Acoustic tomography method facilitates mapping internal defects in real-time and in-situ without destructive testing. The method requires certain number of transmitter and receiver paths to reconstruct the slowness map of scanned area depending upon the target resolution. Once the hardware component is determined, the major software output to feed into the algorithm is the time of flight. There are sophisticated signal processing methods reported in literature to determine the time of flight (TOF) with better accuracy as compared to conventional threshold-based method. The most common approaches are wavelet-based or energy-based methods, which require transforming time history signal into different domains. Domain transformation is typically applied in laboratory-scale experiments. In this paper, a new arrival time pick-up approach based on defining outliers in the derivative of transient signal in time domain is evaluated in terms of accuracy, computational effort and power as compared to threshold-based and wavelet/energy-based methods reported in literature. The waveforms from experiments is used to study the influence of materials and signal-to-noise ratio on the accuracy of detecting the fastest wave mode. In addition, waveforms are also artificially generated with fixed wave velocity using numerical models to further evaluate the performance of the different methods (outlier-based, threshold-based and energy-based). The influence of tomography quality by using these to this method performs better in accuracy and efficiency.
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