Citation

BibTex format

@article{Zhang:2018:10.1121/1.5051641,
author = {Zhang, C and Huthwaite, P and Lowe, M},
doi = {10.1121/1.5051641},
journal = {Journal of the Acoustical Society of America},
pages = {1075--1088},
title = {Eliminating backwall effects in the phased array imaging of near backwall defects},
url = {http://dx.doi.org/10.1121/1.5051641},
volume = {144},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Ultrasonic array imaging is widely used to provide high quality defect detection and characterization. However, the current imaging techniques are poor at detecting and characterizing defects near a surface facing the array, as the signal scattered from the defect and the strong reflection from the planar backwall will overlap in both time and frequency domains, masking the presence of the defect. To address this problem, this paper explores imaging algorithms and relevant methods to eliminate the strong artefacts caused by the backwall reflection. The half-skip total focusing method (HSTFM), the factorization method (FM) and the time domain sampling method (TDSM) are chosen as the imaging algorithms used in this paper. Then, three methods, referred to as full matrix capture (FMC) subtraction, weighting function filtering, and the truncation method, are developed to eliminate or filter the effects caused by the strong backwall reflection. These methods can be applied easily with few tuning parameters or little prior knowledge. The performances of the proposed imaging techniques are validated in both simulation and experiments, and the results show the effectiveness of the developed methods to eliminate the artefacts caused by the backwall reflections when imaging near backwall defects.
AU - Zhang,C
AU - Huthwaite,P
AU - Lowe,M
DO - 10.1121/1.5051641
EP - 1088
PY - 2018///
SN - 0001-4966
SP - 1075
TI - Eliminating backwall effects in the phased array imaging of near backwall defects
T2 - Journal of the Acoustical Society of America
UR - http://dx.doi.org/10.1121/1.5051641
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000443620700058&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/64450
VL - 144
ER -