A Data-Driven Framework for Early-Stage Fatigue Damage Detection in Aluminum Alloys Using Ultrasonic Sensors

A Data-Driven Framework for Early-Stage Fatigue Damage Detection in Aluminum Alloys Using Ultrasonic Sensors

The paper presents a coupled machine learning and pattern recognition algorithm to enable early-stage fatigue damage detection in aerospace-grade aluminum alloys. U- and V-notched Al7075-T6 specimens are instrumented with a pair of ultrasonic sensors and, thereafter, tested on an MTS apparatus integ...

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Bibliographic Details
Main Authors: Susheel Dharmadhikari, Chandrachur Bhattacharya, Asok Ray, Amrita Basak
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Machines
Subjects:
fatigue crack detection
Al7075-T6
ultrasonic sensors
confocal microscope
pattern recognition
symbolic time series analysis
Online Access:https://www.mdpi.com/2075-1702/9/10/211

Internet

https://www.mdpi.com/2075-1702/9/10/211

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