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.

Combine harvesters, as essential equipment in agricultural engineering, frequently experience structural faults due to their complex structure and harsh working conditions, which severely affect their reliability and operational efficiency, leading to significant downtime and reduced agricultural productivity during critical harvesting periods. Therefore, developing accurate and timely Fault Detection and Diagnosis (FDD) techniques is crucial for ensuring food security. This paper provides a systematic and critical review and analysis of the latest advancements in research on data-driven FDD methods for structural faults in combine harvesters. First, it outlines the typical structural sections of combine harvesters and their common structural fault types. Subsequently, it details the core steps of data-driven methods, including the acquisition of operational data from various sensors (e.g., vibration, acoustic, strain), signal preprocessing methods, signal processing and feature extraction techniques covering time-domain, frequency-domain, time–frequency domain combination, and modal analysis among others, and the use of machine learning and artificial intelligence models for fault pattern learning and diagnosis. Furthermore, it explores the required system and technical support for implementing such data-driven FDD methods, such as the applications of on-board diagnostic units, remote monitoring platforms, and simulation modeling. It provides an in-depth analysis of the key challenges currently encountered in this field, including difficulties in data acquisition, signal complexity, and insufficient model robustness, and consequently proposes future research directions, aiming to provide insights for the development of intelligent maintenance and efficient and reliable operation of combine harvesters and other complex agricultural machinery.

Adhesion behavior between wet rice leaves and metal surfaces exacerbates the difficulty in separating and removing grains in the cleaning device. Reducing the adhesion between the wet rice leaves and the cleaning device is an important factor in improving the harvesting performance of rice combine harvesters. This paper investigates the possibility of reducing the adhesion between them. By studying the liquid shape characteristics between the removed grains and the surface, it was found that the adhesion force between the leaf and the surface is greatest when additional pressure is present. Based on biomimetic principles and the convex hull structure of a dung beetle’s head, a convex hull structure for the metal surface was designed to balance the atmospheric pressure on both sides of the leaf in order to eliminate additional pressure. Using the liquid bridge model between a spherical and a flat surface, a liquid bridge model for the leaf and convex hull surface was established. By optimizing the minimum liquid bridge force, the convex hull radius and distance were determined to be 2.47 mm and 1.38 mm, respectively. Contact and collision experiments verified that the convex hull surface is more effective in reducing the adhesion of moist leaves, providing a reference for future research on the cleaning methods of moist rice grains.

Complex mechanical systems, such as agricultural combine harvesters, are subjected to dynamic excitations from multiple coupled sources, compromising structural integrity and operational reliability. Disentangling these vibrations to identify dominant sources and quantify their transmission paths remains a significant engineering challenge. This study proposes a robust diagnostic framework to address this issue. We employed a multi-condition vibration test with sequential source activation and an improved Operational Transfer Path Analysis (OTPA) method. Applied to a harvester chassis, the results revealed that vibration energy is predominantly concentrated in the 0–200 Hz frequency band. Path contribution analysis quantified that the “cutting header → conveyor trough → hydraulic cylinder → chassis frame” path is the most critical contributor to vertical vibration, with a vibration acceleration level of 117.6 dB. Further analysis identified the engine (29.3 Hz) as the primary source for vertical vibration, while lateral vibration was mainly attributed to a coupled resonance between the threshing cylinder (58 Hz) and the engine’s second-order harmonic. This study’s theoretical contribution lies in validating a powerful methodology for vibration source apportionment in complex systems. Practically, the findings provide direct, actionable insights for targeted structural optimization and vibration suppression.

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.

The cleaning of wet rice threshed outputs presents a critical constraint on the operational efficiency of harvesters during humid conditions. This study aimed to quantify the specific impact of wet-state conditions on the physical properties of rice threshed outputs. Utilizing the Hertz–Mindlin with Johnson–Kendal–Roberts contact model, Plackett–Burman screening experiments were designed in Design-Expert to identify contact parameters significantly influencing the dynamic angle of repose. For the six most significant parameters, a six-factor, three-level Box–Behnken experimental design was implemented. Analysis of variance was performed on the experimental data, establishing a multivariate nonlinear regression model relating the dynamic angle of repose to the key contact parameters. Systematic measurements were conducted to determine the compositional content and key physical parameters of the constituent materials: the elastic modulus of paddy was 216.3 MPa; the elastic moduli of stalks (categorized by diameters of 4, 5, and 6 mm) were 5.59, 6.28, and 8.93 MPa, respectively; the paddy friction coefficient was 0.518; the stalk sliding friction coefficient was 0.566 and rolling friction coefficient was 0.115; and the surface moisture contents were 7.76% for paddy and 11.8% for stalks, respectively. The optimized contact parameter group of wet paddy and stalks was compared with the measured values. The relative error of the predicted angle of repose for the paddy was only 0.23%, and the error for the rice stalks was 1.3%. The precise contact parameters established in this study provide crucial foundational support for the development of subsequent CFD-DEM coupled numerical models.