Affiliation:
1. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
2. Li Auto Vehicle Control Operation System, Hangzhou 310000, China
Abstract
The high-cycle bending fatigue experiment is one of the most important necessary steps in guiding the crankshaft manufacturing process, especially for high-power engines. In this paper, an accelerated method was proposed to shorten the time period of this experiment. First, the loading period was quickened through the prediction of the residual fatigue life based on the unscented Kalman filtering algorithm approach and the crack growth speed. Then, the accuracy of the predictions was improved obviously based on the modified training section based on the theory of fracture mechanics. Finally, the fatigue limit load analysis result was proposed based on the predicted fatigue life and the modified SAFL (statistical analysis for the fatigue limit) method. The main conclusion proposed from this paper is that compared with the conventional training sections, the modified training sections based on the theory of fracture mechanics can obviously improve the accuracy of the remaining fatigue life prediction results, which makes this approach more suitable for the application. In addition, compared with the system’s inherent natural frequency, the fatigue crack can save the experiment time more effectively and thus is superior to the former factor as the failure criterion parameter.
Funder
Natural Science Youth Foundation of Jiangsu Province of China
Research Start-up Foundation of Nanjing Forestry University
Youth Foundation for Science, Technology and Innovation of Nanjing Forestry University
Subject
General Materials Science
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