Sectorial Plane Wave Imaging for Ultrasonic Array-Based Angle Beam Inspection

被引:0
|
作者
Lalith Sai Srinivas Pillarisetti
Gangadharan Raju
Anandamurugan Subramanian
机构
[1] IIT Hyderabad,NDT & E Lab, Department of Mechanical and Aerospace Engineering
[2] Kandi,Waygate Technologies
[3] Baker Hughes,undefined
[4] JFWTC,undefined
来源
Journal of Nondestructive Evaluation | 2021年 / 40卷
关键词
Ultrasonic linear arrays; Total focusing method; Plane wave imaging; Sectorial plane wave imaging; Multi-modal imaging; Finite element modeling;
D O I
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中图分类号
学科分类号
摘要
Advanced ultrasonic array-based imaging techniques such as the total focusing method (TFM) and plane wave imaging (PWI) have shown an increased efficiency to image smaller defects with high resolution. In this work, a new imaging technique called sectorial plane wave imaging (SPWI) is proposed by employing the principle of PWI to a framework of the conventional phased array sectorial scan. Besides, the SPWI algorithm is extended for multi-modal ultrasonic imaging using a linear array on an angular wedge. Initially, a plane strain finite element (FE) framework is presented to simulate the forward problem of elastic wave propagation excited by a linear array of elements. In this work, a specimen with an inclined notch is modeled, and multiple FE simulations are carried out to compute the full matrix capture array response. Subsequently, experiments are carried out on specimens with defects to demonstrate the proposed SPWI algorithm’s imaging capabilities. TFM, PWI, and SPWI algorithms are applied for image reconstruction, and their numerical and experimental results are compared. The direct and half-skip mode SPWI results are shown to capture all the specimen defects with good accuracy but at a reduced image resolution compared to TFM and PWI results due to a compromise in reception focusing. However, the enhanced processing speed of SPWI compared to TFM and PWI makes it suitable for quick multi-mode inspections and a viable replacement of the widely used conventional sector scan.
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