As a result of the uneven growth of rice, unbalanced vibration of threshing drum caused by stalk entanglement in combine harvester is more and more severe. In order to reveal the influence of unbalanced excitation on the roller axis locus during rice threshing, the stability of threshing drum was studied. The dynamic signal test and analysis system are used to test the axial trajectory of threshing drum. At the same time, the influence of the unbalanced excitation caused by the axis winding on the axis trajectory is analyzed by the experimental results. Axis locus rules under no-load and threshing conditions are obtained. In order to simulate the axial and radial distribution of unbalanced excitation along the threshing drum, the counterweight was distributed on the threshing drum instead of the entangled stalk. Then, the definite effect of unbalanced excitation on the rotating stability of threshing drum is analyzed. Results show that the amplitude of stem winding along the grain drum is larger in the vertical direction and smaller in the horizontal direction when compared with the unloaded state under 200 g weight. It was found that the amplitude in both horizontal and vertical directions decreased after 400 g and 600 g counterweights were added, respectively, to simulate the radial distribution of stalk winding along the grain barrel. Finally, it can be seen that with the increase in the weight of the counterweight, the characteristics of the trajectory misalignment of the threshing cylinder axis become more and more obvious. This study can provide reference for reducing the unbalanced excitation signal of threshing drum and improving driving comfort.

The self-propelled straw pickup baler in agricultural work is responsible for collecting and compressing straw to facilitate transportation and storage, while reducing waste and environmental pollution. Like other agricultural equipment, the straw pickup baler is a complex mechanical system. During operation, its excitation characteristics under multi-source stimuli and the coupling characteristics of various components are not yet clear. This paper analyzed the excitation mechanics property of each component of the self-propelled straw pickup baler and established balance equations. Based on the balance equations, the coupling characteristics of the structures were studied. Through experiments collecting excitation signals from multiple devices under different operating conditions, the vibration excitation signals of each component were obtained. The experiments revealed that the excitation and coupling signals in the Z direction are particularly evident. Based on experiments, the effective Z-direction vibration signal value on the left front of the chassis exceeds 7 m·s², while on the right front it increases from 1.995 m·s² to 7.287 m·s², indicating the most intense vibration direction. It was also found that, at the driver’s cab, the effective Z-direction vibration signal values at two response points, 11 and 12, both exceed 7 m·s². The data indicate significant vibrations occur in both the longitudinal and vertical directions. Using the Signal Analyzer module in MATLAB for signal processing, it was found that the prominent filtered signals consist of combustion excitation harmonics and continuous low-frequency vibrations from the compression mechanism. The periodic reciprocating compression motion of the crank-slider mechanism causes sustained impacts on the frame, leading to periodic changes in the vibration amplitude of the chassis. Thus, the vibration reduction of the compression mechanism’s periodic motion is key to reducing the overall vibration of the machine.

Due to the complex operating environment of combine harvesters, uneven terrain, multiple vibration sources, and complex transmission systems, failures easily occur in critical working components, especially the bolted connections of the vibrating screen. To address these issues, this study first established a bolt-tightening mechanical model. Secondly, a finite element simulation of the preload force was performed using Ansys Workbench software (2023R2). The simulation results showed that the bolt head area exhibits a ring-shaped strain distribution. To determine the critical state of bolt loosening, a single-bolt loosening test was conducted. The experimental results indicated that when the bolt pressure decreased to 78.4 N and the torque decreased to 0.5 N·m, bolt loosening intensified, and the pressure value showed a sharp decreasing trend. These pressure and torque values can be defined as the bolt loosening threshold, providing an important reference basis for subsequent monitoring and early warning. Finally, to more realistically simulate actual working conditions, a combine harvester field vibration test was conducted. By arranging triaxial acceleration sensors on the bolted connections of the vibrating screen, acceleration signals were collected under both low-speed and high-speed field operating conditions. Time–frequency analysis was performed on the signals to extract characteristic values for each measurement point. The field vibration test results showed that the characteristic values of the transmission shaft bolt structure of the vibrating screen were at a relatively high level, indicating that this part is subjected to a large vibration load. Furthermore, frequency domain feature analysis revealed that the vibration frequency components in this area are complex, which further increases the risk of bolt loosening. This study provides an in-depth analysis of the loosening characteristics and vibration characteristics of the vibrating screen’s bolted connections in combine harvesters. The results provide an important theoretical basis and technical support for the online monitoring of failures in the vibrating screen’s bolt structure.

Rice combine harvester conveyor troughs and their bolted connections are susceptible to vibration-induced failure due to operational and environmental excitations. Addressing the challenge of predicting the state of the combine harvester’s conveyor trough bolted structure prior to vibration-induced failure, this study addresses this by investigating signal analysis, system design, and condition identification for these critical components. Firstly, multi-point vibration signals from the conveyor trough were acquired and analyzed in the time-frequency domain. The analysis pinpointed the X-direction at the trough-frame connection (Point 5) as the most responsive location, with RMS peaking at 6.650 during header start-up (vs. 0.849 idle). Significant responses were also noted at Point 3 (Y-dir, 4.628) and Point 6 (X-dir, 3.896) under certain conditions (where Z-direction responses were minimal), identifying critical points that form the basis for condition assessment. Secondly, a vibration acquisition system was developed using a high-performance AD7606 ADC and A39C wireless technology. It features 16-bit resolution (0.00076 mm/s theoretical sensitivity), 8-channel synchronous sampling up to 200 kSPS, and rapid (0.8 s) wireless data transmission. This system meets the demands for high-frequency, high-precision monitoring of the bolted structure. Finally, after comparing machine learning algorithms, Support Vector Machine was chosen for its superior performance. Using a one-vs.-one strategy and data from critical points, an operational condition identification model was developed. Validation with field data confirmed high accuracy (96.9–99.7%) for principal states and low misclassification rates (<5%). This allows for precise identification of the bolted structure’s working status. The research presented in this study offers effective methodologies and technical underpinning for the condition monitoring of critical structural components in rice combine harvesters.

The combine harvester, as a multi-component machine comprising a cutting table, a conveyor, a threshing cylinder, and other components, experiences significant stress and bolt failures in cutting table-conveyor structures due to inherent excitation and the cutting table’s cantilevered design. To address bolt loosening monitoring in the critical joint, this paper designed a Wheatstone bridge circuit-based wireless monitoring system and a multi-channel Wheatstone bridge sensor, enabling multi-bolt monitoring on combine harvesters. Utilizing LoRa wireless communication, the system effectively overcomes the wiring complexity and deployment difficulties of traditional agricultural machinery bolt monitoring systems. The Wheatstone bridge sensor can precisely monitor pre-tightening forces up to 150 kN for M12–M24 bolts. A calibration test based on dynamic time warping (DTW) accurately fitted the sensor’s response to pressure and displacement with determination coefficients of 0.9780 and 0.9753. Then, a validation test focusing on connection bolts revealed a 95.12% overlap between the simulated measurement range and the calibration range under pre-tightening conditions. Furthermore, fitting curves for simulated measurements against tightening torque and angle yielded coefficients of determination of 0.9945 and 0.9939, which demonstrated accurate fitting of pre-tightening conditions and defined the monitoring range of 3.02 × 10¹² to 3.49 × 10¹². Finally, combined with simulation results, a field performance test confirmed the sensor’s ability to detect minute 5% pre-load reductions, achieve 200 ms data transmission to a host computer, and maintain lossless data transmission over 1.2 km. This sensor and system design provided a valuable reference for bolt loosening monitoring in combine harvesters and other agricultural machinery.

In the mechanized harvesting of root vegetables, loosening is a key factor that restricts harvesting efficiency. Existing mechanical loosening methods have poor loosening effect and high operational resistance. Therefore, more efficient agricultural machinery is needed to reduce energy consumption and improve harvesting efficiency. To this end, based on the efficient excavation mechanism of the first claw toe structure of the mole cricket forefoot, this paper designs the shovel tip structure of the bionic loosening shovel by extracting its contour curve and analyzing the excavation process, constructs the working resistance model and dynamic balance equation of the bionic loosening shovel, determines the optimal working parameters through two-factor and three-level orthogonal simulation experiments, and carries out comparative simulation experiments with the common loosening shovels. The results show that the optimal combination of operating parameters for the bionic loosening shovel is the rotational speed $\omega$ = 5 r/s and the traveling speed of the whole machine v = 0.5 m/s. The disturbance performance of the 31 bionic loosening shovel on the soil is improved by 51.59% compared with that of the common loosening shovel, and the working resistance is reduced by 12.17%. The results of this study proved that the bionic structure of the first claw toe of the mole cricket can significantly improve the working performance of the loosening shovel, which can effectively improve the cutting effect of the soil and reduce the energy loss during the working process.