In this study, the ability of identifying defects in a spot welded structure by using only the natural frequencies is presented. FE model updating has been carried out using SOL200 in NASTRAN for predicting the extent of the defects. The updating procedure is regarded as parameter identification, which aims to bring the numerical prediction to be as close as possible to the measured counterpart. The method has been applied to two identical structures; one (i.e., the benchmark structure) has been produced with smaller manufacturing tolerances to ensure closer physical representation to the nominal design, and another structure has been selected from a set of nine manufactured identical structures. The latter has the biggest variations from the benchmark structure and is classified as defective. The initial FE model for the defective specimen has shown excellent correlation with the experimental findings, mainly because most of the uncertainties (especially for the patch properties) have been successfully identified when updating the benchmark model. Furthermore, the predicted natural frequencies from the updated defective model agree with the measured defective data and the identified defect parameters are found to be reasonable and in agreement with the findings from the visual inspection. The total error of the identified defective model is 1.5%, in comparison to the initial total error of 5.4%. The experimental results of both benchmark and defective structures indicate that the deviations of the defective measured frequencies from the benchmark data are very small, demonstrating the difficulty that frequencies alone often may not be sensitive enough to significantly distinguish damage or defects in a structure. This is a limitation of frequency-based identification approach. To improve accuracy and reliability in damage identification, other modal information should be used. This will be a research topic in the near future.
FE model updating of welded structures for identification of defects
FE-Modellaktualisierung von Schweißkonstruktionen zur Fehleridentifikation
International Journal of Vehicle Noise and Vibration ; 6 , 2-4 ; 163-175
2010
13 Seiten, 6 Bilder, 6 Tabellen, 18 Quellen
Aufsatz (Zeitschrift)
Englisch
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