The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability. This paper quantitatively describes a method to compensate the temperature effect, namely the optimal baseline selection (OBS), extending its application to the case of distributed sensor networks (DSN). The effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and frequent value warning is considered. Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combination of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS approach making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions and also demonstrate that the use of compensation strategies improve detectability of damage.


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    Title :

    Temperature Compensation Strategies for Lamb Wave Inspection using Distributed Sensor Networks


    Contributors:


    Publication date :

    2022-06-27


    Size :

    1606809 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English