Defect Detection from Multi-frequency Limited Data via Topological Sensitivity

被引：36

作者：

Felix Funes, Jose ^{[1
]}

Manuel Perales, Jose ^{[2
]}

Rapun, Maria-Luisa ^{[1
]}

Manuel Vega, Jose ^{[1
]}

机构：

[1] Univ Politecn Madrid, ETSI Aeronaut & Espacio, Dept Matemat Aplicada Ingn Aeroesp, Madrid, Spain

[2] Univ Politecn Madrid, ETSI Aeronaut & Espacio, Dept Aeronaves & Vehiculos Espaciales, Madrid, Spain

来源：

JOURNAL OF MATHEMATICAL IMAGING AND VISION | 2016年 / 55卷 / 01期

关键词：

Non-destructive testing; Defect detection; Acoustic waves; Multi-frequency; Topological derivative; INVERSE SCATTERING; THIN; FUNCTIONALS; INCLUSIONS;

D O I：

10.1007/s10851-015-0611-y

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work we investigate the reconstruction of sound-hard obstacles buried in a bounded material medium by a non-iterative method based on the computation of topological derivatives. The main purpose is to suitably combine multi-frequency data in a fairly demanding measurement configuration: a very reduced number of aligned emitters and receivers are considered. The performance of the algorithm is illustrated for both single and multiple obstacle reconstructions.

引用

页码：19 / 35

页数：17

共 41 条

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Adams R.A., 1975, SOBOLEV SPACES PURE, V5

[2] A study on the topological derivative-based imaging of thin electromagnetic inhomogeneities in limited-aperture problems [J].