摘要
针对通过敲击判断西瓜品质会因品种不同而造成误判的问题,构建振动检测系统,获取皇冠、早佳8424、京欣和硒砂4个品种西瓜频响函数,利用PNN神经网络模型实现西瓜品种的鉴别,准确率达92%以上。同时,利用逐步多元线性回归分析,通过频响函数的主要共振峰频率与糖度的关系,分别建立各品种西瓜的糖度预测模型,确定系数均在0.86以上。对预测集样本先鉴别品种再预测糖度,对于品种鉴别准确的瓜,其糖度测量误差小于6.2%;而对于品种鉴别错误的瓜,由于选用了错误的预测模型,测量误差较大。在上述基础上,可对未知市售西瓜进行品种鉴别,进而自动选取适当相应模型进行糖度测量。
In order to solve the problem of consumers misjudgment by hitting watermelon because of different watermelon varieties,a vibration detection system was built to get the frequency response functions of＂Huang guan＂,＂Zaojia8424＂,＂Jng xin＂and ＂Xisha＂watermelon.Using the PNN neural network model achieved the identification of watermelon varieties,and the accuracy was more than92%.At the same time,according to the relationship between the sugar content and the main resonant peak frequency,the prediction model of the sugar content of each variety of watermelon was established by stepwise multivariate linear regression analysis,and the coefficient were all above 0.86.The prediction set samples were identified and then predicted the sugar content.The measurement error of the sugar content of the watermelons which were identified accurately was less than 6.2%.The measurement error of the sugar content was larger for the watermelon which was identified mistakenly because of error prediction model.On the above basis,the unknown watermelons in the market could be identified,and then the appropriate corresponding model was selected automatically to measure the sugar content.
作者
庄为
李臻峰
宋飞虎
李静
汪迪松
朱冠宇
ZHUANG Wei;LI Zhen-feng;SONG Fei-hu;LI Jing;WANG Di-song;ZHU Guan-yu(School of Mechanical Engineering of Jiangnan University, Wuxi, Jiangsu 214122, China;Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi , Jiangsu 214122, China)
出处
《食品与机械》
CSCD
北大核心
2018年第4期140-145,179,共7页
Food and Machinery
基金
国家自然科学基金(编号:515082290)
江苏省产学研联合创新资金(编号:BY2014023-32)
江苏省食品先进制造装备技术重点实验室开放课题(编号:FM-201406)
关键词
振动检测
西瓜
品种
糖度
共振峰频率
vibration testing
watermelon
varieties
sugar content
formant frequency
