In an effort to overcome this gap, T.D. Williamson (TDW) participated in a DOT project that resulted in the development of an SSWC classifier. The classifier leverages the data collected by the MDS™ platform, which incorporates six primary technologies (SMFL, MFL, IDOD, LFM, GEO, XYZ) that collect multiple data streams simultaneously.

TDW then validated the classifier on 700 SSWC calls made on 75 inline inspection runs over eight years. Dig feedback data available for 201 of these calls provided confidence that the classifier replicates the discrimination ability of the subject matter expert but avoids error-prone human input.

To date, the classifier has proven highly effective in discriminating SSWC.

In 2022, TDW published an industry-first specification that characterised the performance of the SSWC classifier. This white paper describes the statistical backing of the published specification, demonstrating the field data basis and validation.

Download this white paper from T.D. Williamson today to find out more.