Classification of faults in friction stir processed composites using a machine learning and ensemble learning approach

Classification of faults in friction stir processed composites using a machine learning and ensemble learning approach

Aluminium alloy-based surface composites with hard reinforcement particles have a wide scope in the aerospace and automobile manufacturing industries. In this paper, the aluminium composites, manufactured by friction stir processing (FSP) with varying parameters are investigated for the faults that...

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Bibliographic Details
Main Authors: Pragya Saxena, Arunkumar Bongale
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Materials Research Express
Subjects:
composites
defects
feature selection
sensor data
machine learning classification
Online Access:https://doi.org/10.1088/2053-1591/ad8ca2
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https://doi.org/10.1088/2053-1591/ad8ca2

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