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Quantitative Hardness Measurement by Instrumented AFM-indentation
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Automatic Method for Vickers Hardness Estimation by Image Processing.

Jonatan D Polanco1, Carlos Jacanamejoy-Jamioy1, Claudia L Mambuscay1,2

  • 1Semillero Lún, Grupo D+Tec, Faculty of Engineering, Universidad de Ibagué, Ibagué 730007, Colombia.

Journal of Imaging
|January 20, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an automated image processing method to quickly and accurately measure Vickers hardness, overcoming the limitations of manual testing. The new technique significantly reduces measurement time and human error for material quality assessment.

Keywords:
Vickers hardnesshardness estimationimage processingmechanics of materialssteel heat treating

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Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Image Processing

Background:

  • Vickers hardness testing is crucial for material quality assessment and application suitability.
  • Manual measurement of Vickers hardness from sample images is time-consuming, tedious, and prone to human error.
  • High irregularities in indentation marks can further complicate manual analysis.

Purpose of the Study:

  • To develop and validate an automated image processing method for Vickers hardness testing.
  • To improve the speed and accuracy of hardness measurements.
  • To provide a reliable tool for material characterization, even with irregular indentations.

Main Methods:

  • Development of an automated method using image processing techniques.
  • Implementation as a plugin for the ImageJ software.
  • Validation using microscopy images of AISI D2 steel samples with varying heat treatments and coatings (TiNbN), subjected to 5N and 10N forces.

Main Results:

  • The automated method achieved an average measurement time of 2.05 seconds.
  • The method demonstrated high accuracy, with a 98.3% agreement compared to manual measurements.
  • A maximum error of 4.5% was observed relative to the manually obtained golden standard values.

Conclusions:

  • The proposed automated image processing method offers a significant improvement over manual Vickers hardness testing.
  • This technique provides fast, accurate, and reproducible hardness measurements, enhancing material quality assessment.
  • The ImageJ plugin facilitates widespread adoption for efficient material characterization.