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The concrete quality of supporting layer in ballastless track is important for the safe operation of a high-speed railway (HSR). However, the supporting layer is covered by the upper track slab and the functional layer, and it is difficult to detect concealed defects inside the supporting layer. To solve this problem, a method of elastic wave velocity imaging is proposed to analyze the concrete quality. First, the propagation path of the elastic wave in the supporting layer is analyzed, and a head-wave arrival-time (HWAT) extraction method based on the wavelet spectrum correlation analysis (WSCA) is proposed. Then, a grid model is established to analyze the relationships among the grid wave velocity, travel route, and travel time. A loss function based on the total variation is constructed, and an inverse method is applied to evaluate the elastic wave velocity in the supporting layer. Finally, simulation and field experiments are conducted to verify the suppression of noise signals and the accuracy of an inverse imaging for the elastic wave velocity estimation. The results show that the WSCA analysis could extract the HWAT efficiently, and the inverse imaging method could accurately estimate wave velocity in the supporting layer.

- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.7 pp.1760-1764

- Publication Date
- 2020/07/01

- Publicized
- 2020/04/08

- Online ISSN
- 1745-1361

- DOI
- 10.1587/transinf.2019EDL8216

- Type of Manuscript
- LETTER

- Category
- Fundamentals of Information Systems

Yong YANG

Shijiazhuang Tiedao University

Junwei LU

Shijiazhuang Tiedao University

Baoxian WANG

Shijiazhuang Tiedao University

Weigang ZHAO

Shijiazhuang Tiedao University

The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.

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Yong YANG, Junwei LU, Baoxian WANG, Weigang ZHAO, "Analysis on Wave-Velocity Inverse Imaging for the Supporting Layer in Ballastless Track" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 7, pp. 1760-1764, July 2020, doi: 10.1587/transinf.2019EDL8216.

Abstract: The concrete quality of supporting layer in ballastless track is important for the safe operation of a high-speed railway (HSR). However, the supporting layer is covered by the upper track slab and the functional layer, and it is difficult to detect concealed defects inside the supporting layer. To solve this problem, a method of elastic wave velocity imaging is proposed to analyze the concrete quality. First, the propagation path of the elastic wave in the supporting layer is analyzed, and a head-wave arrival-time (HWAT) extraction method based on the wavelet spectrum correlation analysis (WSCA) is proposed. Then, a grid model is established to analyze the relationships among the grid wave velocity, travel route, and travel time. A loss function based on the total variation is constructed, and an inverse method is applied to evaluate the elastic wave velocity in the supporting layer. Finally, simulation and field experiments are conducted to verify the suppression of noise signals and the accuracy of an inverse imaging for the elastic wave velocity estimation. The results show that the WSCA analysis could extract the HWAT efficiently, and the inverse imaging method could accurately estimate wave velocity in the supporting layer.

URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDL8216/_p

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@ARTICLE{e103-d_7_1760,

author={Yong YANG, Junwei LU, Baoxian WANG, Weigang ZHAO, },

journal={IEICE TRANSACTIONS on Information},

title={Analysis on Wave-Velocity Inverse Imaging for the Supporting Layer in Ballastless Track},

year={2020},

volume={E103-D},

number={7},

pages={1760-1764},

abstract={The concrete quality of supporting layer in ballastless track is important for the safe operation of a high-speed railway (HSR). However, the supporting layer is covered by the upper track slab and the functional layer, and it is difficult to detect concealed defects inside the supporting layer. To solve this problem, a method of elastic wave velocity imaging is proposed to analyze the concrete quality. First, the propagation path of the elastic wave in the supporting layer is analyzed, and a head-wave arrival-time (HWAT) extraction method based on the wavelet spectrum correlation analysis (WSCA) is proposed. Then, a grid model is established to analyze the relationships among the grid wave velocity, travel route, and travel time. A loss function based on the total variation is constructed, and an inverse method is applied to evaluate the elastic wave velocity in the supporting layer. Finally, simulation and field experiments are conducted to verify the suppression of noise signals and the accuracy of an inverse imaging for the elastic wave velocity estimation. The results show that the WSCA analysis could extract the HWAT efficiently, and the inverse imaging method could accurately estimate wave velocity in the supporting layer.},

keywords={},

doi={10.1587/transinf.2019EDL8216},

ISSN={1745-1361},

month={July},}

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TY - JOUR

TI - Analysis on Wave-Velocity Inverse Imaging for the Supporting Layer in Ballastless Track

T2 - IEICE TRANSACTIONS on Information

SP - 1760

EP - 1764

AU - Yong YANG

AU - Junwei LU

AU - Baoxian WANG

AU - Weigang ZHAO

PY - 2020

DO - 10.1587/transinf.2019EDL8216

JO - IEICE TRANSACTIONS on Information

SN - 1745-1361

VL - E103-D

IS - 7

JA - IEICE TRANSACTIONS on Information

Y1 - July 2020

AB - The concrete quality of supporting layer in ballastless track is important for the safe operation of a high-speed railway (HSR). However, the supporting layer is covered by the upper track slab and the functional layer, and it is difficult to detect concealed defects inside the supporting layer. To solve this problem, a method of elastic wave velocity imaging is proposed to analyze the concrete quality. First, the propagation path of the elastic wave in the supporting layer is analyzed, and a head-wave arrival-time (HWAT) extraction method based on the wavelet spectrum correlation analysis (WSCA) is proposed. Then, a grid model is established to analyze the relationships among the grid wave velocity, travel route, and travel time. A loss function based on the total variation is constructed, and an inverse method is applied to evaluate the elastic wave velocity in the supporting layer. Finally, simulation and field experiments are conducted to verify the suppression of noise signals and the accuracy of an inverse imaging for the elastic wave velocity estimation. The results show that the WSCA analysis could extract the HWAT efficiently, and the inverse imaging method could accurately estimate wave velocity in the supporting layer.

ER -