Abstract

Changes in environmental conditions, and in particular temperature, limit the sensitivity of guided wave structural health monitoring (SHM) systems that use reference signal subtraction. The limitation on sensitivity is the size of the residual signal left after reference signal subtraction that arises from imperfect subtraction of the signals from benign structural features. The sensitivity can be improved by decreasing the spacing between sensors but the effect of temperature is so strong that it is doubtful whether the resulting SHM system is economically viable. This provides the motivation for searching for alternative strategies to improve sensitivity. One possibility is to record an ensemble of reference signals over a range of temperatures and then use the signal in the ensemble that best matches a subsequent signal for subtraction. Experimental results show that this provides an improvement in sensitivity of around 35 dB. It does however require a large database of signals and there is the potential concern that the subtraction of the best match signal may somehow also remove a genuine signal from damage. Another possibility is signal processing to improve sensitivity. A uniform temperature change to a structure results in a change in wave velocity and a dilation of the structure itself. The net effect is a dilation of the arrival times of each wave-packet in a guided wave signal. An obvious strategy to compensate for this effect is to apply the inverse dilation to the time-axis. However, this does not compensate for the effect exactly since the temperature change does not dilate individual wave-packets. An alternative and exact compensation scheme is presented and its practical application is discussed.

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