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Enhanced Phased Array Imaging Through Reverberating Interfaces.
- Source :
-
AIP Conference Proceedings . 2019, Vol. 2102 Issue 1, p100005-1-100005-7. 7p. - Publication Year :
- 2019
-
Abstract
- A key challenge to achieve non-invasive industrial process analysis is the transmission of information through the vessel wall. Typical non-invasive technologies, such as Raman spectroscopy, require an optically transparent ‘window’ into the process to acquire the process data. In this work, ultrasonic phased arrays were used to image a dynamic process through planar steel vessel walls into a fluid load. Due to the acoustic impedance mismatch at the steel-fluid interface, only a small fraction of the excitation energy comes back to the receiver in the form of useful echoes from the process. Also, the ultrasonic energy that is not transmitted across the steel-fluid interface reverberates within the vessel wall, masking signals that are reflected from within the process. Here, the ultrasonic array was deployed using Full Matrix Capture (FMC) followed by the Total Focusing Method (TFM) that focusses the ultrasonic beam at every pixel in the image. However, the TFM algorithm is not spatial resolved, leading to multiples of the reverberations interfering throughout the desired image region. To extract the signals corresponding to the process fluid, a method has been developed called the Reverberation Pattern Gain Correction Method (RP-GCM). Firstly, the algorithm uses ray-tracing to predict the path length of reverberations from the steel-fluid interface. The signals in the FMC data set corresponding to those reverberations are then windowed and a gain filter applied, prior to application of the regular TFM process. The RP-GCM has been applied to a simulated FMC data set, developed in PZFlex (OnScale, USA). Initial results demonstrate the effectiveness of this method in separating the vessel reverberations from the ultrasonic echoes of interest relating to the process. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 2102
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- AIP Conference Proceedings
- Publication Type :
- Conference
- Accession number :
- 136374317
- Full Text :
- https://doi.org/10.1063/1.5099833