Cleaning is one of the most important steps in the harvesting process, and the prolonged and high-load operation of the vibrating sieve can decrease its reliability. To uncover the structural flaws of the cleaning sieve in the crawler combine harvester and establish a foundation for quality inspection, this paper proposes a method for durability testing and analysis using vibration and strain signals. Via the modal analysis of the cleaning sieve, the most susceptible areas for fault signals are identified. Subsequently, a specialized test rig exclusively designed for the examination of the durability of the cleaning sieve is constructed. After following 96 h of uninterrupted operation, the vibration plate of the cleaning sieve sustains damage, resulting in atypical noise. A signal analysis reveals that the primary vibration signal of the cleaning sieve primarily consists of a fundamental frequency of 5 Hz, corresponding to the driving speed, as well as a frequency doubling signal of 50 Hz. After the occurrence of damage, the peak amplitude of the received vibration signal increases by over 86.3%. Furthermore, the strain gauge sensor situated on the support plate of the rear sieve detects anomalous signals with frequencies exceeding 300 Hz, which are accompanied by a considerable rise in the power spectral density. This research has significant importance for enhancing the service life of the cleaning sieve and optimizing the overall machine efficiency.

Modeling of working environment and coverage path planning method of combine harvesters

The main reason for the massive loss of rapeseed in mechanized harvesting is the mismatch between the harvester requirements and the pod shatter resistance and plant branching characteristics. Low pod resistance, entanglement caused by excessive branches, and inconsistent pod maturity are primary mismatch problems. However, studies on rape characteristics by integrating agricultural machinery and agronomy are limited. A total of 15 varieties were planted for research from 2016 to 2018. In this paper, the Two-Degree-of-Freedom (2-DOF) collision method was adopted to evaluate the pod shatter resistance taken from the field, and the plant agronomic characteristics and their correlation were investigated. In 2020, a screened variety of C6009 with higher shatter resistance and suitable plant features for mechanized harvesting was planted in large areas and harvested by machines for verification. The test results demonstrated that the compact plant varieties with high branches might be more favorable for yield and shatter resistance. The field harvest loss of the screened variety was significantly less than that of the control group. It provides a reliable reference for agronomic experts in terms of rape variety improvement and agricultural machinery experts regarding the optimization of rape harvesters.

Effective indoor testing on a four-poster rig of agricultural machinery should mimic the real-world environment while the machinery is in farming and transportation. The emerging load spectrum extrapolation and compilation are capable of speeding up the use of the indoor vibration testing of tractors. However, most ground load spectrum studies consider a particular type of ground rather than all the rough farmland conditions that tractors experience daily. Such a problem inevitably raises doubts about validating the load spectrum-based fatigue durability and reliability testing of tractors. For a remedy, this article proposes a CEEMDAN-POT (Peak Over Threshold) model to comprehensively build a full life-cycle ground load spectrum of tractor vibration with six ground conditions and different field operations. The study acquires the real four vertical acceleration signals from the front and rear axles of the tractor to collect representative vibration load data. Furthermore, the study refines the measured load data by proposing a CEEMDAN-Wavelet threshold method, which is proved to be effective for the load signal decomposition and denoising. Lastly, the study presents a time domain extrapolation method, integrating the sample principle of the POT model, the proper parameter estimation with the Generalized Pareto Distribution (GPD) function, and the POT super-threshold model. The statistical analysis implies that the produced load spectrum fully preserves the statistical features observed in the original one. After extrapolation, the overall distribution of the rainflow matrix becomes more consistent while the mean and amplitude of the spectrum data increase. This study unifies a load spectrum of tractors operating and transporting on various farm ground conditions, providing the real load data of the indoor four-poster rig test.