MATEC Web Conf.
Volume 139, 20172017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|Number of page(s)||5|
|Published online||05 December 2017|
Feature extraction and influence analysis for the structural performance of complex component
1 School of Mechanical & Automotive Engineering, FuJian University of Technology, Fuzhou 350118, P.R. China
2 Engineering College, Fujian Jiangxia University, Fuzhou 350108, P.R. China
* Corresponding author: firstname.lastname@example.org
To explore the structural performance of complex component deeply, a new method of feature extraction and influence analysis is proposed and its automatic mechanism is established. Using this mechanism, the complex component can be divided into several sub-regions, and the maximum stress in each sub-region can be extracted. After evaluating the danger situation for all sub-regions, the absolute influence of structural parameters for the characteristic stresses in feature regions are carried out based on Spearman rank correlation analysis. And then, the feature knowledge of complex component is acquired. Finally, the excavator boom is taken as an example, which demonstrates that the useful knowledge can be extracted from the structural performance of complex component automatically and effectively by this method.
Key words: Feature extraction; / Influence analysis; / Structural performance; / Spearman rank correlation coefficient; / Significant sensitive
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.