Development of Grain Dryer Control Technology from the Perspective of Low Carbon and Intelligentization
Source abstract
Abstract
The grain-drying process plays a critical role in grain storage and quality assurance. In recent years, with the advancement of low-carbon and intelligent technologies, the control technology of grain dryers has significantly improved. This paper systematically reviews the development status of grain dryer control technology from the perspective of low-carbon and intelligentization, analyzing the technological differences in control systems between domestic and international approaches. Current research challenges include the insufficient integration of control technologies with the drying process, limited control variables, the inadequate application of intelligent control strategies, and unstable sensor accuracy. To enhance the performance of grain-drying systems, this paper suggests optimizing control mechanisms, adopting efficient and environmentally friendly energy sources, improving sensor performance, introducing advanced intelligent control algorithms, and strengthening system monitoring capabilities. Looking ahead, with the further integration of AI, IoT, and green energy, grain-drying control systems are expected to evolve towards greater intelligence, remote operation, and low carbonization, providing technical support for enhancing drying efficiency and environmental performance.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Remote Sensing and Land Use · Regional Development and Environment · Medical Research and Treatments
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Academy of National Food and Strategic Reserves Administration, Institute of Grain Storage and Logistics, Beijing 100037, China
College of Mechanical Engineering, Jiamusi University, Jiamusi 154007, China
College of Mechanical and Electrical Engineering, Tarim University, Alar 843300, China
National Engineering Research Center of Grain Storage and Logistics, Beijing 102209, China
Funding
Academy of National Food and Strategic Reserves Ad-ministration · Joint Research and Development of High-Power Deep Ultraviolet Chip Technology and Application Equipment
References (100+)
Show source-provided references
1. On Food Safety and Agricultural Economic Development
2. Ou, W.Y. (2020). Research on the Design and Application of Cyclic Grain Drying Machines. [Master’s Thesis, South China Agricultural University].
3. The Impact of Non-agricultural Employment and Agricultural Machinery Service Outsourcing on Grain Output
4. Exploration of a Sustainable Intensification Model for Promoting Agricultural Industry Development and Food Security
5. 695.41 Billion Kilograms! A New Record for Total Grain Output
6. The genetic architecture of the dynamic changes in grain moisture in maize10.1111/pbi.13541 ↗
7. Research and Performance Verification of the Variable Temperature Homogeneous Drying Device for Paddy Rice
8. Recent advances in the drying process of grains10.1007/s12393-023-09333-7 ↗
9. Li, J.Q., Yi, X.K., and Jin, Y. (2024). Study of the Targeted Regulation of Rice Drying Characteristics and Quality. Appl. Sci., 14.10.3390/app14093587 ↗
10. Electro-based technologies in food drying-A comprehensive review10.1016/j.lwt.2021.111315 ↗
11. Forecast of the Grain Dryer Market Trend
12. Market Demand Analysis and Development Suggestions for Grain Drying Equipment
13. Yan, Z., Zhou, Z., Jiao, Y., Huang, J., Yu, Z., Zhang, D., and Ni, D. (2023). Hot-air drying significantly improves the quality and functional activity of orange black tea compared with traditional sunlight drying. Foods, 12.10.3390/foods12091913 ↗
14. A review on indirect type solar dryers for agricultural crops–Dryer setup, its performance, energy storage and important highlights10.1016/j.apenergy.2019.114005 ↗
15. Current Status and Trends of Grain Drying Technology Development in China
16. Comparative Study of Grain Drying in China and Japan
17. Exploration and Research on Quality Preservation, Loss Reduction, and Increase in Yield and Efficiency of “Gas Suction Circulation Grain Dryer”
18. Performance enhancement of stepped basin solar still based on OSELM with traversal tree for higher energy adaptive control10.1016/j.desal.2020.114926 ↗
19. Fuzzy logic strategy for priority control of electric vehicle charging10.1109/TITS.2022.3161398 ↗
20. Jin, Y., Yin, J., Zhang, H., Zhang, J., Zhang, Z., and Yang, D. (2021, January 27–28). Parameters predictions of paddy grain drying based on machine learning. Proceedings of the 2021 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), Xi’an, China.10.1109/ICITBS53129.2021.00176 ↗
21. Singular Perturbation-Based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis With Control10.1109/TSG.2024.3357481 ↗
22. Huang, C. (2023). Research on the Structural Optimization of the Dryer’s Angular Box and the Control System of the Entire Machine. [Master’s Thesis, Anhui Agricultural University].
23. Process Optimization and Performance Testing of the Variable Temperature Homogeneous Drying Device for Paddy Rice
24. Moisture Prediction and Optimization of Grain Dryer Based on LSTM Network
25. Performance analysis of a novel biomass-fired grain dryer integrated with thermal storage medium10.1016/j.biosystemseng.2022.02.001 ↗
26. Comprehensive energy analysis and environmental sustainability of industrial grain drying10.1016/j.rser.2024.114442 ↗
27. Research on Intelligent Control Method of Grain Dryer Based on LSTM-MPC
28. Relationship between accumulated temperature and quality of paddy10.1080/10942912.2019.1566241 ↗
29. Jin, Y., Yin, J., Xie, H., and Zhang, Z. (2021). Reconstruction of rice drying model and analysis of tempering characteristics based on drying accumulated temperature. Appl. Sci., 11.10.3390/app112311113 ↗
30. Jin, Y., Yin, J., Xie, H., and Zhang, Z. (2023). Investigation of a Precise Control Scheme for Rice Quality. Appl. Sci., 13.10.3390/app13137532 ↗
31. Analysis of the Characteristics of a Multifunctional Grain Storage System with Low-Temperature Drying, Refrigeration, and Humidity Control
32. Recent developments of artificial intelligence in drying of fresh food: A review10.1080/10408398.2018.1446900 ↗
33. Electrohydrodynamic drying: Can we scale-up the technology to make dried fruits and vegetables more nutritious and appealing?10.1111/1541-4337.12799 ↗
34. Energy and exergy analysis of the drying of corn grains10.1016/j.renene.2020.10.116 ↗
35. Adaptive optimal control of entangled qubits10.1126/sciadv.abq4244 ↗
36. A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition10.1038/s41928-020-00510-8 ↗
37. Cellpose: A generalist algorithm for cellular segmentation10.1038/s41592-020-01018-x ↗
38. Learning-based model predictive control: Toward safe learning in control10.1146/annurev-control-090419-075625 ↗
39. Neural-network-based event-triggered adaptive control of nonaffine nonlinear multiagent systems with dynamic uncertainties10.1109/TNNLS.2020.3003950 ↗
40. Deep adaptive control: Deep reinforcement learning-based adaptive vehicle trajectory control algorithms for different risk levels10.1109/TIV.2023.3303408 ↗
41. Adaptive control and intersections with reinforcement learning10.1146/annurev-control-062922-090153 ↗
42. A review of advanced ground source heat pump control: Artificial intelligence for autonomous and adaptive control10.1016/j.rser.2021.111685 ↗
43. Approximation-based Nussbaum gain adaptive control of nonlinear systems with periodic disturbances10.1109/TSMC.2021.3050993 ↗
44. Adaptive control of a two-link robot using batch least-square identifier10.1109/JAS.2020.1003459 ↗
45. Neuro-predictive control of an infrared dryer with a feedforward-feedback approach10.1002/asjc.1038 ↗
46. Optimal variables estimation for energy reduction via a remote supervisory control: Application to a counter-flow rotary dryer10.1016/j.heliyon.2018.e01087 ↗
47. Fuzzy logic control of relative humidity in microwave drying of hawthorn10.1016/j.jfoodeng.2021.110706 ↗
48. A Comprehensive Review of Composite Adaptive Control for Servo Systems
49. Comparative study of energy management systems for a hybrid fuel cell electric vehicle-A novel mutative fuzzy logic controller to prolong fuel cell lifetime10.1016/j.ijhydene.2022.05.192 ↗
50. Risk assessment and management of excavation system based on fuzzy set theory and machine learning methods10.1016/j.autcon.2020.103490 ↗
51. Power quality improvement for grid-connected PV system based on distribution static compensator with fuzzy logic controller and UVT/ADALINE-based least mean square controller10.35833/MPCE.2021.000285 ↗
52. Asymmetrical interval type-2 fuzzy logic control based MPPT tuning for PV system under partial shading condition10.1016/j.isatra.2020.01.009 ↗
53. Interval type-2 fuzzy logic controlled shunt converter coupled novel high-quality charging scheme for electric vehicles10.1109/TII.2020.3024071 ↗
54. Whale optimization algorithm-based Sugeno fuzzy logic controller for fault ride-through improvement of grid-connected variable speed wind generators10.1016/j.engappai.2019.103328 ↗
55. A comprehensive review on type 2 fuzzy logic applications: Past, present and future10.1016/j.engappai.2020.103916 ↗
56. An adaptive fuzzy logic control of green tea fixation process based on image processing technology10.1016/j.biosystemseng.2021.12.023 ↗
57. Nonsingular terminal sliding mode control with ultra-local model and single input interval type-2 fuzzy logic control for pitch control of wind turbines10.1109/JAS.2021.1003889 ↗
58. Kumar, A., and Raj, R. (2022). Design of a fractional order two layer fuzzy logic controller for drug delivery to regulate blood pressure. Biomed. Signal Process. Control., 78.10.1016/j.bspc.2022.104024 ↗
59. Intelligent approaches for linear controllers tuning with application to temperature control10.3233/IFS-141242 ↗
60. On the Design of a Fuzzy Logic–Based Control System for Freeze-Drying Processes10.1016/j.xphs.2016.08.018 ↗
61. A neural network model used in continuous grain dryer control system10.1080/07373937.2021.1891930 ↗
62. Artificial neural networks for neuroscientists: A primer10.1016/j.neuron.2020.09.005 ↗
63. Single cortical neurons as deep artificial neural networks10.1016/j.neuron.2021.07.002 ↗
64. Artificial neural networks-based machine learning for wireless networks: A tutorial10.1109/COMST.2019.2926625 ↗
65. Perceptron theory can predict the accuracy of neural networks10.1109/TNNLS.2023.3237381 ↗
66. Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics10.1016/j.neunet.2020.02.016 ↗
67. Innovative artificial neural network approach for integrated biogas–wastewater treatment system modelling: Effect of plant operating parameters on process intensification10.1016/j.rser.2020.109784 ↗
68. Jamming detection at the edge of drone networks using multi-layer perceptrons and decision trees10.1016/j.asoc.2021.107806 ↗
69. Direct fit to nature: An evolutionary perspective on biological and artificial neural networks10.1016/j.neuron.2019.12.002 ↗
70. Inverse design of porous materials using artificial neural networks10.1126/sciadv.aax9324 ↗
71. Brain-inspired replay for continual learning with artificial neural networks10.1038/s41467-020-17866-2 ↗
72. Application of artificial neural networks (ANNs) in drying technology: A comprehensive review10.1080/07373937.2015.1036288 ↗
73. The effect of ultrasound pre- treatment on quality, drying, and thermodynamic attributes of almond kernel under convective dryer using ANNs and ANFIS network10.1111/jfpe.12868 ↗
74. Modelling and control of laboratory scale conveyor belt type grain dryer plant
75. Robust feedback control of convective drying of particulate solids10.1016/j.jprocont.2018.07.010 ↗
76. Machine learning in drying10.1080/07373937.2019.1690502 ↗
77. Introduction to the special issue on Intelligent Control and Optimisation10.1016/j.engappai.2023.106325 ↗
78. Communication-free voltage-regulation and current-sharing for DC microgrids: An intelligent edge control10.1109/TSMC.2023.3277560 ↗
79. Fuzzy logic type-2 intelligent moisture control system10.1016/j.eswa.2023.121581 ↗
80. Security-based fuzzy control for nonlinear networked control systems with DoS attacks via a resilient event-triggered scheme10.1109/TFUZZ.2022.3148875 ↗
81. A survey on intelligent control for multiagent systems10.1109/TSMC.2020.3042823 ↗
82. An intelligent control method for the low-carbon operation of energy-intensive equipment10.1016/j.eng.2023.05.018 ↗
83. Wu, X., Wang, Y., Wang, C., Wang, W., and Dong, F. (2021). Moving average convergence and divergence indexes based online intelligent expert diagnosis system for anaerobic wastewater treatment process. Bioresour. Technol., 324.10.1016/j.biortech.2020.124662 ↗
84. Intelligent terminal sliding mode control of active power filters by self-evolving emotional neural networ10.1109/TII.2022.3168654 ↗
85. Intelligent control of cardiac rhythms using artificial neural networks10.1007/s11071-023-08447-1 ↗
86. Intelligent leader-following consensus formation control using recurrent neural networks for small-size unmanned helicopters10.1109/TSMC.2019.2896958 ↗
87. Intelligent wind farm control via deep reinforcement learning and high-fidelity simulations10.1016/j.apenergy.2021.116928 ↗
88. Autonomous intelligent control of earth pressure balance shield machine based on deep reinforcement learning10.1016/j.engappai.2023.106702 ↗
89. Li, F., and Du, Y. (2023). Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning. Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems, Springer International Publishing.10.1007/978-3-031-45357-1_4 ↗
90. Development of intelligent fault-tolerant control systems with machine leaprning, deep learning, and transfer learning algorithms: A review10.1016/j.eswa.2023.121956 ↗
91. Deep reinforcement learning for autonomous internet of things: Model, applications and challenges10.1109/COMST.2020.2988367 ↗
92. Intelligent traffic control system based on cloud computing and big data mining10.1109/TII.2019.2929060 ↗
93. Internet of things for smart farming and frost intelligent control in greenhouses10.1016/j.compag.2020.105614 ↗
94. Research on the Automatic Control System of Grain Dryer Based on Fuzzy Control
95. Design and Implementation of the Automatic Control System for the Tube Bundle Dryer
96. Design of Online Moisture Measurement System for Grain Drying
97. Experimental Study on the Hot Air Drying Process of Red Dates
98. Liu, L.J. (2019). Design and Implementation of the Control System for a Novel Heat Pump Dryer. [Master’s Thesis, Southwest University of Science and Technology].
99. Retrofit of the Electrical Control System for China South Rail Sunyang 5HSZ-C-50 Small Continuous Grain Dryer
100. Design of the Control System for Cyclic Grain Dryer Based on PLC