Non-parametric Inference Applied to Damage Detection in the Electromechanical Impedance-based Health Monitoring

Abstract

The electromechanical impedance-based structural health monitoring is a non-traditional vibration technique that compares a pristine signature to a damaged one. However, in order to compare a complete frequency response function to another, it is necessary to create a virtual index called damage metric, which indicates how far the investigated structure states from the initial condition. The most used index is the RMSD (Root Mean Square Deviation) to have a quantitative measurement of the monitored structures but CCD (Correlation Coefficient Deviation) is more robust to temperature changes. Thus, this contribution focuses on thisCCD damage metric for simulated damages (mass addition) of Al beams in a 2x5 factorial design. The first factor considered was the pristine or damage condition. The second factor was the environmental temperature of the specimen, during the signature gathering, for five levels: -10 oC, 0 oC, 10 oC, 20 oC and 30 oC. According to the references, temperature is a very important aspect to be considered because some changes in the signature can be promoted, and for this purpose a temperature chamber was used in the study. Several statistical evaluations were performed and this contribution illustrates the median of the damage metrics are greater than the baseline ones. Also, although the temperature level creates shifts of the damage metrics, this not caused false positives, enabling the technique to differentiate the damage to the pristine conditions.