Considerable research effort has been devoted to distinguishing changes caused by the environmental variability from changes due to structural damage, but unfortunately, investigations studying the operational variability, such as traffic events, have been lacking. In order to obtain signals of high quality, we need to deal with baseline drift problems mainly caused by temperature changes and traffic jams. In this paper, we present a new baseline correction method, the most-crossing method, to deal with the baseline of the strain signals collected from a sensor network installed on a concrete bridge. It is a piece-wise method based on probability theory. This method needs only a few manual parameter selection and can be used automatically for real time baseline correction. We compare the performance of the most-crossing method with that of the first derivative method and the iterative polynomial method. The experimental results indicate that the most-crossing method is superior in dealing with civil engineering signals. Copyright (c) 2014 John Wiley & Sons, Ltd.