Machine Vision-Based Automatic Detection for Electromechanical Equipment

Shijie Lyu

doi:10.5281/zenodo.13830975

OPEN ACCESS |Research Article ||2 November 2024

Machine Vision-Based Automatic Detection for Electromechanical Equipment

Shijie Lyu

Georgia Institute of Technology

slyu41@gatech.edu

Georgia Institute of Technology, USA.

* Corresponding Author¹: Shijie Lyu, E-Mail: slyu41@gatech.edu

Publication

Accepted Unknow ; Published 2024 November 2

Journal of Computer Technology and Applied Mathematics, 2024, 1(4), 3007-4126.

Abstract

With the continuous development of industrial production, efficient and accurate inspection of mechanical equipment has become crucial for production safety, efficiency, and economic benefits. By collecting and analyzing imaging data from electromechanical equipment, effective online monitoring and fault diagnosis can be achieved, enhancing operational efficiency and accuracy while reducing manual intervention. This is a significant research direction in the field of industrial automation control. This paper begins with the fundamental principles of electromechanical equipment testing, conducting an in-depth study of its working mechanisms and providing a detailed discussion on its design and development. The main content includes the system architecture design, functional module design, and key algorithm design, laying a solid foundation for the research on automated testing of electromechanical equipment.

Keywords

Automatic Detection Technology , Machine Vision , Electromechanical Equipment , Economic Benefits .

Metadata

DOI:

10.5281/zenodo.13830975

ARK:

ark:/40704/JCTAM.v1n4a02

Pages: 12-20

References: 36

Disciplines: Computer Science

Subjects: Machine Vision

Cite This Article

APA Style

Lyu, S. (2024). Machine vision-based automatic detection for electromechanical equipment. Journal of Computer Technology and Applied Mathematics, 1(4), 12-20. https://doi.org/10.5281/zenodo.13830975

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

FUNDING

Not applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not applicable.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

INFORMED CONSENT STATEMENT

Not applicable.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHOR CONTRIBUTIONS

Not applicable.

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