Design and Experiment of a Sowing Quality Monitoring System of Cotton Precision Hill-Drop Planters

Bai, Shenghe; Yuan, Yazhou; Niu, Kang; Shi, Zenglu; Zhou, Liming; Zhao, Bo; Wei, Liguo; Liu, Lijing; Zheng, Yuankun; An, Shi; Ma, Yihua

doi:10.3390/agriculture12081117

Cited by 12 publications

(7 citation statements)

References 3 publications

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“…Adjustment time Y1 regression equation in X3, X2X3, X 2 3 had a significant effect on the regression equation (0.01 ≤ p < 0.05). The regression equation Y1 was optimized by removing the insignificant regression term from the regression equation, as shown in Equation (6).…”

Section: Test Results and Analysismentioning

confidence: 99%

“…In developed nations, research on leafy vegetable harvesting equipment was conducted earlier. When combined with sensor detection, hydraulic control, and electric control technologies, leafy vegetable harvesting mechanization has increased significantly, and intelligent technologies are at a relatively mature stage [4][5][6]. An electric cutting height device is built into the SLIDE VALERIANA green vegetable harvester made by the Italian company HORTECH and put in front of the cutting mechanism.…”

Section: Introductionmentioning

confidence: 99%

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PID-Based Design of Automatic Control System for a Travel Speed of the 4UM-120D Electric Leafy Vegetable Harvester

Chen

Wang

et al. 2022

Sustainability

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The study developed a PID-based automatic control system for travel speed based on the analysis of the entire machine structure of the 4UM-120D electric leafy vegetable harvester to enhance the operation quality of the harvester and lessen the workload of operators. Taking the system adjustment time during the process of starting and maintaining the travel speed of the harvester within ±2% of the set value as the main evaluation index, the Box–Behnken test method was applied based on the single-factor test, and the proportional coefficient Kp, the integral coefficient Ki and the initial value U of the travel motor drive voltage of the PID control algorithm were used as the test factors, and the PID-based 4UM-120D electric leafy vegetable harvester travel speed automatic control system operating parameters based on PID was studied in a three-factor, three-level experiment, and a multiple regression model of evaluation indexes on each factor was established to analyze the influence of each factor on system rapidity and to obtain the optimal operating parameters. The test findings demonstrated that the beginning value of the driving voltage of the travel motor U, the integration factor Ki, and the proportionality factor Kp had the largest to smallest influences on the system regulation time. When the initial value of the driving voltage of the travel motor was 1.81 V, the integration factor was 0.020, the proportionality factor was 0.127, the system regulation time was 2.14 s, and the relative error was 1.8% compared with the optimized value. The results of the study could provide a way to improve the operation quality of leafy vegetable harvesters and reduce the work intensity of operators.

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Section: Test Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PID-Based Design of Automatic Control System for a Travel Speed of the 4UM-120D Electric Leafy Vegetable Harvester

Chen

Wang

et al. 2022

Sustainability

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“…Photoelectric [2,3], machine vision [4,5], piezoelectric [6,7], and capacitive detection techniques [8][9][10] are frequently used for determining the state of seeding. A fiber optic sensor was used as a detection element, which was installed in the seed guide tube to achieve seed leakage detection in a corn planter [11].…”

Section: Introductionmentioning

confidence: 99%

Seed State-Detection Sensor for a Cotton Precision Dibble

Ren,

Wang,

et al. 2023

Agriculture

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In Xinjiang, precision hole-sowing technology is used for cotton cultivation. A disc-type seed disperser has problems with missing seeds and multi-seeding; therefore, an interdigital (multiple pairs of coplanar electrodes crossed) capacitance sensor is designed to determine the seed pick-up status by gathering electrical capacity information. Firstly, a theoretical derivation is performed for calculating the capacitance of the sensor, and it is concluded that the interdigital spacing, interdigital width, and interdigital logarithm all affect the output capacitance. Then, by analyzing the working process of the dibble, the assemblage position of the sensor and the dimensional constraints were determined. In order to explore the impact of various structural parameters on the sensor’s performance (signal strength and capacitance variation), a Maxwell simulation platform was established, and orthogonal tests were created to optimize the structural parameters. In addition, the STM32 microcontroller is utilized as the core, and it is linked with the PCAP01-AD chip to form a tiny capacitance-detecting circuit. Finally, the capacitance threshold division test determined the capacitance threshold at different seed states. The test results demonstrate that the interdigital capacitive sensor can accurately determine the precision dibble’s seeding status, with detection accuracies of 96.9% for normal seeding, 99.67% for miss-seeding, and 93.77% for multiple seeds. These results can be used as a research reference for capacitive seeding status-detection technology.

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“…The first category has eleven papers under the following sub-heading: Intelligent sensing for the crop or machine system [1,4,7,9,10,12,16,17,22,23,26]. Currently, a large number of studies focus on deep learning techniques, which have shown their superb impact on robotic sensing applications, as reflected in this issue.…”

mentioning

confidence: 99%

“…For intelligent agricultural machines, Bai et al [1] designed a monitoring system for the sowing quality of cotton precision planters, to realize the real-time monitoring of the cotton precision seeding operation processes and improve the intelligence level of cotton precision planters.…”

mentioning

confidence: 99%