Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis
In this study, free high-level programming languages, GNU Octave and Python, are used to model the mechanical part simulating the periodic signal generated in the mechanical system and to link with the signal processing unit that analyzes the generated signal, providing an integrated educational too...
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EDP Sciences
2025-01-01
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| Series: | Mechanics & Industry |
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| Online Access: | https://www.mechanics-industry.org/articles/meca/full_html/2025/01/mi240010/mi240010.html |
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| author | Park Yonghu |
| author_facet | Park Yonghu |
| author_sort | Park Yonghu |
| collection | DOAJ |
| description | In this study, free high-level programming languages, GNU Octave and Python, are used to model the mechanical part simulating the periodic signal generated in the mechanical system and to link with the signal processing unit that analyzes the generated signal, providing an integrated educational tool capable of recognizing faults in the mechanical system. A design system was developed using GNU Octave to acquire the dynamic characteristics of a closed system in real time, inputting them into the signal processing unit. This is achieved by utilizing the Lagrangian multiplier method to process constraint equations and calculating solutions for differential-algebraic equations using the Runge-Kutta method. Subsequently, a predictive model that simulates real-time cycle data was established, and a design scenario was proposed to assess the stability of the mechanical system by continuously updating and comparing its dynamic characteristic data. In particular, the system structure, where the mechanical part (GNU Octave) and the signal processing part (Python) share data in the form of a .txt file, is designed to improve data processing speed. Additionally, the prediction model, Prophet (developed by Facebook), is incorporated to aid in the development of mechanical products from a hardware perspective, such as simple strength and dynamic characteristics analysis. This is achieved by establishing a user-defined periodic model for unique periodic signals, efficiently processing accumulated data, reviewing reliability based on the difference between the prediction model and actual data, and proposing abnormality detection methods. The system aims to enhance the programming capabilities of mechanical engineering students and industrial personnel by providing hands-on experience with the element technologies used in developing automation systems compatible with electronic equipment and programs. |
| format | Article |
| id | doaj-art-710c2e2f8fea4d6aaf9756451a7b1b16 |
| institution | DOAJ |
| issn | 2257-7777 2257-7750 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Mechanics & Industry |
| spelling | doaj-art-710c2e2f8fea4d6aaf9756451a7b1b162025-08-20T03:06:30ZengEDP SciencesMechanics & Industry2257-77772257-77502025-01-01261610.1051/meca/2024035mi240010Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysisPark Yonghu0Department of Mechanical Engineering, Sunmoon UniversityIn this study, free high-level programming languages, GNU Octave and Python, are used to model the mechanical part simulating the periodic signal generated in the mechanical system and to link with the signal processing unit that analyzes the generated signal, providing an integrated educational tool capable of recognizing faults in the mechanical system. A design system was developed using GNU Octave to acquire the dynamic characteristics of a closed system in real time, inputting them into the signal processing unit. This is achieved by utilizing the Lagrangian multiplier method to process constraint equations and calculating solutions for differential-algebraic equations using the Runge-Kutta method. Subsequently, a predictive model that simulates real-time cycle data was established, and a design scenario was proposed to assess the stability of the mechanical system by continuously updating and comparing its dynamic characteristic data. In particular, the system structure, where the mechanical part (GNU Octave) and the signal processing part (Python) share data in the form of a .txt file, is designed to improve data processing speed. Additionally, the prediction model, Prophet (developed by Facebook), is incorporated to aid in the development of mechanical products from a hardware perspective, such as simple strength and dynamic characteristics analysis. This is achieved by establishing a user-defined periodic model for unique periodic signals, efficiently processing accumulated data, reviewing reliability based on the difference between the prediction model and actual data, and proposing abnormality detection methods. The system aims to enhance the programming capabilities of mechanical engineering students and industrial personnel by providing hands-on experience with the element technologies used in developing automation systems compatible with electronic equipment and programs.https://www.mechanics-industry.org/articles/meca/full_html/2025/01/mi240010/mi240010.htmlintegrated design systemmulti-body dynamicsdifferential-algebraic equationrunge-kutta methodsignal processtime series analysis |
| spellingShingle | Park Yonghu Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis Mechanics & Industry integrated design system multi-body dynamics differential-algebraic equation runge-kutta method signal process time series analysis |
| title | Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis |
| title_full | Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis |
| title_fullStr | Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis |
| title_full_unstemmed | Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis |
| title_short | Development of an integrated engineering education model using multi-body closed system modeling, computational analysis, and signal processing analysis |
| title_sort | development of an integrated engineering education model using multi body closed system modeling computational analysis and signal processing analysis |
| topic | integrated design system multi-body dynamics differential-algebraic equation runge-kutta method signal process time series analysis |
| url | https://www.mechanics-industry.org/articles/meca/full_html/2025/01/mi240010/mi240010.html |
| work_keys_str_mv | AT parkyonghu developmentofanintegratedengineeringeducationmodelusingmultibodyclosedsystemmodelingcomputationalanalysisandsignalprocessinganalysis |