Abstract
In this paper, a novel master S-N curve fitting method based on improved neighborhood rough set is proposed. The neighborhood relationship is used to granulate the fatigue information system of aluminum alloy welded joints, and the neighborhood rough set model is constructed from the information perspective. Based on conditional entropy, a neighborhood rough set attribute reduction algorithm (NRSBCE) is proposed. By means of this algorithm, comprehensive mathematical analysis model for fatigue life influencing factors is established and optimization of the S-N curve fitting method is introduced. In this work, the fatigue decision system of the aluminum welded joints is constructed firstly. The key influencing factors of the welded joints are obtained by means of NRSBCE algorithm subsequently. After that, the concept of fatigue characteristic domain is introduced according to the reduction result of the NRSBCE algorithm. Then, the master S-N curve fitting is carried out according to the divided fatigue characteristic domain. Correspondingly, a set of S-N curve clusters are fitted. Finally, fatigue analysis system for welded joints based on the fatigue characteristic domain is designed and developed. In the system, the equations of master S-N curve based on the mesh-insensitive structural stress method and the master S-N curve cluster based on the fatigue characteristic domain could be both obtained by uploading the practical fatigue test data of the aluminum alloy welded joints. This work helps to further reduce the dispersion degree of the fatigue sample data of the aluminum alloy welded joints thus provide reference for fatigue design.
Highlights
Considering the advantages such as light weight, easy processing, and good connectivity, welded structure is widely used in the mechanical equipment
FATIGUE DECISION SYSTEM OF WELDED JOINTS To acquire comprehensive analysis on the influencing factors of fatigue life of welded joints, neighborhood rough set theory is used to establish the analysis model for fatigue influencing factors of the aluminum welded joints
Based on the established fatigue decision system, NRSBCE algorithm is used for establishment of the analysis model of the influencing factors of the aluminum alloy welded joints
Summary
Considering the advantages such as light weight, easy processing, and good connectivity, welded structure is widely used in the mechanical equipment. In this study, aiming to further reduce the dispersion degree of fatigue samples of the aluminum alloy welded joints in the mesh-insensitive structural stress method and to obtain comprehensive analysis model for different fatigue life influencing factors of the welded joints, an improved neighborhood rough set reduction algorithm is proposed. The main contributions of our work are two aspects: One aspect, we extend the neighborhood rough set model by introducing conditional entropy as the uncertain measure of attribute importance Another aspect, concept of fatigue characteristic domain is proposed and determined so that a set of S-N curves instead of only one curve could be obtained in the mesh-insensitive structural stress method.
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