... Figure cyberphysical system structural health monitoring guided wave smart sensing signal processing composite structure machine learning aerospace engineering automotive engineering continuous and periodic condition assessment damage classification diagnostic feature extraction...

... are limited to the detection of through-the-flange-width debonding (i.e., full debonding). This paper attempts to develop a methodology for the detection and assessment of early-stage debonding (i.e., partial debonding) in the stiffened panel using machine learning (ML) algorithms. An experimentally validated...

...Jethro Nagawkar; Leifur Leifsson The objective of this work is to reduce the cost of performing model-based sensitivity analysis for ultrasonic nondestructive testing systems by replacing the accurate physics-based model with machine learning (ML) algorithms and quickly compute Sobol’ indices...

... the fatigue test of a specimen is required to assess the accuracy of the test and for downstream activities such as for stress–strain based material model developments and stress analysis validation. In this paper, we discuss an artificial intelligence and machine learning framework for predicting time-series...

... 2020 25 11 2020 25 11 2020 19 01 2021 bearings vibration fault diagnosis envelope analysis sensor k-nearest neighbor (kNN) machine learning Bearing fault diagnostics has attracted intensive research interest as the bearings are crucial elements of rotary machinery...