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Sustainability
Volume 15
Issue 10
10.3390/su15108228
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Article

Accurate Detection of Concrete Pavement Thickness Based on Ultrasonic Array

by
Yu Tian
1,2,
Jinyu Wu
2,
Shifu Liu
2,*,
Jianming Ling
2,
Yaqi Zheng
3,
Xindong Zhao
2 and
Le Liu
2
1
Key Laboratory of Transport Industry of Road Structure and Material, Research Institute of Highway, Ministry of Transport, Beijing 100029, China
2
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC, Tongji University, Shanghai 200092, China
3
Taizhou Airport Investment Development Co., Ltd., Taizhou 317700, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(10), 8228; https://doi.org/10.3390/su15108228
Submission received: 14 March 2023 / Revised: 12 May 2023 / Accepted: 15 May 2023 / Published: 18 May 2023
(This article belongs to the Special Issue Structural Health Monitoring and Sustainable Built Structures)
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Abstract

Thickness detection of concrete pavement is a critical step in construction completion acceptance and serves as an important metric for subsequent pavement performance evaluations. The crux of thickness evaluation lies in determining the interface reflection echo propagation sound time. Based on the acoustic impedance difference between the surface layer and contact layer, pavement can be classified into two types: large-difference and small-difference. By examining the singularity of the detection signal, we employed the improved correlation coefficient method and the wavelet transform maximum value method to identify the interface reflection echo sound time. This study refines the traditional correlation coefficient method by using the surface direct wave as the reference signal, simplifying the signal analysis process. In actual detection, for the type of concrete pavement with large differences in acoustic impedance, the average relative error between the improved correlation coefficient method and the core drilling method can be reduced to 1.7%; for the type with small differences, the average relative error of the detection results obtained using the wavelet transform modulus maximum method can be reduced to 1.9%, showcasing high accuracy.
Keywords: ultrasonic array; concrete pavement; thickness detection; signal processing ultrasonic array; concrete pavement; thickness detection; signal processing

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MDPI and ACS Style

Tian, Y.; Wu, J.; Liu, S.; Ling, J.; Zheng, Y.; Zhao, X.; Liu, L. Accurate Detection of Concrete Pavement Thickness Based on Ultrasonic Array. Sustainability 2023, 15, 8228. https://doi.org/10.3390/su15108228

AMA Style

Tian Y, Wu J, Liu S, Ling J, Zheng Y, Zhao X, Liu L. Accurate Detection of Concrete Pavement Thickness Based on Ultrasonic Array. Sustainability. 2023; 15(10):8228. https://doi.org/10.3390/su15108228

Chicago/Turabian Style

Tian, Yu, Jinyu Wu, Shifu Liu, Jianming Ling, Yaqi Zheng, Xindong Zhao, and Le Liu. 2023. "Accurate Detection of Concrete Pavement Thickness Based on Ultrasonic Array" Sustainability 15, no. 10: 8228. https://doi.org/10.3390/su15108228

APA Style

Tian, Y., Wu, J., Liu, S., Ling, J., Zheng, Y., Zhao, X., & Liu, L. (2023). Accurate Detection of Concrete Pavement Thickness Based on Ultrasonic Array. Sustainability, 15(10), 8228. https://doi.org/10.3390/su15108228

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