In order to solve the problems such as the inability to automatically mix a variety of solid fertilizers and the unreasonable fertilizer amount, improve fertilizer utilization, and reduce production costs, this study designs a variable formula fertilization control system based on a prescription diagram, including pressure sensor, speed sensor, servo motor, fertilizer discharge actuator, Programmable Logic Controller (PLC controller), vehicle control terminal, etc. Based on pre-loaded soil prescription diagram and combining fertilizer pressure and ground wheel speed detection information, the system obtained a formula fertilization control strategy through calculation to realize the function of fast and automatic formula of nitrogen, phosphorus, and potassium fertilizers and precise variable fertilization. The experimental study on the performance of the variable formula fertilization control system showed the following: the measurement error range of the pressure sensor was 0.005~0.03%; the relationship between the motor speed and the amount of nitrogen, phosphorus, and potassium fertilizer discharged was calibrated. Three gears were established for the motor speed: low (10 r/min), medium (30 r/min), and high (50 r/min); the measurement accuracy of the speed sensor was above 98%. The test verified that the control accuracy of the variable formula fertilization system reached more than 95%, which met the requirements of fast automatic formula and precise variable fertilization and had good practicability and economy.

No abstract

In view of the difficulty in diagnosing and discriminating fault conditions during the operation of combine harvesters, difficulty in real-time processing of health status, and low timeliness of fault processing, a comprehensive operation and maintenance platform for combine harvesters was developed in this study which realized the functions of data monitoring and the full operation and maintenance of a combine harvester. At the same time, through the comprehensive operation and maintenance platform, the harvester information was obtained in real-time, the diagnosis results were obtained, and the maintenance service was effectively carried out through the platform. The IPSO-SVM fault diagnosis algorithm was proposed, and the performance of the fault diagnosis of the combine harvester was verified by the simulation test. The experimental verification showed that the system met the requirements of remote monitoring of combine harvesters, and the prediction accuracy of this method was 97.96%. Compared with SVM (87.51%), GA-SVM (89.44%), and PSO-SVM (92.56%), this system had better generalization ability and effectively improved the management level of the comprehensive operation and maintenance of the combine harvester. A theoretical basis and technical reference will be provided for the follow-up research for the comprehensive operation and maintenance platform of the combine harvester in this paper.

To solve the inspection problems in cotton storage, as well as the need for environmental monitoring in the process of modern cotton bale storage, an intelligent inspection and temperature and humidity intelligent monitoring system based on RFID cotton bale was developed by adopting RFID (Radio Frequency Identification) technology, wireless temperature and humidity real-time monitoring technology and handheld terminal intelligent inspection technology. The system was composed of RFID positioning inspection module and temperature and humidity real-time monitoring and transmission module. The artificial neural network (ANN) based on the particle swarm optimization (PSO) algorithm was used to process the monitoring data of the system by Gaussian filtering, and an accurate classification model of RSSI and label position was established. The test results showed that: Through the comparative analysis of the RFID indoor positioning algorithm, the positioning error of the PSO-ANN algorithm was small. In the actual cotton bale warehouse test, the relative error of positioning and monitoring for RFID cotton bale intelligent inspection and monitoring system was less than 6.7%, which effectively improved the working efficiency of inspection personnel and the security of cotton bale storage. The relative error of temperature and humidity was less than 8% and less than 7%, which could display the temperature and humidity information in real time and meet the real-time demand. This study improved the management personnel's effective positioning and inspection of the cotton bale, prevented the loss of cotton bale, reduced the deterioration probability of cotton bale, and effectively improved the storage management level of the cotton bale. It was of great practical significance to realize the networking, automation, and intelligence of cotton bale storage management.