Hongwen Li’s research while affiliated with China Agricultural University and other places

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Publications (108)

Research on vibration characteristics of no-tillage seeding unit based on the MBD-DEM coupling
  • Article

March 2025

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4 Reads

Computers and Electronics in Agriculture

Dong He

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Hongwen Li

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Jin He

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[...]

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Zhen Gao
Ground straw mulching level classification based on a terral grid system and deep learning

January 2025

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1 Read

Computers and Electronics in Agriculture

Shan Jiang

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Hongwen Li

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Dong He

The detection of ground straw mulching levels plays a crucial role in implementing conservation tillage efficiently. To address the need for quick and accurate determination of straw mulching levels, a rapid detection method based on deep learning was proposed, which consists of a terral grid system, semi-automatic straw mulching grading based on ASPP-CBAM MobileNet (AC-MobileNet), and a deep residual network ResNet101. The terral grid system was applied to obtain local sliced images at the grid intersections from straw mulching images. Then, the AC-MobileNet model was used to acquire the type of local sliced images automatically, making it obtain the true value of each straw mulching level and establish the dataset quickly. Subsequently, the deep residual network ResNet101 was utilized for straw mulching level detection. The test results showed that the AC-MobileNet model achieved a sliced image classification accuracy of 96.3%, surpassing the MobileNetv3 network model by 2.1%. In comparison with classification networks such as AlexNet, ShuffleNetv1, and EfficientNetv2, the AC-MobileNet model exhibited the highest accuracy. The accuracy of ResNet101 in straw mulching level classification was 98.3%, outperforming DenseNet161, EfficientNetv2, and VGG16 networks. The proposed method demonstrated a detection speed of 750 times higher than that of manual detection in the field, keeping the straw mulching level classification results aligned with the manual results. The developed methodology paves the road for accurate and rapid detection of ground straw mulching levels.

The geometric model of the experimental device, including the container and ultrasonic transducers. The dimensions of the container are as follows: length (l) = 100 mm, height (h) = 130 mm, and width (d) = 40 mm. The container body and the pressure plate are made of steel plates with a thickness (s) of 10 mm. The container is designed to hold soil and secure the ultrasonic transducers (including both the the transmitting and receiving transducers), which are utilized for simulating vibrations to generate ultrasonic signals. A total of 600,000 soil particles are allowed to free-fall into the container under the influence of gravity (g = 9.8 m/s²), using the Hertz–Mindlin model with an expanded particle size of 2 mm. The upper pressure plate is pressed down h1 along the inner wall of the container to achieve a set soil compression rate of 12%. The fixed time step is set to 1.0 × 10⁻⁷ s (2% of the Rayleigh time step), and the grid unit size is set to 2 mm (twice the minimum particle radius).
Schematic diagram of the transmitting transducer motion. The motion mode of the transmitting transducer is set to sinusoidal translation. When transmitting an ultrasonic signal, the transmitting transducer actively translates along the Y axis, while the receiving transducer remains stationary. When the signal is transmitted, the transmitting transducer starts from its original position and moves in the positive direction of the Y-axis (a). Upon reaching the maximum movement distance, the distance from the transmitting transducer to its original position is defined as the amplitude (b). It then begins to move in the negative direction of the Y-axis, and after reaching the farthest position, it reverses direction again to move in the positive direction of the Y-axis (c). When it returns to its original position, it completes a full movement cycle (d). During the transmission of ultrasonic continuous signals, the transmitting transducer does not stop moving when passing through the original position, but continues to repeat the above motion process according to the set motion frequency within the defined time (a–d).
Interface soil pressure waveform at an excitation frequency of 40 kHz and an excitation amplitude of 0.010 mm. The signal is received at 0 s, and the soil pressure changes in the time period of 0–5 × 10⁻⁴ s are observed, including the 10-cycle ultrasonic signal when the transmitting transducer is moving and the soil pressure change after the transmitting transducer stops moving. Based on the characteristics of the waveform, the entire waveform is divided into four bands: “Early wave”, “Wave in the process”, “Late wave” and “Wave after the transmitting transducer stops moving”. In the subsequent analysis, only the bands in the transmission process (“First wave”, “Wave in the process”, “Late wave”) are analyzed, while the bands after the transmission stops is only labeled and not analyzed. H0–H5 represent the peak positions of the first six cycles, and L1–L5 represent the trough positions of the first five cycles. |H1|–|H5| represent the peak value of the wave corresponding to H1–H5 (calculated by Equation (3)), and |L1|–|L5| represent the trough values corresponding to L1–L5 (calculated by Equation (3)). |H0| represents the peak value of the first wave (calculated by Equation (3)), |H| represents the average peak value of other waves (calculated by Equation (4)), and |L| represents the average of the trough values (calculated by Equation (5)). In Equation (3), to distinguish between the peak value and the trough value, when referring to the peak value, |P| = |H| or |P| = |Hx| (x = 0, 1, 2, 3, 4, 5); when referring to the trough value, |P| = |L| or |P| = |Lx| (x = 0, 1, 2, 3, 4, 5).
Ultrasonic continuous signal transmitting process (40 kHz-0.010 mm). (a) The complete waveform of the ultrasonic continuous signal at the transmitting transducer–soil interface is labeled with three typical patterns of the ultrasonic transmitting process: I, II, III. I represents the waveform at the initial stage of signal transmission (b(i)), marking the inflection point of the soil pressure change (A1–G1). II is the waveform of the signal transmission process (c(i)), marking the inflection point of the soil pressure change (A2–G2). III is the waveform at the end of the signal transmission (d(i)), which marks the inflection point of the soil pressure change (A3–G3). b(ii), c(ii) and d(ii) show the color changes in soil particles near the interface at the initial stage of signal transmission, during signal transmission process, and at the end of the signal transmission, respectively. The red color of the interface soil particles indicates that the interface soil is compressed, and the soil pressure is in the positive direction of the Y-axis; the blue color of the particles indicates that the interface soil is gradually loosening, and the soil pressure changes to the negative direction of the Y-axis. The same symbol labels in the diagram represent the same meaning or stage.
The correspondence between the change in interface soil pressure and the motion of the transmitting transducer. (c) The local enlargement of (a(i)). The motion curve of the transmitting transducer lags behind the soil pressure curve. The change in soil pressure and the motion of the transmitting transducer are divided into three phases: “The beginning” (a(i)), “Cyclical changes” (a(ii)), and “The end” (a(iii)). The blue curve indicates the change in soil pressure, while the red curve indicates the motion trajectory of the transmitting transducer. A4–D4 represent the position of the transmitting transducer when the soil pressure reaches its peak and trough (a(i)), and A5–E5 represent the inflection points where the magnitude and direction of the transmitting transducer’s velocity change (c). (b) shows the changes in the magnitude and direction of the transmitting transducer’s velocity during “The beginning” and “Cyclical changes”, with the meanings of A4–D4, and A5–E5 corresponding to those in (a(i),c). (d) illustrates the motion state during “The end” and after the transmitting transducer stops moving. The length of the arrow indicates the magnitude of the velocity value (b,d). The graph only expresses the correspondence between the soil pressure curve and the motion curve of the transmitting transducer on the time axis, and the magnitude of the curve shape does not represent the actual values.

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Propagation Laws of Ultrasonic Continuous Signals at the Transmitting Transducer–Soil Interface
  • Article
  • Full-text available

August 2024

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12 Reads

Zhinan Wang

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Hongwen Li

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Hanyu Yang

Ultrasonic detection is one of the main methods for information detection and has advantages in soil detection. Ultrasonic signals attenuate in soil, resulting in unique propagation laws. This paper studies the propagation laws of ultrasound in soil, focusing on the propagation characteristics of ultrasonic continuous signals at the transducer–soil interface. This study uses excitation frequency and amplitude as experimental factors and employs the discrete element simulation method to analyze the vibration characteristics of soil particles. It reveals the relationship between changes in soil pressure at the interface and the movement of the transducer. The results show that the motion curve of the transmitting transducer lags behind the soil pressure changes, and the energy of the ultrasonic signal increases with higher excitation frequency and amplitude. Specifically, the peak value of the first wave |H0| at 40 kHz and 60 kHz is 210% and 263% of that at 20 kHz, respectively. When the excitation amplitude increases from 0.005 mm to 0.015 mm, the value of the peak value of other waves |H| increases by 323%. This paper preliminarily reveals the propagation laws of ultrasonic continuous signals at the transducer–soil interface, providing theoretical support for the development of ultrasonic soil property detection instruments.

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Citations (76)

... These sensors are utilized in the system's feedback loop to provide reliable representations of actual operational parameters. Subsequently, through the system's main control algorithm, the precision of transplanting is achieved [14][15][16]. Developed countries such as the United States and Japan initiated earlier research on the control aspects of transplanters [17,18]. Xin Jin et al. designed a precision control system utilizing a GA-fuzzy PID controller, addressing issues of low precision and poor speed adaptability in the mechanized transplanting of rice potted seedlings. ...

Reference:

Design and Experiment of Electric Control System for Self-Propelled Chinese Herbal Medicine Materials Transplanter
A precise maize seeding parameter monitoring system at the end of seed tube: Improving monitoring accuracy using near-infrared diffusion emission-diffuse reflectance (NIRDE-DR)
  • Citing Article

  • December 2024

Computers and Electronics in Agriculture

Chengkun Zhai

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Hongwen Li

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Zhengyang Wu

... Shallow plowing layers can limit the development of crop roots. Through deep plowing and deep loosening techniques, the soil plow layer can be broken, the soil thickness can be increased, the soil structure can be improved, and a deeper root growth space can be provided for crops [4]. Meanwhile, returning straw to the field is also an effective method to increase soil organic matter content and improve soil physical properties. ...

Reference:

A Review of Research on Obstacle Factor Reduction Techniques for Medium and Low Yield Fields
Progress and Suggestions of Conservation Tillage in China
  • Citing Article

  • January 2024

Chinese Journal of Engineering Science

Caiyun Lu

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Xiwen Luo

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Hongwen Li

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Yinggang Ou

... [1][2][3] This significant phenomenon has been observed in discrete granular systems, including landslide particle flow, the size distribution of rubble in asteroid belts across the universe, avalanches, the design of agricultural machinery, and the quality control of industrial products. [4][5][6][7] The particle system is inherently disordered, consisting of numerous discrete granular entities. When subjected to external influences such as shear and vibration, variations in particle size, shape, density, friction, and other physical and mechanical properties give rise to complex dynamic behaviors, including fluidity, interaction, and segregation effects. ...

Reference:

Numerical study on inverse grading segregation mechanism of single coarse particles with different particle sizes under two-dimensional cyclic shear
Experimental research on vertical straw cleaning and soil tillage device based on Soil-Straw composite model
  • Citing Article

  • January 2024

Computers and Electronics in Agriculture

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Hongwen Li

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Dong He

... This is because in addition to the usual surface fluctuation factors, the complex and changeable soil physical environment, such as the surface covered by straw, root stubble planted into the soil, soil moisture, and soil penetration resistance, are inconsistent. The abovementioned reasons result in inconsistency of sowing depth for no-tillage planter, and instability problems become particularly prominent [4][5][6][7]. The current research on the sowing depth stability of no-tillage planter focuses on two control technologies to improve the sowing depth stability: using semi-active control for stability control [8,9] and using sensors to directly or indirectly measure the sowing depth in real time, and using the active executive component to actively control the downforce of the no-tillage planter row unit to stabilize the sowing depth, including pneumatic control and electro-hydraulic control [10][11][12][13][14]. ...

Reference:

Sowing depth stability analysis and test verification of no-tillage planter parallel four-bar row unit
Design and experiment of the pneumatic pressure control device for no-till planter

International Journal of Agricultural and Biological Engineering

Xinpeng Cao

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Hongwen Li

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[...]

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Xiuhong Wang

... The force when the rotary blade cuts the stubble is shown in Figure 5, f 1 is the friction between the stubble and the ground, f 2 is the friction between the stubble and the rotary blade, F N is the support force of the rotary blade to the stubble, and F g is the cohesion between the root-soil. It is assumed that the device remains stable throughout the operation process [19,20]. tion angle range of the anti-blocking device is 10° 30°. ...

Reference:

Design and Experiment of Oblique Stubble-Cutting Side-Throwing Anti-Blocking Device for No-Tillage Seeder
Design and Test of Single-Disc Opener for No-Till Planter Based on Support Cutting
Guangyuan Zhong

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Hongwen Li

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Jin He

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[...]

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Dong He

... Current research efforts mainly focus on optimization through changes in hole shape and layout, the design of auxiliary filling methods (Zhang et al., 2022), or altering the discharging methods. Pneumatic metering devices include vacuum (Wang et al., 2023), air blow (Han et al., 2018), and integrated pneumatic types , in which pressure differentials are used for filling; this results in high filling speeds and low seed damage rates, making them suitable for high-speed precision planting. However, pneumatic metering devices have high requirements in terms of operating environments, as they requiring a continuous and stable pressure differential environment. ...

Reference:

SIMULATION TEST FOR A PUSH-TYPE PRECISION METERING DEVICE BASED ON DISCRETE ELEMENT METHOD
THE INFLUENCE OF SEED VARIETY AND HIGH SEEDING SPEED ON PNEUMATIC PRECISION SEED METERING

Engenharia Agrícola

Chao Wang

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Hanyu Yang

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Jin He

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[...]

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Hongwen Li

... It is one of the simplest methods for assessing powder fluidity. With advancements in computer science and image processing technology, the precision of the AoR measurement has gradually improved (Ferreira et al., 2021;Klanfar et al., 2021;Müller et al., 2021;Tan et al., 2021;Wu et al., 2023). A smaller AoR indicates lower interparticle friction and better fluidity. ...

Reference:

Parameter calibration of discrete element model for gluten densification molding
Development and evaluations of an approach with full utilization of point cloud for measuring the angle of repose
  • Citing Article

  • June 2023

Computers and Electronics in Agriculture

Zhengyang Wu

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Hongwen Li

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Dong He

... To solve the difficulties in strip fertilization caused by the caking of organic fertilizer, a striping machine was designed to crush solid organic fertilizer. Additionally, on the basis of DEM-based simulation analysis, a field experiment was conducted to obtain the optimal parameter combination of the striping machine [16,17]. The research results provide equipment support for crushing and striping. ...

Reference:

Design and Parameter Optimization of a Combined Rotor and Lining Plate Crushing Organic Fertilizer Spreader
Experimental research on a propeller blade fertilizer transport device based on a discrete element fertilizer block model
  • Citing Article

  • May 2023

Computers and Electronics in Agriculture

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Hongwen Li

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Mengyao Sun

... Adjusting planting density and nitrogen application rate also plays a critical role in optimizing the growth, yield and quality of silage maize [15]. A study on cutting corn stalks using water jet technology found that the cutoff ratio of stalks and stem nodes increased with water jet pressure and decreased with target distance and traverse speed [16]. Experimental studies on the cutting process of stalk crops revealed the influence of cutting speed, raw material supply and number of counter cuts on specific energy consumption and average particle size, providing insights into the optimization of cutting process parameters [17]. ...

Reference:

Multi-Objective Optimization For Minimize Cutting Force and Power Consumption in Corn Stalk Chopping Processes
Experimental Study on the Effect of Water Jet Cutting Parameters on Maize Stalks
Dandan Cui

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Hongwen Li

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Jin He

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[...]

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Guangyuan Zhong