酿酒原粮大米中碎米含量测定的不确定度评定
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摘要
利用大米外观测定仪,通过图像处理技术得到米粒的图像并判断米粒的大小、整米、大碎米和小碎米,使用大米外观测定仪来自动计算大米碎米含量的实验。列举出实验中可能影响检测结果各个分量的不确定度,建立合成不确定度的数学模型,计算和评估各个分量的不确定度对检测结果的影响。从实验的计算数据分析来看,影响测定酿酒原粮大米中碎米含量的不确定度其最大分量来源于样品重复性测定和仪器测定的精密度,因此选择精度高的大米外观测定仪器、增加平行测定的次数、提高操作水平是保证实验数据准确度的关键。
In the experiment, rice kernel image was obtained by use of appearance tester through image processing technology, then the size of rice kernels, unbroken kernels, broken kernels and small broken kernels were judged, and broken kernel content was calculated automatically. The uncertainties of each component probably influencing the determination were listed, the mathematic model of synthesized uncertainties was set up, and the uncertainties of each component were calculated and their influence on the determination was assessed. Through the analysis of the calculated data in the experiment, it was found that sample repeated measurement and instrument precision were the biggest component sources influencing the determination. Accordingly, the selection of high-precision appearance tester, the increase of parallel determination times, and the improvement of operating capability were the keys to ensure the accuracy of the experimental data.
In the experiment, rice kernel image was obtained by use of appearance tester through image processing technology, then the size of rice kernels, unbroken kernels, broken kernels and small broken kernels were judged, and broken kernel content was calculated automatically. The uncertainties of each component probably influencing the determination were listed, the mathematic model of synthesized uncertainties was set up, and the uncertainties of each component were calculated and their influence on the determination was assessed. Through the analysis of the calculated data in the experiment, it was found that sample repeated measurement and instrument precision were the biggest component sources influencing the determination. Accordingly, the selection of high-precision appearance tester, the increase of parallel determination times, and the improvement of operating capability were the keys to ensure the accuracy of the experimental data.
引文
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[8]董婉婉,聂连芝,郭乾玲,等.探讨酿酒原粮中淀粉测定的不确定度因素[J].酿酒科技, 2018(5):65-70.
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[2]谢结珍.不确定度评定在水泥检测中的应用[J].建材与装饰,2016(41):47-49.
[3]全国粮油标准化技术委员会.粮油检验碎米检验法:GB/T 5503—2009[S].北京:中国标准出版社,2009.
[4]全国法制计量管理计量技术委员会.测量不确定度评定与表示:JJF 1059.1—2012[S].北京:中国标准出版社,2013.
[5]苏尔进,谭雪,潘玉梅,等.分光光度法测定水中总磷含量结果不确定度评定[J].大众科技,2017,19(12):12-15.
[6]聂连芝,张良东,王录.白酒工业废水中氨氮的测定不确定度因素的探讨[J].酿酒,2017,44(5):64-68.
[7]宋江,陈津津.微量移液器示值误差测量不确定度评定[J].计量与测试技术,2017,44(12):121-122.
[8]董婉婉,聂连芝,郭乾玲,等.探讨酿酒原粮中淀粉测定的不确定度因素[J].酿酒科技, 2018(5):65-70.
[9]谢结珍.不确定度评定在水泥检测中的应用[J].建材与装饰,2016(41):47-49.