Abstract
Objective: To solve the problem of unstable rice output quality caused by the lack of information exchange and coordinated control between equipment in the rice processing system. Methods: Based on the industrial internet of things technology, a five-layer architecture of the rice processing system was constructed, and the solutions to the technical problems existing in the network layer, decision layer and control layer of the architecture were proposed for the corresponding layer problems such as the wireless sensor network model based on machine vision, the fuzzy self-tuning control model based on differential evolutionary algorithm and the rubber roller synchronization control method of the huller. The hardware and software of the system were designed, the actual transformation of the hulling and milling section was carried out, and then early indica rice grains were selected for processing tests. Results: Compared with the traditional processing, the improved rice processing system increased the browning rate about 1%, the whole fine rice rate by about 1%, and the production energy consumption is reduced about 15%. Conclusion: The researched rice processing system based on IOT technology has implications for improving the intelligent transformation of process processing systems such as rice processing.
Publication Date
10-20-2023
First Page
93
Last Page
98
DOI
10.13652/j.spjx.1003.5788.2022.81100
Recommended Citation
Jin, ZHOU; Shuang, LIU; and Qing, MIAO
(2023)
"Research on paddy processing system based on industrial internet of things,"
Food and Machinery: Vol. 39:
Iss.
7, Article 14.
DOI: 10.13652/j.spjx.1003.5788.2022.81100
Available at:
https://www.ifoodmm.cn/journal/vol39/iss7/14
References
[1] 胡文忠. 当前我国稻谷市场供需形势与价格走势[J]. 中国粮食经济, 2021(4): 60-62.
HU W Z. Current supply and demand situation and price trend in China's rice market[J]. China Grain Economy, 2021(4): 60-62.
[2] 胡纪东. 湖北省稻谷加工粮食损失现状调查与评估[D]. 武汉: 武汉轻工大学, 2018: 8-20.
HU J D. Investigation and estimate on the status of rice processing loss in Hubei province[D]. Wuhan: Wuhan Polytechnic University, 2018: 8-20.
[3] 陈思思, 樊琦. 我国稻谷过度加工造成营养物质损失浪费的研究[J]. 粮食与油脂, 2020, 33(7): 10-13.
CHEN S S, FAN Q. Research on nutrient loss and waste during rice over processing in China[J]. Cereals & Oils, 2020, 33(7): 10-13.
[4] ADEDEJI K A, RAJI N A, OYETUNJI E O, et al. Design and fabrication of a motorized rice hulling machine[J]. Journal of Engineering Research, 2020, 11(1): 1-10.
[5] ROSALES M M, CORONEL G M C, LORILLA J K P, et al. Cloud-based Portable Rice Milling Machine using Internet of Things[C]// 2022 2nd International Conference on Intelligent Technologies (CONIT). Hubli: IEEE, 2022: 1-7.
[6] SAIRI S A M, MUSTAFFHA S. Comparative study of three rice brands' quality through measuring broken rice percentage using sortex A ColorVision (Buhler) optical sorters[J]. IOP Conference Series: Earth and Environmental Science, 2020, 515(1): 012017.
[7] 蒋志荣, 刘华旺, 贾雳, 等. 水稻加工智能工厂浅述[J]. 粮食加工, 2019, 44(1): 35-37.
JIANG Z R, LIU H W, JIA L, et al. Brief introduction to intelligent rice processing plant[J]. Grain Processing, 2019, 44(1): 35-37.
[8] 郝运. 智能物联网技术及应用的发展新趋势[J]. 科技创新与应用, 2022, 12(26): 153-156.
HAO Y. New trend in the development of smart internet of things technologies and applications[J]. Technology Innovation and Application, 2022, 12(26): 153-156.
[9] WEYRICH M, EBERT C. Reference architectures for the internet of things[J]. IEEE Software, 2015, 33(1): 112-116.
[10] LIU R, WANG J F. Internet of things: Application and prospect[J]. MATEC Web of Conferences, 2017, 100: 02034.
[11] CUI L, YANG S, CHEN F, et al. A survey on application of machine learning for internet of things[J]. International Journal of Machine Learning and Cybernetics, 2018, 9(8): 1 399-1 417.
[12] 和征, 李彦妮, 杨小红. 制造企业工业物联网的发展与智能制造转型分析: 基于三一重工的案例研究[J]. 制造技术与机床, 2022(7): 69-74.
HE Z, LI Y N, YANG X H. Analysis on the development of industrial internet of things and the transformation of intelligent manufacturing enterprises: Based on the case study of sany group[J]. Manufacturing Technology & Machine Tool, 2022(7): 69-74.
[13] LATIF S, DRISS M, BOULILA W, et al. Deep learning for the industrial internet of things (IIoT): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions[J]. Sensors, 2021, 21(22): 7 518.
[14] BOYES H, HALLAQ B, CUNNINGHAM J, et al. The industrial internet of things (IIoT): An analysis framework[J]. Computers in Industry, 2018, 101: 1-12.
[15] 吴建永, 刘成梅, 刘伟, 等. 大米加工精度检测方法研究进展[J]. 食品工业科技, 2015, 36(18): 395-399.
WU J Y, LIU C M, LIU W, et al. Research progress in methods for detecting milling degree of rice[J]. Science and Technology of Food Industry, 2015, 36(18): 395-399.
[16] SALEH M I, MEULLENET J F. Effect of moisture content at harvest and degree of milling (based on surface lipid content) on the texture properties of cooked long-grain rice[J]. Cereal Chemistry, 2007, 84(2): 119-124.
[17] REN H B, QI S M, ZHANG L H, et al. Variations in the appearance quality of brown rice during the four stages of milling[J]. Journal of Cereal Science, 2021, 102: 103344.
[18] PERDON A A, SIEBENMORGEN T J, MAUROMOUSTAKOS A, et al. Degree of milling effects on rice pasting properties[J]. Cereal Chemistry, 2001, 78(2): 205-209.
[19] RODRIGUEZ-ARZUAGA M, CHO S, BILLIRIS M A, et al. Impacts of degree of milling on the appearance and aroma characteristics of raw rice[J]. Journal of the Science of Food and Agriculture, 2016, 96(9): 3 017-3 022.
[20] 张士雄, 阮竞兰, 武照云, 等. 基于双电机驱动全自动气压胶辊砻谷机的研制与控制系统设计[J]. 粮食与饲料工业, 2015(11): 5-7.
ZHANG S X, RUAN J L, WU Z Y, et al. The development and control system design of dual motor-based automatic pneumatic rubber brick husker[J]. Cereal & Feed Industry, 2015(11): 5-7.