Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.