Experimental investigation on static damage of concrete bridge under shear loading based on acoustic emission

Abstract

This article presents techniques used to observe the shear behaviour of modified Z-shaped concrete specimens, experimental results, and a method proposed to classify the shear cracking pattern of a concrete bridge based on acoustic emission (AE). Z-shaped specimens under shear were designed with steel plate reinforcement. A finite element (FE) model for this specimen was developed to validate the concrete crack propagation. AE parameters, including the peak amplitude, counts, cumulative energy, average frequency (AF) and rise angle (RA), were found to successfully correlate with the observed cracking process in the specimens. A cluster analysis based on the K-means algorithm was proposed to automatically classify the AE signal into tensile and shear clusters. An existing bridge underwent reinforcement and then testing under two test scenarios. AE signals were detected at the web of the bridge under heavy truck loads or full random traffic flows. Using the proposed crack classification showed that the signals from the bridge belonged to shear crack clusters characterized by lower AE energy. Thus, this work developed an AE method to classify cracks in concrete shear tests and extended the method to classify the shear cracks in a bridge to provide an early warning of future failure.

Keywords:

• Acoustic emission (AE)
• crack classification
• concrete bridge
• field test
• hollow slab
• K-means algorithm
• shear failure
• Z-shaped concrete specimen

Disclosure statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research reported in this article was conducted with the financial supports from the National Basic Research Program of China (Grant No. 2015CB057706), the National Science Fund of China (Grant No. 52078054), the department of Transportation of Hunan Province (Grant No. 2019329), the education department fund of Hunan Province (Grant No. 18B140), the Hunan Province Engineering Laboratory of Bridge Structure (CSUST) (Grant No.16KD02), and the postgraduate research innovation project of Hunan Province (Grant No. CX20190650). The support is gratefully acknowledged.