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Research on Fatigue Life Prediction Method of Key Component of Turning Mechanism Based on Improved TCD
The main objective of this paper is to accurately obtain fatigue life prediction for the key components of a turning mechanism using the improved theory of critical distances (TCD). The irregularly shaped rotating arm is the central stressed part of the turning mechanism, which contains notches. It...
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Published in: | Metals (Basel ) 2022-03, Vol.12 (3), p.506 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The main objective of this paper is to accurately obtain fatigue life prediction for the key components of a turning mechanism using the improved theory of critical distances (TCD). The irregularly shaped rotating arm is the central stressed part of the turning mechanism, which contains notches. It has been found that TCD achieves good results in predicting the fatigue strength or fatigue life of notched components with regular shape but is less commonly used for notched components with irregular shape. Therefore, TCD was improved and applied broadly to predict the fatigue life of an irregularly shaped rotating arm. Firstly, the notch depth and structure net width parameters were introduced into the low-order and low-accuracy classical TCD function to obtain a novel stress function with high computational efficiency and high accuracy, whereas the stress concentration factor was introduced to modify the length of critical distance. Secondly, the improved TCD was used to predict the fatigue strength of notched components with regular shape, and its accuracy was demonstrated by a fatigue experiment. Finally, the improved TCD was applied to predict the fatigue life of an irregularly shaped rotating arm. The deviation between prediction results and experimental results is less than 18%. The results demonstrate that the improved TCD can be applied effectively and accurately to predict the fatigue life of key components of turning mechanisms. |
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ISSN: | 2075-4701 2075-4701 |
DOI: | 10.3390/met12030506 |