Design of Water Content Measurement System for Animal Granular Feed Based on BP Neural Network

doi:10.15933/j.cnki.1004-3268.2021.09.020

Abstract

Abstract: In order to solve the problems of high cost，low efficiency，and failing to realize rapid on⁃line detection in the process of traditional measurement of moisture content in the livestock and poultry granular feed，a new nondestructive indirect on⁃line rapid measurement system of moisture content was designed. According to the requirements of overall structure of measurement system and GB/T 6435—2014，the STM32F103C8T6 was used as microcontroller； the differential frequency cylindrical capacitance sensor was selected to detect the capacitance of the granular feed sample；the temperature sensor DS18B20 was used to measure the temperature of the sample test environment；the multi⁃sensor data fusion based on BP neural network algorithm compensated for the error by temperature，compactness and other factors.According to the method of multiple regression analysis，the moisture content model of granular feed sample was established and fitted with MATLAB curve.The experimental results showed that the system could determine the moisture content of granular feed in 5—8 s，the absolute error was less than 1.2%，and the repeatability error was less than 0.2.The system meets the new requirements of precise management of feed production and effective reduction of feeding cost.

Key words: Granular feed for livestock and poultry, Moisture content, Measurement system, Nondestructive online detection, Moisture model, BP network fusion algorithm, MATLAB curve fitting

摘要： 为了解决传统畜禽粒状饲料水分含量测定过程中存在的成本耗费大、测定效率低、无法实现快速在线检测等问题，设计了间接式新型水分含量测定系统，用于畜禽粒状饲料在线快速测量。根据GB/T6435—2014要求及测定系统总体结构，以嵌入式芯片STM32F103C8T6为主控核心，选取差频式圆柱形电容传感器检测粒状饲料样品电容，使用温度传感器DS18B20测定样品测试环境温度，基于BP神经网络融合算法实现多传感器数据融合以补偿温度、紧实度等因素所造成的测定误差，根据多元回归分析方法建立粒状饲料样品水分测定模型，并利用MATLAB曲线拟合。结果表明，设计的测定系统能够在5~8 s内测定粒状饲料水分含量，测定绝对误差低于1.2%，测量重复性误差小于0.2。可见，设计的粒状饲料水分含量测定系统符合养殖业饲料生产精准管理且有效降低饲养成本的要求。

关键词: 畜禽粒状饲料, 水分含量, 测定系统, 无损在线检测, 水分模型, BP网络融合算法, MATLAB曲线拟合

CLC Number:

S126
TP393

ZHANG Xiyu, ZHU Guolu, CHEN Yuxin, GAO Haoyuan, LI Jiale. Design of Water Content Measurement System for Animal Granular Feed Based on BP Neural Network[J]. Journal of Henan Agricultural Sciences, 2021, 50(9): 163-171.

张洗玉, 朱果露, 陈雨欣, 高浩源, 李嘉乐. 基于BP 神经网络的畜禽粒状饲料水分测定系统设计[J]. 河南农业科学, 2021, 50(9): 163-171.

Figures/Tables 10

References

［1］韩浩月，Hy-Line技术团队.饲料颗粒大小的测定及其对蛋鸡生产性能的重要影响［J］.国外畜牧学（猪与禽），2017，37（3）：48⁃52．
HAN H Y，HY⁃Line technical team.Determination of feed particle size and its important influence on laying performance［J］.Foreign Animal Husbandry （Pig and Poultry），2017，37（3）：48⁃52．
［2］宋文静，李峰.颗粒饲料水分检测控制的研究［J］.饲料博览，2014（9）：52⁃53．
SONG W J，LI F.Study on the detection and control of water content in pellet feed［J］.Feed Expo，2014（9）：52⁃53．
［3］韩晓华，娜日娜，李峰影响颗粒饲料水分含量的因素及控制方法［J］.贵州畜牧兽医，2013，37（5）：26⁃27．
HAN X H，NA R N，LI F.Factors affecting the moisture content of pellet feed and control methods［J］.Guizhou Animal Husbandry and Veterinary，2013，37（5）：26⁃27．
［4］徐之航，欧阳威，武元新.基于改进克隆卡尔曼滤波的视觉惯性里程计实现［J］.信息技术，2020，44（5）：21⁃27，36．
XU Z H，OU YANG W，WU Y X.Realization of visual⁃inertial odometer based on improved clonal Kalman filter［J］.Information Technology，2020，44（5）：21⁃27，36．
［5］朱中胜，张莹，刘红艳，等.家禽颗粒饲料加工工艺参数研究进展［J］.饲料博览，2016（12）：35⁃38．
ZHU Z S，ZHANG Y，LIU H Y，et al.Research Progress on processing parameters of poultry pellet feed［J］.Feed Expo，2016（12）：35⁃38．
［6］张越，赵进，赵丽清，等.基于介电特性谷物水分在线测量仪的设计与试验［J］.中国农机化学报，2020，41（5）：105⁃110.
ZHANG Y，ZHAO J，ZHAO L Q，et al.Design and experiment of grain moisture online measuring instrument based on dielectric properties［J］.China Agricultural Machinery Chemistry Journal，2020，41（5）：105⁃110.
［7］黄世群，文婷，秦琳，等.青饲料及青贮饲料中水分测定方法的探讨［J］.四川农业科技，2020（10）：46⁃47，49.
HUANG S Q，WEN T，QIN L，et al.Discussion on determination method of moisture in green fodder and silage［J］.Sichuan Agricultural Science and Technology，2020（10）：46⁃47，49.
［8］陈素彬，胡振，杨华.近红外光谱法检测饲料玉米品质的优化PLS模型［J］.饲料研究，2020，43（5）：112⁃116.
CHEN S B，HU Z，YANG H.PLS optimization model for detecting feed corn quality by near infrared spectroscopy［J］.Feed Research，2020，43（5）：112⁃116.
［9］孙书静.三种测定饲料水分含量的方法比较［J］.江西饲料，2019（2）：9⁃10.
SUN S J.Comparison of three methods for determining moisture content in feed［J］.Jiangxi Feed，2019（2）：9⁃10
［10］杨君.饲料中水分的测定不确定度评定［J］.食品安全导刊，2020（24）：118.
YANG J.Evaluation of uncertainty in determination of mowasture in feed［J］.Food Safety Guide，2020（24）：118.
［11］黄仲兴，王金娥.饲料中水分含量快速测定方法的研究［J］.黑龙江畜牧兽医，2018（9）：219⁃221.
HUANG Z X，WANG J E.Study on Rapid Determination of water content in feed［J］.Heilongjiang Animal Husbandry and Veterinary，2018（9）：219⁃221.
［12］陆永祥，严显明，周朝相，等.不同添加剂对高水分全株玉米青贮饲料发酵品质和细菌群落的影响［J］.草地学报，2021，29（4）：842⁃847.
LU Y X，YAN X M，ZHOU C X，et al.Effects of different additives on fermentation quality and bacterial community
of high moisture corn silage［J］.Acta Grassland Sinica，2021，29（4）：842⁃847.
［13]杨霞，王定美，麦力文，等.不同含水率饲料对黑水虻生长发育的影响及其对饲料的转化特征研究［J］.环境昆虫学报，2020，42（5）：1183⁃1190.
YANG X，WANG D M，MAI L W，et al.Effects of different water content feed on growth and development of black water fly and its feed transformation characteristics［J］.Acta Entomologica Sinica，2020，42（5）：1183⁃1190.
［14］金楠，李腾飞，王红英，等.饲料限水糊化动力学及其颗粒结构特性的表征［J］.农业工程学报，2020，36（16）：293⁃299.
JIN N，LI T F，WANG H Y，et al.Gelatinization kinetics of feed and characterization of its granule structure［J］.Journal of Agricultural Engineering，2020，36（16）：293⁃299.
［15］李洪志，燕淑海，傅善江.高粱的加工、粒度和水分对饲料制粒和肉鸡生长性能的影响［J］.中国饲料，2020（2）：93⁃97.
LI H Z，YAN S H，FU S J.Effects of sorghum processing，grain size and moisture content on feed granulation and growth performance of broilers［J］.China Feed，2020（2）：93⁃97.
［16］王佳辉，高圣玥，陈杰.饲料霉变发生的原因分析［J］.现代畜牧科技，2020（1）：37⁃39.
WANG J H，GAO S Y，CHEN J.Cause analysis of feed mildew［J］.Modern Animal Science and Technology，2020（1）：37⁃39.
［17］高亚平，安峰，赵东海，等.基于介电特性的青萝卜干燥品质预测模型［J］.天津科技大学学报，2019，34（4）：63⁃71.
GAO Y P，AN F，ZHAO D H，et al.Prediction model for drying quality of green radish based on dielectric properties［J］.Journal of Tianjin University of Scienceand Technology，2019，34（4）：63⁃71.
［18］朱孟兆，朱文兵，陈鑫，等.不同水分含量下三元混合式绝缘油浸纸板的介电、工频击穿及产气特性对比研究［J］.绝缘材料，2020，53（11）：89⁃95.
ZHU M Z，ZHU W B，CHEN X，et al. Comparative study on dielectric，power frequency breakdown and gas production characteristics of ternary hybrid insulating oil impregnated paperboard with different moisture content［J］.Insulating Materials，2020，53（11）：89⁃95.
［19］牛智有，刘芳宏，刘鸣，等.平行极板电容传感器介电式颗粒饲料水分检测仪设计与试验［J］.农业工程学报，2019，35（18）：36⁃43．
NIU Z Y，LIU F H，LIU M，et al.Design and test of dielectric particle feed moisture detector with parallel plate capacitance sensor［J］.Journal of Agricultural Engineering，2019，35（18）：36⁃43．
［20］韩志恒，陶志影，曾育宁，等.基于介电特性的异位发酵床稻谷壳含水率的检测［J］.河南农业科学，2021，50（5）：173⁃180.
HAN Z H，TAO Z Y，ZENG Y N，et al.Detection of moisture content of rice husk in ectopic fermentation bed based on dielectric properties ［J］.Henan Agricultural Sciences，2021，50（5）：173⁃180.
［21］张琦，梁国栋，张鹏飞，等.水产饲料含水率预测模型研究［J］.中国农机化学报，2021，42（3）：84⁃90.
ZHANG Q，LIANG G D，ZHANG P F，et al.Study on prediction model of water content in aquatic feed［J］.China Agricultural Machinery Chemical Journal，2021，42（3）：84⁃90.

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