Active time-reverse imaging: Defect detection by coda waves in digital concrete physics

The localization of defects (i.e., fractures or damages) is essential in evaluating and assessing concrete in, for example, bridges. For this reason, this study presents a non-destructive testing method used primarily in passive seismology applied to active ultrasonic waveforms. Changes in the coda wave can provide information about the defect location by comparing two measurements with and without a defect.

The signal comparison of active transducer signals recorded with several receivers for material before and after an applied load is the basis of Active Time-Reverse Imaging (A-TRI). This study applies the TRI technique to the signal-based analysis of reinforced concrete specimens' acoustic emission (AE). Classical time-reverse modeling uses recorded passive signals, recorded laboratory, or field experiments as input. The recorded wavefield is reversed in time and backpropagated numerically through an adequate medium representation. The wavefield will then ideally focus on the original source location. In contrast to the standard passive TRI method, an active ultrasound method using the generated wavefield from an active source is used in A-TRI. The general workflow is divided into two basic steps: (1) Ultrasonic waves are emitted from single or multiple transducers on the surface and propagate through the original medium. Several receivers record the signals. (2) The experiment is repeated with precisely the same setting after a specific loading scenario. However, the potential damage is to be detected in this case. The difference of both signals is reversed in time and used as the input signal for a time-reverse simulation to locate the defect.

We see the A-TRI method as a complementary method to typically used coda-wave interferometry (CWI) to detect velocity changes in the medium. On the other hand, A-TRI can precisely determine the location of the defect. In the following, a feasibility study is presented in which the A-TRI method is applied to a synthetic data set to localize the defect.