Abstract
The aim of this work is to explore the implementation of a structural change detection method proposed by the authors to detect internal rail defects. The B-Spline Signature Response (BSR) is a signature time history response of a dynamic system which is independent of loading, is a characteristic of the system, and captures the condition of the system at the time of acquisition without the need for identifying structural properties. The BSR changes only when the system changes. This is the basis of a non-parametric data-driven change detection method, which utilizes cross-correlation to distinguish variance in two BSRs of the same system extracted at different points in time. System change is determined when the correlation of two BSRs drops below a threshold value that is dependent on the type and level of change being monitored. The methodology is first demonstrated in a deterministic manner through computer simulations with a numerical sensitivity study on an idealized dynamic system and through an experimental study on a steel plate supported by a braced frame. Next, the method is implemented in a numerical computer simulation to detect a transverse cut in the rail head of a 2-meter-long segment of rail. A parametric study determined the optimal excitation and response types and locations, and the method was conducted successfully with both high and low frequency sampling rates, demonstrating flexibility that will facilitate laboratory and field implementation.