An Algorithm for Correcting Levels of Useful Signals on Interpretation of Eddy-Current Defectograms

To ensure rail traffic safety, rails are regularly inspected by various approaches and methods of nondestructive testing, including eddy-current flaw detection methods. In this regard, automatic analysis of large datasets (defectograms) output by the corresponding equipment is a relevant problem. This analysis constitutes a process of identifying damaged or defective sections along with identifying structural elements of rails within defectograms. The article continues a series of studies on the problem of automatic recognition of images of flaws and structural elements of rails in eddy-current defectograms. These images are formed exclusively on useful signals, which are determined on amplitude threshold levels calculated automatically on the eddy-current data. The previous algorithm for identifying threshold levels was geared primarily towards cases in which the vast a majority of the signals output by the flaw detector are rail noise. A signal is considered useful and is a subject to further analysis if its amplitude exceeds the relevant noise threshold by two times. This article is concerned with the problem of adjusting threshold levels in order to make it possible to identify extensive rail surface flaws. An algorithm for calculating threshold levels of rail noise amplitudes with their subsequent correction in the case of a large number of useful signals from extensive flaws is proposed. Examples of the algorithm’s application to real eddy-current data are provided.