Image processing algorithm for detection, quantification and classification of microdefects in wire electric discharge machined precision finish cut surfaces
P. M., Abhilash and Chakradhar, Dupadu (2021) Image processing algorithm for detection, quantification and classification of microdefects in wire electric discharge machined precision finish cut surfaces. Journal of Micromanufacturing. ISSN 2516-5992 (https://doi.org/10.1177/25165984211015410)
Preview |
Text.
Filename: Puthanveettil_Madathil_Chakradhar_JIM_2021_Image_processing_algorithm_for_detection.pdf
Accepted Author Manuscript License: Strathprints license 1.0 Download (2MB)| Preview |
Abstract
This study aims to create an image processing algorithm that categorises the wire electric discharge machine (WEDM) processed finish cut surfaces, based on surface microdefects. The algorithm also detects the defect locations and suggests alternate parameter settings for improving the surface integrity. The proposed automated analysis is more precise, efficient and repeatable compared to manual inspection. Also, the method can be used for automatic data generation to suggest parameter changes in closed loop systems. During the training phase, mean, standard deviation and defect area fraction of enhanced binary images are extracted and stored. The training dataset consists of 27 WEDM finish cut surface images with labels, 'coarse', 'average' and 'smooth'. The trained model is capable of categorising any machined surface by detecting the microdefects. If the machined surface image is not classified as a smooth image, then alternate input parameter settings will be suggested by the model to minimise the microdefects. This is done based on the Euclidean distance between the current image datapoint and the nearest 'smooth' class datapoint.
ORCID iDs
P. M., Abhilash ORCID: https://orcid.org/0000-0001-5655-6196 and Chakradhar, Dupadu;-
-
Item type: Article ID code: 80694 Dates: DateEvent2 June 2021Published2 June 2021Published Online25 February 2021AcceptedSubjects: Technology > Manufactures Department: Faculty of Engineering > Design, Manufacture and Engineering Management Depositing user: Pure Administrator Date deposited: 12 May 2022 15:12 Last modified: 09 Oct 2024 00:36 URI: https://strathprints.strath.ac.uk/id/eprint/80694