Baseline subtraction is commonly used in guided wave structural health monitoring to identify the signal changes produced by defects. However, before subtracting the current signal from the baseline, it is essential to compensate for changes in environmental conditions such as temperature between the two readings. This is often done via the baseline stretch method that seeks to compensate for wave velocity changes with temperature. However, the phase of the signal generated by the transduction system is also commonly temperature sensitive and this effect is neglected in the usual compensation procedure. This article presents a new compensation procedure that deals with both velocity and phase changes. The results with this new method have been compared with those obtained using the standard baseline stretch technique on both a set of experimental signals and a series of synthetic signals with different coherent noise levels, feature reflections, and defect sizes, the range of noise levels and phase changes being chosen based on initial experiments and prior field experience. It has been shown that the new method both reduces the residual signal from a set baseline and enables better defect detection performance than the conventional baseline signal stretch method under all conditions examined, the improvement increasing with the size of the temperature and phase differences encountered. For example, in the experimental data, the new method roughly halved the residual between baseline and current signals when the two signals were acquired at temperatures 15°C apart.

This article describes a new system for high-speed and noncontact rail integrity evaluation being developed at the University of California at San Diego. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection has been tested at the University of California at San Diego Rail Defect Farm. In addition to a real-time statistical analysis algorithm, the prototype uses a specialized filtering approach due to the inherently poor signal-to-noise ratio of the air-coupled ultrasonic measurements in rail steel. The laboratory results indicate that the prototype is able to detect internal rail defects with a high reliability. Extensions of the system are planned to add rail surface characterization to the internal rail defect detection. In addition to the description of the prototype and test results, numerical analyses of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach algorithm and some of these results are shown. The numerical analysis has helped designing various aspects of the prototype for maximizing its sensitivity to defects.

In guided wave structural health monitoring, defects are typically detected by identifying high residuals obtained via the baseline subtraction method, where an earlier measurement is subtracted from the ‘current’ signal. Unfortunately, varying environmental and operational conditions, such as temperature, also produce signal changes and hence, potentially, high residuals. While the majority of the temperature compensation methods that have been developed target the changed wave speed induced by varying temperature, a number of other effects are not addressed, such as changes in attenuation, the relative amplitudes of different modes excited by the transducer and the transducer frequency response. A temperature compensation procedure is developed whose goal is to correct any spatially dependent signal change that is a systematic function of temperature. At each structural position, a calibration function that models the signal variation with temperature is computed and is used to correct the measurements, so that in the absence of a defect the residual is reduced to close to zero. This new method was applied to a set of guided wave signals collected in a blind trial of a guided wave pipe monitoring system employing the T(0,1) mode, yielding residuals de-coupled from temperature and reduced by at least 50% compared to those obtained using the standard approach at positions away from structural features, and by more than 90% at features such as the pipe end. The method therefore promises a substantial improvement in the detectability of small defects, particularly at existing pipe features.

A rail inspection system based on ultrasonic guided waves and non-contact (air-coupled) ultrasound transduction is under development at the University of California at San Diego. The system targets defects in the rail head that are major causes of train accidents. Because of the high acoustic impedance mismatch between air and steel, the non-contact system poses severe challenges and questions on the defect detection performance. This article presents an extensive numerical study, conducted with a local interaction simulation approach, to model the ultrasound propagation and interaction with defects in the proposed system. This model was used to predict the expected detection performance of the system in the presence of various defects of different sizes and positions, and at varying levels of signal-to-noise ratios. When possible, operating variables for the model were chosen consistently with the field test of an experimental prototype that was conducted in 2014. The defect detection performance was evaluated through the computation of receiver operating characteristic curves in terms of probability of detection versus probability of false alarms. The study indicates that despite the challenges of non-contact probing of the rail, quite satisfactory inspection performance can be expected for a variety of defect types, sizes, and positions. Beyond the specific cases examined in this article, this numerical framework can also be used in the future to examine a larger variety of field test conditions.