Search results for " Fatigue Crack."
showing 4 items of 4 documents
Outlier analysis and principal component analysis to detect fatigue cracks in waveguides
2009
Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), outlier analysis and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defectsensitive features to perform a multivariate diagnosis of damage. The framework presented in this paper is applied to the de…
Proof of concept of wayside railroad wheel inspection using a laser-air hybrid ultrasonic technique
2003
Non-destructive inspection of railroad wheels is performed in maintenance shops, where wheels are removed and inspected individually. No technique is yet available to the railroad industry to perform wayside inspections of wheels on a moving train. The characteristics of laser and air-coupled ultrasound are discussed to justify the use of a laser-air hybrid ultrasonic technique. Laser generation of ultrasound is combined with air-coupled detection to provide a flexible non-contact and remote technique that would enable the railroad industry to perform wayside inspections of moving railroad wheels. The present paper describes Proof of Concept set-up and results of the experiments performed a…
Performance improvements of asphalt mixtures by dry addition of polymeric additives
2017
This paper shows the results of an experimental study concerning the development and optimization of asphalt mixtures for binder and base courses, improved with specifically engineered additives. The focus was on the mechanical improvements of the mixtures as achievable via dry modification with polymeric additives by making use of aggregate and bitumen of average quality, as locally available, in order to limit the consumption of virgin materials. The results allowed interesting conclusions to be drawn about the use of polymeric additives for these mixtures. In particular, the modified mixtures proved to have better performance in terms of both permanent deformation resistance and stiffnes…
Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys
2022
Fatigue cracks are a major defect in metal alloys, and specifically, their study poses defect evaluation challenges in aluminum aircraft alloys. Existing inline inspection tools exhibit measurement uncertainties. The physical-based methods for crack growth prediction utilize stress analysis models and the crack growth model governed by Paris’ law. These models, when utilized for long-term crack growth prediction, yield sub-optimum solutions and pose several technical limitations to the prediction problems. The metaheuristic optimization algorithms in this study have been conducted in accordance with neural networks to accurately forecast the crack growth rates in aluminum alloys. Through ex…