基于粮温时空相关性的储粮数量监管方法研究
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摘要
针对我国储备粮人工稽核费时、费工等问题,提出了基于粮温时空相关性的储粮数量监管方法。首先,分析粮堆测温平面的自相关性与互相关性,检测粮堆异常发生的日期与平面;然后,分析粮堆异常日期内异常平面上测温线的自相关性,检测发生异常的测温线;接着分析异常测温线上测温点的自相关性,检测并统计异常点的个数;最后,根据异常点个数判定异常种类,进而实现储粮数量监管。在3个储粮区(低温区、中温区、高温区)中分别选取粮仓粮温进行相关性分析,根据分析结果设定测温平面自相关系数阈值为0. 8,互相关系数变化率阈值区间为[-0. 15 d~(-1),0. 15 d~(-1)];测温线的自相关系数阈值为0. 8;测温点的自相关系数阈值为0. 8;同时分析结果显示,短周期内测温线与点的互相关性无法作为异常判定依据。进行了储量监管试验,试验结果表明,基于粮温时空相关性的储粮数量监管方法不仅能够实现储粮数量监管,同时能够检测出粮堆发热等异常变化。
The supervision and verification of grain bulks is an important segment during storage.Reliable reserves monitoring method for grain storage can effectively guarantee national grain quantity security. To solve the problems such as time consuming,labor cost and other problems in the manual audit of reserves,a monitoring method for grain storage quantity based on correlation analysis was proposed. Firstly,the autocorrelation and intercorrelation of the temperature measurement planes in the grain bulks were analyzed, so that the abnormal date and planes were detected. Secondly, the autocorrelation and the intercorrelation of temperature measurement lines in the abnormal date were analyzed,and the abnormal lines were detected in the abnormal date. Then the autocorrelation and intercorrelation of the temperature measurement points in the abnormal temperature line were analyzed.The number of abnormal points was counted,and the type of abnormal occurrence and the abnormal proportion were determined according to the number. At the same time,the granaries were selected in three storage grain areas: low temperature zone,medium temperature zone and high temperature zone for correlation analysis. According to the analysis results,the threshold of autocorrelation coefficient of temperature measurement plane was set to be 0. 8,the threshold of change rate of intercorrelation coefficient was [-0. 15 d~(-1),0. 15 d~(-1)]; the threshold of autocorrelation coefficient of temperature measurement line was 0. 8; and the autocorrelation coefficient of temperature measurement point was 0. 8.Meanwhile,the analysis results showed that the correlation between temperature measurement lines and points in short period can not be used as an anomaly criterion. The supervision test of grain storage was carried out. The test results showed that the grain storage supervision method based on the correlation analysis can not only realize the reserves monitoring,but also detect the local heating and other anomalies of grain bulk. The purpose was to analyze the correlation coefficient of grain temperature data in the granaries of several different grain storage areas,monitor the quantity of grain and provide a theoretical basis for the analysis of grain data in different regions.
The supervision and verification of grain bulks is an important segment during storage.Reliable reserves monitoring method for grain storage can effectively guarantee national grain quantity security. To solve the problems such as time consuming,labor cost and other problems in the manual audit of reserves,a monitoring method for grain storage quantity based on correlation analysis was proposed. Firstly,the autocorrelation and intercorrelation of the temperature measurement planes in the grain bulks were analyzed, so that the abnormal date and planes were detected. Secondly, the autocorrelation and the intercorrelation of temperature measurement lines in the abnormal date were analyzed,and the abnormal lines were detected in the abnormal date. Then the autocorrelation and intercorrelation of the temperature measurement points in the abnormal temperature line were analyzed.The number of abnormal points was counted,and the type of abnormal occurrence and the abnormal proportion were determined according to the number. At the same time,the granaries were selected in three storage grain areas: low temperature zone,medium temperature zone and high temperature zone for correlation analysis. According to the analysis results,the threshold of autocorrelation coefficient of temperature measurement plane was set to be 0. 8,the threshold of change rate of intercorrelation coefficient was [-0. 15 d~(-1),0. 15 d~(-1)]; the threshold of autocorrelation coefficient of temperature measurement line was 0. 8; and the autocorrelation coefficient of temperature measurement point was 0. 8.Meanwhile,the analysis results showed that the correlation between temperature measurement lines and points in short period can not be used as an anomaly criterion. The supervision test of grain storage was carried out. The test results showed that the grain storage supervision method based on the correlation analysis can not only realize the reserves monitoring,but also detect the local heating and other anomalies of grain bulk. The purpose was to analyze the correlation coefficient of grain temperature data in the granaries of several different grain storage areas,monitor the quantity of grain and provide a theoretical basis for the analysis of grain data in different regions.
引文
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[14]张德贤,杨铁军,傅洪亮,等.基于压力传感器的粮仓储粮数量在线检测方法[J].中国粮油学报,2014,29(4):98-100.ZHANG Dexian,YANG Tiejun,FU Hongliang,et al. An on-line detection method of granary storage quantity based on pressure sensor[J]. Journal of the Chinese Cereals and Oils Association,2014,29(4):98-100.(in Chinese)
[15]秦瑶,陈洁,方广有,等.雷达层析成像技术对粮仓储量信息的探测[J].电波科学学报,2010,25(1):66-72,201.QING Yao,CHEN Jie,FANG Guangyou,et al. Radar tomography technology to detect reserves of barn[J]. Chinese Journal of Radio Science,2010,25(1):66-72,201.(in Chinese)
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[19]赫振方,赵玉霞,曹阳,等.平房仓粮堆温度时空分布的基本统计特征分析[J].粮食储藏,2010,39(4):15-20.HAO Zhenfang,ZHAO Yuxia,CAO Yang,et al. Statistical character on temporal and spatial distributing of grain temperature in warehouse[J]. Grain Storage,2010,39(4):15-20.(in Chinese)
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[21]安西友.鲁西南地区均温型谷物冷却机控温储藏稻谷生产应用研究[D].郑州:河南工业大学,2017.
[22]吴瑞林,王建中,袁克海.多分格相关与皮尔逊相关的蒙特卡罗仿真[J].北京航空航天大学学报,2009,35(12):1507-1510,1515.WU Ruilin,WANG Jianzhong,YUAN Kehai. Monte Carlo simulation of polychoric correlation and Pearson correlation coefficient[J]. Journal of Beijing University of Aeronautics and Astronautics,2009,35(12):1507-1510,1515.(in Chinese)
[23]余永维,杜柳青,闫哲,等.基于深度学习特征的铸件缺陷射线图像动态检测方法[J/OL].农业机械学报,2016,47(7):407-412. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? file_no=20160755&flag=1&journal_id=jcsam.DOI:10. 6041/j. issn. 1000-1298. 2016. 07. 055.YU Yongwei,DU Liuqing,YAN Zhe,et al. Dynamic detection of casting defects radiographic image based on deep learning feature[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(7):407-412.(in Chinese)
[24]温皓杰,周婧,傅泽田,等.面向语义挖掘的蔬菜病害知识视频场景检测[J/OL].农业机械学报,2016,47(增刊):386-391. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? file_no=2016s059&flag=1&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2016. S0. 059.WEN Haojie,ZHOU Jing,FU Zetian,et al. Semantic mining oriented scene detection of vegetable disease videos[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(Supp.):386-391.(in Chinese)
[25]李兴岩,王卫华,王昆,等.浅谈储粮发热及处理办法[C]∥中国粮油学会学术年会,2010.
[2]吕平原,姜洪,樊庆风,等.粮食质量安全监测方式及其有效性、时效性探讨[J].粮食科技与经济,2017,42(4):18-20.LPingyuan,JIANG Hong,FAN Qingfeng,et al. Discussion on the monitoring method of grain quality and safety and its effectiveness and timeliness[J]. Grain Science and Technology and Economy,2017,42(4):18-20.(in Chinese)
[3]刘凌.对完善我国储备粮监督管理机制的立法建议[J].河南工业大学学报(社会科学版),2015,11(2):49-52.LIU Ling. Legislative proposals on improving the supervision&management mechanism of China grain reserves[J]. Journal of Henan University of Technology(Social Science Edition),2015,11(2):49-52.(in Chinese)
[4]张昌彩.国外粮食储备管理及其对我国的启示[J].经济研究参考,2004(24):33-43.ZHANG Changcai. The management of foreign grain reserve and its englightenment to China[J]. Review of Economic Research,2004(24):33-43.(in Chinese)
[5]唐为明.加拿大的粮食流通技术[J].粮油科技,2003(3):2-7.TANG Weiming. Food circulation technology in Canada[J]. Science and Technology of Grain and Oil,2003(3):2-7.(in Chinese)
[6]王铁滨,苏建民,白玲,等.数字林业智能地衡管理系统设计[J].林业机械与木工设备,2007,35(1):34-36.WANG Tiebin,SU Jianmin,BAI Ling,et al. Design of digital forestry intelligent land balance management system[J]. Forestry Machinery&Woodworking Equipment,2007,35(1):34-36.(in Chinese)
[7]朱铁军,施艳舞,孟凡刚,等.激光扫描技术测量粮堆体积试验[J].粮食科技与经济,2012,37(4):30-31.ZHU Tiejun,SHI Yanwu,MENG Fan'gang,et al. Study on measuring grain bulk by laser scanning[J]. Grain Science and Technology and Economy,2012,37(4):30-31.(in Chinese)
[8] WANG Y T,FENG H Y. Effects of scanning orientation on outlier formation in 3D laser scanning of reflective surfaces[J].Optics and Lasers in Engineering,2016,81:31-45.
[9]宋立明,李秀华,李万龙.基于计算机视觉的储粮智能稽核方法[J].吉林大学学报(信息科学版),2013,31(1):109-111.SONG Liming,LI Xiuhua,LI Wanlong. Survey on reserved grain intelligent audit methods based on computer vision[J].Journal of Jilin University(Information Science Edition),2013,31(1):109-111.(in Chinese)
[10]祝玉华,陈军涛,甄彤,等.储粮数量检测技术研究进展[J].河南工业大学学报(自然科学版),2016,37(6):116-122.ZHU Yuhua,CHEN Juntao,ZHEN Tong,et al. Present situation and prospect of grain storage quantity detection technology[J]. Journal of Henan University of Technology(Natural Science Edition),2016,37(6):116-122.(in Chinese)
[11]陈得民,张元.基于压力传感器网络的粮仓储粮数量监测系统[J].微计算机信息,2009,25(5):142-143.CHEN Demin,ZHANG Yuan. The system of monitoring the number of grain storage based on the pressure sensor netmork[J].Microcomputer Information,2009,25(5):142-143.(in Chinese)
[12] CHAUDHURY A R,PANTAZIS A K,CHRONIS N. An image contrast-based pressure sensor[J]. Sensors and Actuators A:Physical,2016,245:63-67.
[13]张新新,张元,廉飞宇.储粮数量的电磁波探测技术研究[J].电脑知识与技术,2014,10(10):2453-2454.ZHANG Xinxin,ZHANG Yuan,LIAN Feiyu. A study on electromagnetic wave detection technology for grain storage amount[J]. Computer Knowledge and Technology,2014,10(10):2453-2454.(in Chinese)
[14]张德贤,杨铁军,傅洪亮,等.基于压力传感器的粮仓储粮数量在线检测方法[J].中国粮油学报,2014,29(4):98-100.ZHANG Dexian,YANG Tiejun,FU Hongliang,et al. An on-line detection method of granary storage quantity based on pressure sensor[J]. Journal of the Chinese Cereals and Oils Association,2014,29(4):98-100.(in Chinese)
[15]秦瑶,陈洁,方广有,等.雷达层析成像技术对粮仓储量信息的探测[J].电波科学学报,2010,25(1):66-72,201.QING Yao,CHEN Jie,FANG Guangyou,et al. Radar tomography technology to detect reserves of barn[J]. Chinese Journal of Radio Science,2010,25(1):66-72,201.(in Chinese)
[16]国家质量监督检验检疫总局,国家标准化管理委员会.粮油储藏技术规范:GB/T 29890—2013[S].北京:中国标准出版社,2013.
[17]吴子丹.绿色生态低碳储粮新技术[M].北京:中国科学技术出版社,2011.
[18]王明洁.绿色储粮与食品安全[J].食品科学,2003(8):153-154.WANG Mingjie. Green grain storage and food safety[J]. Food Science,2003(8):153-154.(in Chinese)
[19]赫振方,赵玉霞,曹阳,等.平房仓粮堆温度时空分布的基本统计特征分析[J].粮食储藏,2010,39(4):15-20.HAO Zhenfang,ZHAO Yuxia,CAO Yang,et al. Statistical character on temporal and spatial distributing of grain temperature in warehouse[J]. Grain Storage,2010,39(4):15-20.(in Chinese)
[20]王振清,田栋杰,刘海燕.钢筋混凝土圆形地下粮仓温度场试验研究[J].河南工业大学学报(自然科学版),2018,39(3):99-102,126.WANG Zhenqing,TIAN Dongjie,LIU Haiyan. Experimental study on temperature field of underground reinforced concrete circular granary[J]. Journal of Henan University of Technology(Natural Science Edition),2018,39(3):99-102,126.(in Chinese)
[21]安西友.鲁西南地区均温型谷物冷却机控温储藏稻谷生产应用研究[D].郑州:河南工业大学,2017.
[22]吴瑞林,王建中,袁克海.多分格相关与皮尔逊相关的蒙特卡罗仿真[J].北京航空航天大学学报,2009,35(12):1507-1510,1515.WU Ruilin,WANG Jianzhong,YUAN Kehai. Monte Carlo simulation of polychoric correlation and Pearson correlation coefficient[J]. Journal of Beijing University of Aeronautics and Astronautics,2009,35(12):1507-1510,1515.(in Chinese)
[23]余永维,杜柳青,闫哲,等.基于深度学习特征的铸件缺陷射线图像动态检测方法[J/OL].农业机械学报,2016,47(7):407-412. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? file_no=20160755&flag=1&journal_id=jcsam.DOI:10. 6041/j. issn. 1000-1298. 2016. 07. 055.YU Yongwei,DU Liuqing,YAN Zhe,et al. Dynamic detection of casting defects radiographic image based on deep learning feature[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(7):407-412.(in Chinese)
[24]温皓杰,周婧,傅泽田,等.面向语义挖掘的蔬菜病害知识视频场景检测[J/OL].农业机械学报,2016,47(增刊):386-391. http:∥www. j-csam. org/jcsam/ch/reader/view_abstract. aspx? file_no=2016s059&flag=1&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2016. S0. 059.WEN Haojie,ZHOU Jing,FU Zetian,et al. Semantic mining oriented scene detection of vegetable disease videos[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(Supp.):386-391.(in Chinese)
[25]李兴岩,王卫华,王昆,等.浅谈储粮发热及处理办法[C]∥中国粮油学会学术年会,2010.