Displacement field denoising for high-temperature digital image correlation using principal component analysis

被引：20

作者：

Hao, Wenfeng ^{[1
]}

Zhu, Jianguo ^{[1
]}

Zhu, Qi ^{[1
]}

Chen, Lei ^{[1
]}

Li, Longkang ^{[2
]}

机构：

[1] Jiangsu Univ, Fac Civil Engn & Mech, Zhenjiang 212013, Jiangsu, Peoples R China

[2] China Univ Min & Technol Beijing, Sch Mech & Architectural Engn, Beijing, Peoples R China

来源：

MECHANICS OF ADVANCED MATERIALS AND STRUCTURES | 2017年 / 24卷 / 10期

基金：

中国国家自然科学基金;

关键词：

High-temperature; digital image correlation; principal component analysis; thermal disturbance; noise reduction; singular value decomposition; STRAIN-MEASUREMENT;

D O I：

10.1080/15376494.2016.1196787

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Principal component analysis (PCA) was extended to minimize the noise effect in digital image correlation (DIC) measurement under a high-temperature atmosphere environment. First, the principle of PCA was introduced, and the singular vectors and singular values for each component of the displacement fields from DIC were obtained. Then, the simulated high-temperature speckle images were developed to investigate the influences of noise on the DIC method under a high-temperature environment. Finally, the displacement fields of several special conditions were extracted from the simulated speckle images and experimental images; the effects of noise on the PCA were also analyzed.

引用

页码：830 / 839

页数：10

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