Research on ultrasonic sparse DC-TFM imaging method of rail defects

Zhu, Wen-Fa; Xiang, Yanxun; Zhang, Haiyan; Yang, Cheng; Fan, Guopeng; Zhang, Hui

doi:10.1016/j.measurement.2022.111690

Cited by 19 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Firstly, it is necessary to have a basic understanding of Total Focusing Method (TFM) ultrasound imaging. This algorithm is based on full matrix capture (FMC), and if the phased array probe has N elements, a total of N × N transmit and receive operations need to be completed [90][91][92]. This means that the ultrasound is first transmitted by element 1, and all elements receive the signals.…”

Section: Hadamard Spatial Encodingmentioning

confidence: 99%

Coded Excitation for Ultrasonic Testing: A Review

Weng,

Gu,

Jin

2024

Sensors

View full text Add to dashboard Cite

Originating in the early 20th century, ultrasonic testing has found increasingly extensive applications in medicine, industry, and materials science. Achieving both a high signal-to-noise ratio and high efficiency is crucial in ultrasonic testing. The former means an increase in imaging clarity as well as the detection depth, while the latter facilitates a faster refresh of the image. It is difficult to balance these two indicators with a conventional short pulse to excite the probe, so in general handling methods, these two factors have a trade-off. To solve the above problems, coded excitation (CE) can increase the pulse duration and offers great potential to improve the signal-to-noise ratio with equivalent or even higher efficiency. In this paper, we first review the fundamentals of CE, including signal modulation, signal transmission, signal reception, pulse compression, and optimization methods. Then, we introduce the application of CE in different areas of ultrasonic testing, with a focus on industrial bulk wave single-probe detection, industrial guided wave detection, industrial bulk wave phased array detection, and medical phased array imaging. Finally, we point out the advantages as well as a few future directions of CE.

show abstract

Section: Hadamard Spatial Encodingmentioning

confidence: 99%

Coded Excitation for Ultrasonic Testing: A Review

Weng,

Gu,

Jin

2024

Sensors

View full text Add to dashboard Cite

show abstract

“…The TFM image is optimized by establishing a compensation factor based on the directivity function, taking into account the energy attenuation of ultrasonic waves. It has a better effect of suppressing the structural noise and improving the SNR in ultrasonic phased array inspection of high-attenuation metal coarse-crystalline materials [32,33]. However, there are also fewer studies on the application of this method to ultrasonic phased array inspection of HDPE piping materials.…”

Section: Introductionmentioning

confidence: 99%

High-Density Polyethylene Pipe Butt-Fusion Joint Detection via Total Focusing Method and Spatiotemporal Singular Value Decomposition

Zhang,

Wang,

Zhou

et al. 2024

Processes

View full text Add to dashboard Cite

High-density polyethylene (HDPE) pipes are widely used for urban natural gas transportation. Pipes are usually welded using the technique of thermal butt fusion, which is prone to manufacturing defects that are detrimental to safe operation. This paper proposes a spatiotemporal singular value decomposition preprocessing improved total focusing method (STSVD-ITFM) imaging algorithm combined with ultrasonic phased array technology for non-destructive testing. That is, the ultrasonic real-value signal data are first processed using STSVD filtering, enhancing the spatiotemporal singular values corresponding to the defective signal components. The TFM algorithm is then improved by establishing a composite modification factor based on the directivity function and the corrected energy attenuation factor by adding angle variable. Finally, the filtered signal data are utilized for imaging. Experiments are conducted by examining specimen blocks of HDPE materials with through-hole defects. The results show the following: the STSVD-ITFM algorithm proposed in this paper can better suppress static clutter in the near-field region, and the average signal-to-noise ratios are all higher than the TFM algorithm. Moreover, the STSVD-ITFM algorithm has the smallest average error among all defect depth quantification results.

show abstract

“…Yang et al [27] used GAs to optimize sparse arrays and improved image quality based on phase coherence weighting, to some extent eliminating artifacts around defects. Zhu et al [28] introduced energy attenuation compensation and directivity correction to enhance the imaging quality of sparse arrays, slightly reducing Array Performance Index (API) and signal-to-noise ratio (SNR) but greatly shortening imaging computation time. While these methods have substantially improved computational efficiency, they have not yet deeply explored the performance of sparse array layout optimization algorithms.…”

Section: Introductionmentioning

confidence: 99%

Multi-layered medium ultrasonic phased array sparse TFM imaging based on self-adaptive differential evolution algorithm

Yao,

Zhao,

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

Multilayer Composite material structures have been widely used in modern engineering fields. However, defects within these materials can adversely affect mechanical properties. Ultrasonic phased array Total Focusing Method (TFM) imaging has advantages of high precision and dynamic focusing over the entire range, achieving significant progress in homogeneous medium detection. However, heavy computational burdens of multilayer structures lead to inefficient imaging. To address this issue, a sparse-TFM imaging algorithm using ultrasonic phased arrays suitable for multilayer media is proposed in this paper. This method constructs a fitness function with constraints such as main lobe width and sidelobe peak. Its objective is to obtain the distribution of sparse array element positions using an Self-adaptive differential evolution algorithm(SaDE). Subsequently, the delay time of each array element in multilayer media sparse TFM is calculated using the Root Mean Square (RMS) principle and combined with amplitude weighting, the method corrects the imaging results. Compared with the Ray-based full-matrix capture and total focusing method method (Ray-based FMC/TFM), the root mean square-based full-matrix capture and total focusing method (RMS-based FMC/TFM), and the phase shift method (PSM), the experimental and simulation results demonstrate that the proposed method significantly reduces the imaging data volume, improves computational efficiency, and maintains quantitative errors within 0.2 mm.

show abstract

Research on ultrasonic sparse DC-TFM imaging method of rail defects

Cited by 19 publications

References 31 publications

Coded Excitation for Ultrasonic Testing: A Review

Coded Excitation for Ultrasonic Testing: A Review

High-Density Polyethylene Pipe Butt-Fusion Joint Detection via Total Focusing Method and Spatiotemporal Singular Value Decomposition

Multi-layered medium ultrasonic phased array sparse TFM imaging based on self-adaptive differential evolution algorithm

Contact Info

Product

Resources

About