Dynamic Vibration Modelling and Damping Optimisation of a Combine Harvester Cutter System Using Cuckoo Search Algorithm
The goal of this study is to help solve the problem of large vibrations generated by the motion of the cutter and pendulum ring system during the operation of a combined harvester, which in turn leads to significant vibrations in the cab. The kinematic equations of the cutter and pendulum ring system and the simplification of these complex equations into a two-degree-of-freedom system model are established in this study. On this basis, we apply the cuckoo search algorithm to obtain the optimal parameter combination of the cutter system, which can effectively reduce the vibration. The SIMULINK simulation model was constructed to obtain the simulation results of the vibration acceleration of the cutter system under four working conditions. The results prove that the simulation results for Case 1 are similar to the experimental measurements under the original parameters of the harvester. The vibration acceleration amplitude of the cutter is -240$ m/s^2 to 220 m/s^2, and the vibration acceleration amplitude of the pendulum ring is -13 m/s^2 to 15 m/s^2, which verifies the correctness of the simplified model and provides a basis for subsequent vibration damping of the cutter system. The experimental study shows that through parameter optimisation and adjustment, the cutter vibration decreased by 8.4% and the cab vibration decreased by 12.9%.
Authors
- Kuizhou Ji
- Zhiwu Yu (ORCID: https://orcid.org/0009-0000-9646-0738)
- Yuhang Chen (ORCID: https://orcid.org/0000-0002-4275-5458)
- Yanbin Liu (ORCID: https://orcid.org/0000-0003-3940-2560)
- Yaoming Li (ORCID: https://orcid.org/0000-0003-1297-9458)
- H. F. Wang (ORCID: https://orcid.org/0009-0002-3372-7874)
Publication Details
- Journal
- The International Journal of Acoustics and Vibration
- Published
- 2025-06-28
- DOI
- https://doi.org/10.20855/ijav.2025.30.22131
- Citations
- 1
- Primary Topic
- Belt Conveyor Systems Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.71