and unbalanced internal and external qualities. However, both the internal and external qualities are vital to its value. The grading device for online non-destructive testing of internal and external quality of apple is thus designed in this research pursuant to the experimental analysis under static conditions. The device is composed of dumbbell roller, chain conveyor module, belt drive module, machine vision system module for detection of external quality, near-infrared internal quality testing module, grading module and control system. In the design of machine vision system module for detection of external quality, in order to increase the contrast ratio between the bruised and non-bruised parts of apple, the reflectivity spectra of bruised and non-bruised parts were collected, and it was determined that the largest difference of the reflectivity between the two parts is at the position of 730 nm, and thus a red LED (light emitting diode) light source with a wavelength of 730 nm is selected as the light source of vision module. In order to get the integrated surface information, apple completed the rotation in the process of forward movement, and the self-designed segmentation and synthesis algorithm was utilized to extract and synthesize the images of a single apple under 3 states of motion. Then the images were processed by Gaussian filtering, QTSU binarization and contour extraction. When the apple is judged to have bruising, a rejection instruction is directly sent. When it is determined that there is no bump, the contour extraction image is subjected to circle fitting processing, and the size of the apple is obtained by fitting the circle diameter. The near-infrared internal quality testing module is mainly used to detect the soluble solids of apple, and the modelling effects of arranging the probe respectively on the upper part and the lower part were contrasted so as to determine the best modelling method under static condition. Experiments show that it will be better to arrange the probe at the lower part. Finally, the on-line detection performance of the device was verified by experiments. The accuracy of the device for detection of bumps on apples was 94%, the correlation coefficient for size detection was 0.9646, and the root mean square error was 2.281 mm. Then, an on-line model was established for measuring the content of soluble solids in apple. The correlative coefficient of the calibration set was 0.950 8, the root mean square error of the correction set was 0.342 6%, the correlation coefficient of the prediction set was 0.949 2, and the root mean square error of the prediction set was 0.448 7%. The detection time for a single apple was 0.71 s. The device has the advantages of small size, simple structure and low cost, which is suitable for the needs of farmers and middle-sized and small-sized enterprises.