Phase coherence weighted ultrasound total focusing method towards the improved imaging of CFRP defects

Tian, Jiaxing; Chen, Zhan; Lu, Shun; Qi, Xin; Pu, Shiliang; Liu, Menglong

doi:10.1016/j.coco.2023.101736

Cited by 2 publications

(2 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on equation (12), DSAS can be understood as phase and amplitude weighting of DAS results and combining spatial coherence with echo intensity. The coherence of defect scattering signals in ultrasonic echoes is much greater than the coherence of noise signals generated by interlayer scattering [20]. DSAS results are greatly enhanced when the cross-channel data are highly coherent.…”

Section: Analysis Of Dsas For Improved Resolutionmentioning

confidence: 97%

See 1 more Smart Citation

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Zhao,

Zhang,

Zhang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

High-resolution ultrasonic imaging for defects in anisotropic multilayer carbon fiber reinforced polymers (CFRPs) is challenging because of the severe ultrasonic attenuation and the low signal-to-noise ratio (SNR) of echoes. The existing delay-multiply-and-sum (DMAS) beamforming outperforms delay-and-sum (DAS) beamforming in resolution, but with high computational complexity and energy loss. This paper presents a novel delay-sum-and-square (DSAS) beamforming algorithm. It takes full advantage of spatial coherence of captured data in the receiving and transmitting apertures. The non-coherent components caused by background noise are suppressed during the imaging. The back-wall reflection method (BRM) is used to correct the direction-dependent velocity. Full-matrix data is experimentally captured and processed on three different CFRP samples. Compared with DAS and DMAS, DSAS has a significant improvement in resolution, SNR and contrast. It demonstrates excellent defect characterization and noise suppression capability with only 17.4% computation time of DMAS.

show abstract

Section: Analysis Of Dsas For Improved Resolutionmentioning

confidence: 97%

“…Depending on the phase deviation of the signal, circular CF (CCF) can suppress sidelobes and noise effectively [19]. PCF, SCF, CCF are incorporated into ultrasound velocity corrected TFM [20]. The feasibility of these adaptive weighting algorithms for composites have been demonstrated and the lateral resolution of defects is improved.…”

Section: Introductionmentioning

confidence: 99%

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Zhao,

Zhang,

Zhang

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

Automatic detection of thermal fusion joints defects of high-density polyethylene gas pipes using ultrasonic total focusing method and deep learning

Chen,

Wang,

Xiao

et al. 2024

Preprint

View full text Add to dashboard Cite

Inspection of thermal fusion joints is essential for in-service high-density polyethylene (HDPE) gas pipe operating safety. A directivity-compensated circular coherence factor weighted total focusing method (D-CCF-TFM) algorithm is presented to solve the problem of low imaging quality of phased array ultrasonic testing during inspecting thermal fusion joints of HDPE pipes. The D-CCF-TFM leverages the circular coherence factor (CCF) to reduce noise interference during calculating the phase of defect and employs a directivity function to compensate sound field intensities in different directions, leading to obvious average signal-to-noise ratio (SNR) improvement compared to TFM, as confirmed through experiments on thermal fusion joint and test block. To automate defect detection in D-CCF-TFM images, an improved YOLOX algorithm is proposed, incorporating a convolutional block attention module (CBAM) and adopting the complete intersection over union (CIoU) as the regression loss. Evaluation of this improved YOLOX algorithm on a dataset of 2504 images yielded a mean average precision (mAP) of 99.15%, demonstrating its effect in detecting small defects. Thus, it provides theoretical and technical support for quality detection of thermal fusion joint welding.

show abstract

Phase coherence weighted ultrasound total focusing method towards the improved imaging of CFRP defects

Cited by 2 publications

References 21 publications

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Automatic detection of thermal fusion joints defects of high-density polyethylene gas pipes using ultrasonic total focusing method and deep learning

Contact Info

Product

Resources

About