A PTV method based on ultrasound imaging and feature tracking in a low-concentration sediment-laden flow. (18th January 2018)

• Record Type: Journal Article
• Authors: Ma, Zhimin; Hu, Wenbin; Zhao, Xiaohong; Tao, Weiliang
• Is Part Of: Measurement science & technology. Volume 29:Number 2(2018:Feb.)
• Publication Date: 2018-01-18
• Subjects: PTV -- ultrasound imaging -- feature detector -- sediment-laden flow -- low concentration; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/aa98c6
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: This study aims to provide a particle tracking velocimetry (PTV) method based on ultrasound imaging and feature-tracking in a low-concentration sediment-laden flow. A phased array probe is used to generate a 2D ultrasound image at different times. Then, the feature points are extracted to be tracked instead of the centroids of the particle image. In order to better identify the corresponding feature point, each feature is described by an oriented angle and its location. Then, a statistical interpolation procedure is used to yield the displacement vector on the desired grid point. Finally a correction procedure is adopted because the ultrasound image is sequentially acquired line by line through the field of view. A simple test experiment was carried out to evaluate the performance. The ultrasound PTV system was applied to a sediment-laden flow with a low concentration of 1‰, and the speed was up to 10 cm s −1 . In comparison to optical particle image velocimetry (PIV), ultrasound imaging does not have a limitation in optical access. The feature-tracking method does not have a binarisation and segmentation procedure, which can result in overlapping particles or a serious loss of particle data. The feature-tracking algorithm improves the peak locking effect and measurement accuracy. Thus, the ultrasound PTV algorithm is a feasible alternative and is significantly more robust against gradients than the correlation-based PIV algorithms in a low-concentration sediment-laden fluid.