Document Type

Journal Article

Publication Title

Sensors

Volume

21

Issue

13

PubMed ID

34203468

Publisher

MDPI

School

School of Engineering

RAS ID

36052

Comments

Akkoyun, F., Ercetin, A., Aslantas, K., Pimenov, D. Y., Giasin, K., Lakshmikanthan, A., & Aamir, M. (2021). Measurement of micro burr and slot widths through image processing: Comparison of manual and automated measurements in micro‐milling. Sensors, 21(13), article 4432. https://doi.org/10.3390/s21134432

Abstract

In this study, the burr and slot widths formed after the micro‐milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user‐defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open‐sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user‐friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation.

DOI

10.3390/s21134432

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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Engineering Commons

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