首页> 外文期刊>Computers & Structures >PCA-based damage classification of delaminated smart composite structures using improved layerwise theory
【24h】

PCA-based damage classification of delaminated smart composite structures using improved layerwise theory

机译:基于PCA的分层智能复合结构基于改进分层理论的损伤分类

获取原文
获取原文并翻译 | 示例

摘要

A Principal Component Analysis (PCA)-based damage classification method is proposed, to analyze delaminated smart composite structure. The delamination of smart composite laminates was modeled using the improved layerwise theory. The transient sensor signals obtained from the proposed model were analyzed by the system identification algorithm, to identify the system parameters for both healthy and delaminated structures. The identified system parameters were used to classify the damage categories, and to assess the damage severity, based on PCA results. The numerical results of cross-ply and angle ply composite laminates demonstrated that the proposed method resulted in excellent damage classification ability of delaminated smart composite structures.
机译:提出了一种基于主成分分析(PCA)的损伤分类方法,对分层的智能复合结构进行了分析。智能复合材料层压板的分层使用改进的分层理论建模。通过系统识别算法分析了从提出的模型中获得的瞬态传感器信号,以识别健康和分层结构的系统参数。根据PCA结果,使用已识别的系统参数对损坏类别进行分类,并评估损坏的严重程度。交叉层和角层复合材料层合板的数值结果表明,该方法导致分层智能复合材料结构具有优异的损伤分类能力。

著录项

  • 来源
    《Computers & Structures》 |2014年第8期|26-35|共10页
  • 作者单位

    Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 100-715, Republic of Korea;

    Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 100-715, Republic of Korea;

    Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 100-715, Republic of Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Delamination; Sensor; Composite laminates; System identification; Principal component analysis; Damage classification;

    机译:分层;传感器;复合层压板;系统识别;主成分分析;损害分类;

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