Impact sounding has been recognized as an effective technique to detect delamination in concrete structures, such as concrete decks. An enormous amount of sounding data can be generated/collected by the autonomous inspection systems equipped with impactors and microphones. However, the main challenge in the practical application of this technology is the development of advanced data analysis approaches for identifying defects from impact sounding data. In this study, the empirical mode decomposition (EMD) analysis and power-spectral density (PSD) analysis are combined to extract useful features of sounding data generated by the impact hammer. It has been found that the EMD method can effectively eliminate noise from the captured data during the identification of features such as the fundamental frequency. Based on extracted features, a defect contour of the inspected structure can be generated for fast decision making and reliable inspection ratings of concrete structures.

Research Center/Lab(s)

INSPIRE - University Transportation Center


Principal Investigator: Anil K. Agrawal
Co-Principal Investigators: Jizhong Xiao

Grant Period: 30 Nov 2016 - 30 Sep 2022

Project Period: 31 Mar 2017 - 33 Mar 2020

Report Number


Document Type

Technical Report

Document Version

Final Version

File Type





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Publication Date

31 Mar 2020