The importance of diagnosing the flow regime in bubble columns by noninvasive and easy-to-implement methods is well-known. Hence, the aim of this work is to diagnose the flow regime in a pilot scale bubble column by comparing the attractor that gives the fingerprint of a tested underlying hydrodynamic condition against the attractor of a reference condition, using the statistical S test, developed by Diks et al.(1) The attractors are reconstructed from the time series of two characteristic variables: the trajectory of a liquid flow follower, determined by CARPT (computer-assisted particle tracking), and pressure fluctuations. Since CARPT fully maps the hydrodynamics in multiphase systems in a Lagrangian sense, the tracer particle trajectory time series is used to establish the optimal set of parameters required for the S test when analyzing pressure fluctuations. This work demonstrates that the same set of optimal parameters determined when applying the S test to CARPT experimental time series leads to successful flow regime identification when applying the global S test to pressure fluctuation signals detected at various locations. This validates the use of pressure fluctuation signals in industrial settings as an economic way to detect flow regimes.