首页> 外文会议>Annual American Control Conference >A decomposition multi-objective optimization method based on dynamic weight adjustment for infrared thermal image defect feature adaptive extraction method
【24h】

A decomposition multi-objective optimization method based on dynamic weight adjustment for infrared thermal image defect feature adaptive extraction method

机译:基于动态重量调整的红外热图像缺陷的分解多目标优化方法特征自适应提取方法

获取原文
获取外文期刊封面目录资料

摘要

In order to visually display defect features, it is necessary to extract features from infrared thermal sequence data. Due to the different types of pixels in the damaged region are motivated by the heat after the temperature change is different, according to the transient thermal responses (TTRs) of pixels change trend, with the improved mean-shift clustering algorithm relies on pixel itself in the space the temperature characteristic of adaptive partition for defect type, obtain the TTRs of different types of damage. In typical TTRs of extracted from each damage set, considering the similarity of similar pixel point temperature and similar pixel point temperature difference, choose the multi-objective optimization algorithms, but may occur in the process of solving uneven Pareto front led to the decrease of the diversity of solution set, so here use a dynamic weighting multi-objective optimization adjustment of decomposition algorithm from the various damage focus on selected typical TTRs.
机译:为了在视觉上显示缺陷功能,有必要从红外热序数据中提取特征。由于损坏区域中的不同类型的像素通过热量在温度变化不同之后,根据像素改变趋势的瞬态热响应(TTRS),改进的平均移位聚类算法依赖于像素本身缺陷类型的自适应分区温度特性的空间,获得不同类型损坏的TTR。在从每个损伤集中提取的典型TTR中,考虑到相似像素点温度和类似像素点温度差的相似性,选择多目标优化算法,但可能发生在求解不均匀的帕匹托前面的过程中的过程中的降低解决方案集的多样性,因此在这里使用来自各种损坏的分解算法的动态加权多目标优化调整在所选择的典型TTR上的各种损坏。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号