Power density based fatigue load spectrum editing for accelerated durability testing for tractor front axles

Abstract

The fatigue load spectrum is one of the most important parts in accelerated durability testing of agricultural machinery; however, the traditional editing approach just focuses on influence of load amplitude on mechanical components, which is not suitable for the agricultural machinery, the loads of which are broad in frequency bandwidth and time-varying in stress amplitude. Therefore, considering the comprehensive influence of load amplitude and frequency on the fatigue life of materials, a power-density-based fatigue load spectrum editing (PD-LSD) approach for accelerated durability testing is proposed ensuring that fatigue load spectrum for accelerated durability testing of tractor components can reproduce operation load characteristics of components. The concept of power density is introduced, and a fatigue analysis method based on power density and short-time Fourier transform (STFT) is discussed. For the approach of this study, STFT and stress-life (S–N) curve were used to derive accumulative power density (AccPD) of the load signal. The AccPD identified and extracted high fatigue damage segments of original load signal and obtained reduced accelerated load spectrum of components. Based on the load signal of the 88-kW tractor front axle, this approach and the time damage editing approach were applied to edit the load signal. The results show that, the accelerated load Signal Ⅰ based on the PD-LSD approach with a shorter length of time contained almost same damage of the original load signal, and the statistical parameters (mean value, root mean square and kurtosis coefficient) and the signal amplitude domain of the accelerated load Signal Ⅰ were more consistent with the original load signal, which verifies the acceleration, accuracy and effectiveness of the approach. This research supports fatigue testing and durability analysis for a key component of agricultural machinery.