Master Degree Program in Agricultural Electrification and Automation

Research Directions

1. Agricultural Power Equipment and Power Quality Control

Using high-performance microprocessors, digital communication, power electronics, and modern control theory, this direction addresses active power filtering, harmonic suppression, dynamic reactive-power compensation, and high-power power-electronics applications in power systems. Proprietary products have been developed across static var generators (SVG), active-filter theory, instantaneous harmonic detection, fault-state operation and detection, system modeling, intelligent SVC and intelligent SVG, drive and protection of main-circuit power devices, voltage and current balancing, nonlinear intelligent control algorithms for unbalanced loads — including impact-type and symmetric or asymmetric conditions — and DSP-based composite digital control.

2. Crop Growth and Environmental Information Sensing and Control

This direction develops rapid, non-destructive detection mechanisms and methods for growth, physiological-ecological, and soil moisture and nutrient information in protected crops — a core challenge in precision agriculture — and builds non-destructive nutrient and moisture detectors.

Investigates virtual plant growth systems based on growth models and image-based 3D reconstruction, and physiological-ecology-based dynamic growth and development models and biomass accumulation models for protected vegetables. Water-cycling and transport dynamics in crop–soil–atmosphere systems under controlled conditions are characterized, as are crop water-demand patterns, and multi-objective environmental control strategies for protected crops and model-based information-fusion methods for real-time dynamic parameter optimization of greenhouse environments.

Develops equipment for protected-crop growth and environmental monitoring, and research extends to fruit maturity and quality detection, harvest-target identification and localization, mechanical behavior of harvesting end-effectors, and hand-eye coordination control, leading to the study of flexible robotic-hand harvesting systems.

3. Environmental Monitoring and Control for Industrial-Scale Farming and Microbial Growth

In the monitoring and environmental optimization control of industrial-scale farming — a critical domain in modern agricultural engineering — remote distributed measurement and control methods for multiple environmental factors, including water temperature, dissolved oxygen, and pH, are investigated, and image-processing methods for automatic fish-disease diagnosis are studied. A J2EE-based precision pig-farming technology platform for commercial swine is developed, a whole-process quality and safety information system for pork products is constructed, and online health diagnosis of pigs is performed using audio-video emotion-recognition based on activity morphology and vocalization.

In the detection and control of microbial reactors — a complex system in agricultural engineering — soft measurement of biomass during microbial reaction processes is carried out, including total sugar concentration, cell density, and key residual-metabolite concentration, and optimized control methods are developed.

4. Pest, Disease, and Weed Detection and Precision Application

Studies image, color, morphology, texture, and spectral features of field crops, pests, diseases, and weeds, leading to the development of intelligent diagnosis systems for pests, diseases, and weeds and crop target identification and localization systems.

Examines droplet–target interfacial effects and deposition behavior as well as spray-system working and structural parameters for efficient, low-pollution precision application equipment is development.

Investigates integrated sensing and detection, obstacle avoidance and path planning, anti-leak and anti-re-spray control, and nozzle servo technology for autonomous mobile spray platforms, .

5. Agricultural Machinery Monitoring and Control

Studies agricultural robotic technology, and detection methods and monitoring devices for carry-over loss, cleaning loss, and feed rate in combine harvesters, with multi-sensor fusion theory applied to the monitoring and control of combine harvesters. Develop integrated mechanical-electrical-hydraulic load-feedback control systems for combine harvesters, fault-diagnosis systems and methods, and yield-metering systems centered on low-cost, high-precision grain-flow sensors.

Investigates machine-vision-based precision planter seed-metering performance detection, and intelligent monitoring of planter-operation faults. Studies motion-parameter detection for sparse-planting rice-transplanting mechanisms based on high-speed imaging, and proposes image-monitoring evaluation methods for operation quality.

Research neural-network inverse systems to "linearize" and dynamically decouple complex, multi-variable, nonlinear, strongly coupled controlled systems, for resolution of fundamental problems in transmission-system control of specialized agricultural equipment.

6. Agricultural Information Technology

Using computer technology, sensor technology, bio-information pattern recognition, and spatial information processing and automatic graphics generation, research is conducted on agricultural power-grid information management systems and field-crop water-demand information and distribution, providing information support for agricultural power-grid energy management and field water-saving irrigation.

Application Link

https://oec.ujs.edu.cn/en/ADMISSIONS/Application_Procedure.htm