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AUTOMATIC ACQUISITION OF STRESS DISTRIBUTION CHARACTERISTIC AND INFLUENCE KNOWLEDGE FOR LARGE-SCALE COMPONENT
To explore the difference of the factors influencing stress distribution for large-scale component,an automatic mechanism of acquiring stress distribution characteristics and influence knowledge was established. For the large-scale component with continuous changing geometry,a stress survey method was proposed to extract maximum stress of each sub-region for every sample. After evaluating the danger situation,some characteristic regions were determined and the characteristic stress sets were acquired. Furthermore,the influences of structural parameters for characteristic stresses and lightweight index were analyzed. By constructing knowledge reasoning model based on multi-states adjusting strategy,the main influence factors as well as their saliency under different expectations were acquired to reflect the priority of structural parameters for adjusting. Finally,the gooseneck-type boom was taken as an example,which demonstrates that the process of modeling,analysis,feature extraction and knowledge acquisition can be realized automatically and the useful knowledge can be acquired efficiently and flexibly for the intelligent optimization of large-scale component.
AUTOMATIC ACQUISITION OF STRESS DISTRIBUTION CHARACTERISTIC AND INFLUENCE KNOWLEDGE FOR LARGE-SCALE COMPONENT
To explore the difference of the factors influencing stress distribution for large-scale component,an automatic mechanism of acquiring stress distribution characteristics and influence knowledge was established. For the large-scale component with continuous changing geometry,a stress survey method was proposed to extract maximum stress of each sub-region for every sample. After evaluating the danger situation,some characteristic regions were determined and the characteristic stress sets were acquired. Furthermore,the influences of structural parameters for characteristic stresses and lightweight index were analyzed. By constructing knowledge reasoning model based on multi-states adjusting strategy,the main influence factors as well as their saliency under different expectations were acquired to reflect the priority of structural parameters for adjusting. Finally,the gooseneck-type boom was taken as an example,which demonstrates that the process of modeling,analysis,feature extraction and knowledge acquisition can be realized automatically and the useful knowledge can be acquired efficiently and flexibly for the intelligent optimization of large-scale component.
AUTOMATIC ACQUISITION OF STRESS DISTRIBUTION CHARACTERISTIC AND INFLUENCE KNOWLEDGE FOR LARGE-SCALE COMPONENT
HUA HaiYan (author) / LIN Hua (author)
2019
Article (Journal)
Electronic Resource
Unknown
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