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Load identification method for pepper harvesting drum based on dynamic chaotic characteristics of vibration-torque
Chen Wei1, Jin Lei2, Xinyan Qin1
1College of Mechanical and Electrical Engineering, Shihezi University, Shihezi, China.
Plos One
|June 29, 2026
Summary
This study introduces a novel method for identifying pepper harvesting drum load states using chaotic dynamics of vibration-torque coupling. This approach enhances accuracy and interpretability for optimized agricultural machinery operation.
Area of Science:
- Agricultural Engineering
- Robotics and Automation
- Nonlinear Dynamics
Background:
- Accurate load-state identification is crucial for pepper harvesting drums to ensure operational stability and minimize fruit damage.
- Complex field disturbances challenge traditional load identification methods, necessitating more robust approaches.
Purpose of the Study:
- To develop a load identification method for pepper harvesting drums that improves accuracy, robustness, and interpretability.
- To enable real-time drum load-state information for adaptive adjustment of harvesting parameters.
- To reduce fruit damage and enhance the overall operational stability of pepper harvesters.
Main Methods:
- A six-dimensional nonlinear coupled dynamical system integrating Lorenz and Rössler models was constructed to represent vibration-torque coupling.
- A hybrid framework combining genetic algorithms and Gauss-Newton iteration was employed for parameter identification.
- The maximum Lyapunov exponent was extracted to quantify trajectory divergence for chaos-based load characterization.
Main Results:
- Optimal operating parameters were identified as 150 r/min drum rotational speed and 0.42 m/s forward speed.
- Under optimal conditions, the picking rate reached 99.05%, fruit damage rate was 2.35%, and average load identification accuracy was 90.47%.
- The proposed method demonstrated superior performance compared to conventional techniques and successful real-time implementation on embedded hardware.
Conclusions:
- The proposed chaotic dynamics-based method offers a robust and physically interpretable solution for pepper harvesting drum load identification.
- This approach supports adaptive control and optimization of pepper harvester operations, leading to improved efficiency and reduced crop damage.
- The findings are applicable to on-machine real-time load identification in agricultural machinery.
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