Measuring Hardness System Based on Image Processing

In this work, we developed a system to determine the hardness of a metallic material. The method provides the Brinell hardness value through image analysis, a microscope, and mechatronic elements. The system consists of a microscope with an attached camera where the amplification factor is fixed. The system modifies the height of the microscope to focus the tested object through the movement of a stepper motor, the motor is stopped when the edge detection of the image is maximum. The Arduino platform controls the stepper motor, and Matlab was employed to develop the image processing algorithm, these two stages are synchronized by the USB communication. Once the microscope is correctly focused, an image of the indentation is captured by the camera and analyzed using the Hough transform for circle detection. Finally, the hardness value is obtained using the diameter detected, finding a standard deviation error of 1.44 micrometers in the impression measurement and a considerable time reduction in the measurement process.

Authors

Publication Details

Published
2024-10-23
DOI
https://doi.org/10.1109/cce62852.2024.10771036
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.35

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article

Measuring Hardness System Based on Image Processing

Jesús Puente, José Manuel Rivera Garnica, César Augusto García Isáis
1 citations
Industrial Vision Systems and Defect Detection
0.35
article

Measuring Hardness System Based on Image Processing

Jesús Puente, José Manuel Rivera Garnica, César Augusto García Isáis
article en
1 citations

Abstract

In this work, we developed a system to determine the hardness of a metallic material. The method provides the Brinell hardness value through image analysis, a microscope, and mechatronic elements. The system consists of a microscope with an attached camera where the amplification factor is fixed. The system modifies the height of the microscope to focus the tested object through the movement of a stepper motor, the motor is stopped when the edge detection of the image is maximum. The Arduino platform controls the stepper motor, and Matlab was employed to develop the image processing algorithm, these two stages are synchronized by the USB communication. Once the microscope is correctly focused, an image of the indentation is captured by the camera and analyzed using the Hough transform for circle detection. Finally, the hardness value is obtained using the diameter detected, finding a standard deviation error of 1.44 micrometers in the impression measurement and a considerable time reduction in the measurement process.

Instituto Politécnico Nacional
Openalex Percentile: Top 32%
Industrial Vision Systems and Defect Detection
0.35
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