The development of new low-cost transducers and systems has been extensively aimed in both industry and academics in order to promote a correct failure diagnosis in several types of aerospace, naval and civil structures. In this context, structural healthy monitoring (SHM) engineering field is focused on promoting human safety and reduction of maintenance costs of these components. Traditionally, SHM aims to detect structural damages at the initial stage, before it reaches a critical level of severity. Numerous approaches for damage identification and location have been proposed in literature. One of the most common damage location technique is based on acoustic waves triangulation, which stands out to be an effective approach. This method uses a piezoelectric transducer as a sensor to capture acoustic waves emitted by a crack or damage. Basically, the damage location is defined by calculating the difference in the time of arrival (TOA) of the signals. Although it may be simple, the detection of TOA require complex statistical and signal processing techniques. Based on this issue, this work proposes the evaluation of a low cost piezoelectric transducer to damage location in metallic structures by comparing two methodologies of TOA identification, the Hinkley Criterion and the Statistical Akaike Criterion. The tests were conducted on an aluminium bar which two piezoelectric transducers were attached at each end. The damage was simulated by mass variation applied in four different spots of the component and the acoustic signals emitted by the damage were acquired and processed by Hinkley and Akaike criterion. The results indicate that, although both signal processing methodologies were able to perform the damage location, Akaike presented higher precision when compared to Hinkley approach. Moreover, the experimental results indicated that the low-cost piezoelectric sensors have a great potential to be applied in the location of damage structures.
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Structural Damage Location by Low-Cost Piezoelectric Transducer and Advanced Signal Processing Techniques
Published: 14 November 2018 by MDPI in 5th International Electronic Conference on Sensors and Applications session Structural Health Monitoring Technologies and Sensor Networks
Keywords: piezoelectric sensors, low-cost sensor, Akaike criterion, Hinkley criterion, signal processing analysis.