The vibration of the combine harvester header assembly directly affects harvesting efficiency and operational quality. To address the insufficient dynamic characterization of the cantilever conveying trough under complex field excitations, this study systematically analyzes the vibration response characteristics of the header assembly under multi-source coupled excitation through field experiments and theoretical modeling. Acceleration sensors arranged at three measurement points on the header bottom collected vibration data, revealing that the dominant vibration frequency of the header has a deterministic harmonic relationship with the threshing drum’s operating frequency (3rd harmonic on the left side, 1.5th harmonic on the right side), demonstrating dynamic coupling effects within the integrated system. Through acceleration response analysis at four symmetric measurement points on the connection, the external excitation force was quantified as a sinusoidal function correlated to the feed quantity (F = 1094.4 sin(50πt/3)). A damped pendulum model of the cantilever conveying trough was established using the Lagrange method. Validation results show that the error between the predicted steady-state swing amplitude and measured values is only 1.11–4.3%, confirming the effectiveness of this simplified model in characterizing the system’s steady-state response. This research provides a theoretical foundation and methodological support for dynamic characterization, parameter optimization, and stability control of the cantilever header system in combine harvesters.

Excessive swing of the cantilevered conveyor trough is a key issue restricting the working efficiency and operational stability of combine harvesters. To suppress its swing, this study established a dynamic model of the conveyor trough to reveal the influence mechanisms of the initial angle, overall length, and cylinder pivot length on its swing characteristics. Orthogonal experimental design and multi-factor analysis of variance were employed to systematically analyze the significance of these three factors on swing amplitude, identifying cylinder pivot length as the most dominant factor. Optimization results determined the optimal parameter combination as an initial angle of 48.33°, an overall length of 1.45 m, and a cylinder pivot length of 1.1 m. Field tests verified that this optimized scheme reduces the swing amplitude by 11.62%, with a minimal error of 0.57% between theoretical and measured values, providing a reliable theoretical and experimental basis for the low-vibration design of combine harvester conveying mechanisms.

Aiming at the problems of low separation efficiency and high impurity content in the cleaning process of moist rice threshed materials, this study systematically explored the influence mechanism of moisture on the segregation behavior of rice threshed products by combining physical experiments and CFD-DEM coupling simulation. Physical test results show that moist conditions significantly change the properties of threshed materials: the impurity mass fraction increases from 3.1% to 6.8%, the straw breakage rate rises from 5.97% to 6.99%, and the working load and unbalanced dynamic load of the threshing unit increase noticeably. On this basis, a gas–solid coupling simulation model of the cleaning device embedded with the Johnson–Kendall–Roberts (JKR) cohesive contact model is established. It is found that moist threshed materials exhibit an obvious stratified movement on the sieve surface, in which the bottom straw layer moves slowly while the upper material layer flows rapidly, resulting in a 50% increase in the sieve surface load. This phenomenon directly accounts for the rising impurity content observed in experiments. Through integrated experimental and simulation analysis, this research clarifies the macroscopic laws of moisture effects and reveals three key pathways for moisture to deteriorate cleaning performance: changing physical characteristics of threshed materials, enhancing inter-particle adhesion, and forming stratified movement. The findings provide an innovative research scheme and reliable theoretical support for the design and optimization of high-efficiency cleaning devices for rice combine harvesters.

Due to topographic and climatic constraints, a large proportion of grain is cultivated in relatively flat areas, where it is highly susceptible to lodging caused by natural disasters or improper field management. However, research on the full-process intelligent harvesting of lodged grain remains limited. This paper aims to examine the current state of the grain industry and its level of mechanization, with a focus on the challenges in mechanized harvesting of lodged grain, including the lack of suitable equipment, high harvest losses, and low operational efficiency. The article provides a comprehensive review of the key technologies critical to achieving fully automated intelligent harvesting, including the acquisition of lodging information, combine harvester operations, and the development of intelligent modular systems. It also summarizes recent advancements in cutting-edge mechanized grain harvesting equipment. Additionally, the article presents recommendations for the future development and research of mechanized grain harvesting technologies, focusing on grain lodging feature recognition, equipment modularization, and the integration of intelligent technologies. The aim is to offer valuable insights for advancing progress in this field.