IMPEDANCE-BASED STRUCTURAL HEALTH MONITORING AND KOHONEN NETS FOR DAMAGE DETECTION

Autor:	Alexsander Lindolfo de Lima, Stanley Washington F. Rezende, Quintiliano S. S. Nomelini, Jose Waldemar Silva, Roberto M. Finzi Neto, Carlos A. Gallo, Jose dos Reis V. Moura Jr
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	Structural health monitoring Self-organizing maps Artificial neural networks
DOI:	10.5281/zenodo.8019381
Popis:	Several expensive structures have been developed in the past century. Thus, corrective, preventive, and predictive maintenance techniques were proposed based on the ability to investigate a monitoring parameter up to the inflection point of the component's useful life. Consequently, several structural health assessment methodologies have been implemented using smart sensors. In general, damage classification models in this kind of monitoring have a limitation due to the influence of temperature on piezoelectric sensors, requiring a temperature compensation step (normalization). In this work, a Kohonen map is used with a Principal Component Analysis to demonstrate the potential of this kind of model in eliminating the compensation step and classifying the damage correctly. For the case study, an aluminum beam instrumented with a PZT (Pb-lead Zirconate Titanate) patch was used and subjected to different temperatures in a climatic chamber in 11 levels of temperature. The test structure had thickness removals with seven levels at the opposite end of the beam with the sensor. Several parameters of the models were changed and demonstrated the availability to use the proposed methodology as an approach to the temperature-independent damage model. In conclusion, this type of result enables the use of this model in real structural monitoring. Impedance-based Structural Health Monitoring and Kohonen Nets for Damage Detection Alexsander Lindolfo de Lima, Stanley Washington F. Rezende, Quintiliano S. S. Nomelini, Jose Waldemar Silva, Roberto M. Finzi Neto, Carlos A. Gallo and Jose dos Reis V. Moura Jr, Published in International Journal of Advances in Engineering & Technology (IJAET), Volume 16 Issue 2, pp. 20-34, April 2023. {"references":["O. ABDELJABER & O. AVCI, Nonparametric structural damage detection algorithm for ambient vibration response: utilizing artificial neural networks and self-organizing maps. 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Databáze:	OpenAIRE
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