Swing Door Simulator
Casaril, Maud
Promotor(s) :
Sacré, Pierre
Date of defense : 30-Jun-2025/1-Jul-2025 • Permalink : http://hdl.handle.net/2268.2/23234
Details
| Title : | Swing Door Simulator |
| Author : | Casaril, Maud
|
| Date of defense : | 30-Jun-2025/1-Jul-2025 |
| Advisor(s) : | Sacré, Pierre
|
| Committee's member(s) : | Boigelot, Bernard
Zambon, Alain De Groef, Thibault |
| Language : | English |
| Number of pages : | 89 |
| Keywords : | [en] swing door [en] simulator [en] automation [en] MVC |
| Discipline(s) : | Engineering, computing & technology > Electrical & electronics engineering |
| Target public : | Other |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master : ingénieur civil électricien, à finalité spécialisée en Neuromorphic Engineering |
| Faculty: | Master thesis of the Faculté des Sciences appliquées |
Abstract
[fr] Currently, no automated testing tool for sensors deployed on swing doors has been developed within BEA Sensors. All tests are performed manually by members of the R&D team, resulting in a long process. Consequently, this extends the development process for new sensors and delays the validation of hardware or software upgrades to existing products. This thesis addresses these challenges by developing a user-friendly testing interface designed to automate and standardize the sensor validation process on swing doors.
The developed tool enables the recording of movement data by extracting sensor readings in real-world conditions. The recorded data can then be edited to highlight specific characteristics of the motion. Afterwards, these recordings can be replayed on a servo-driven test door. Finally, each replay can be analyzed in detail to evaluate the performance of the tested sensor. The tool records data in a standardized format and saves it in a dedicated directory to create a comprehensive library of challenging test cases for swing doors. This provides a valuable resource for future sensor validation and development.
This thesis explores the development process of the tool, explaining in detail the code architecture chosen to ensure maintainability, robustness, and a clear hierarchy of responsibilities. It also explains how the Festo servo motor is controlled via the CANopen protocol, as well as the methods used to extract data from the BEA Sensors.
The tool is already operational and has demonstrated its ability to faithfully reproduce complex motion profiles and extract performance metrics from the replays. While certain limitations remain, such as the limited accuracy of the sensor and the significant system inertia, this testing platform provides a robust foundation for future automation and more advanced sensor validation.
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thesis_maud_casaril.pdf
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summary_thesis_maud_casaril.pdf
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