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基于SVR的粮仓储粮重量在线检测模型

On-line Granary Storage Weight Detection Based on SVR

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【作者】 张德贤张苗张庆辉张元吕磊

【Author】 ZHANG De-xian;ZHANG Miao;ZHANG Qing-hui;ZHANG Yuan;L Lei;School of Information Science and Engineering,Henan University of Technology;Grain Information Processing and Control,Key Laboratory of Ministry of Education;

【机构】 河南工业大学信息科学与工程学院粮食信息处理与控制教育部重点实验室

【摘要】 粮仓储粮重量自动检测是国家粮食安全的重要保障技术.本文针对粮堆散粒体特性,建立了粮仓储粮重量与粮仓底面和侧面压强的数学关系,证明了基于压力传感器进行粮仓数量在线检测的可行性.提出了基于内外圈两圈布置的压力传感器布置模型和基于多项式展开的粮仓储粮重量检测模型,利用内外圈传感器输出值均值的多项式展开构建粮仓储粮重量估计.针对实仓检测中内外圈传感器输出值均值存在较大波动的问题,提出了基于SVR的粮仓储粮重量检测模型,给出了SVR输入项序列的具体提取方法,设计了具体的建模算法.实验表明,实验粮仓检测模型建模与预测结果的误差小于±3%,证明了所提出的粮仓储粮重量检测模型与方法的有效性,可以满足国家粮仓储粮重量检测的要求.

【Abstract】 Automatic detection of granary storage quantity is an important technology for national food security. In this paper,according to the characteristics of grain peaks,the m athem atical relationship between granary storage weight and the bottom/side pressure of granaries is established; the feasibility of the online granary storage quantity detection based on pressure sensors is also dem onstrated. Furtherm ore,a newgranary storage weight detection m odel based on polynom ial expansion is proposed by using pressure sensors arranged along the inner and outer rings. The polynom ial expansion of the average value of the pressure sensors is used to evaluate the granary storage weight. As the average value fluctuates inpractical warehouse detection,a granary storage weight detection m odel based on SVR is proposed. The detailed extraction m ethod for SVR input sequences is described,and specific m odeling algorithm is designed. Practical storage weight detection results showthat the detection accuracy of the proposed m odel is better than 97%,which dem onstrates that the proposed granary storage weight detection m odel is effective and well m eet the dem and of national granary storage quantity detection.

【基金】 国家高科技研究发展计划(863计划)(No.2012AA01608);国家科技支撑计划(No.2013BAD17B04);国家自然科学基金(No.U1404617);粮食信息处理与控制教育部重点实验室开放基金(No.KFJJ2016102);河南省高校科技创新团队(No.16IRTSTHN026)
  • 【文献出处】 电子学报 ,Acta Electronica Sinica , 编辑部邮箱 ,2018年05期
  • 【分类号】TP274
  • 【被引频次】10
  • 【下载频次】197
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