Exploring the Potential of Artificial Intelligence in the Development of a New AC Resistor Calibration Bridge at the National Metrology Laboratory of Morocco LPEE-LNM
Electrical reactive components, such as resistors, capacitors, and inductors, play a pivotal role in industries like automotive, aerospace, and electronics. Accurate calibration of these components, particularly AC resistors, is critical for ensuring precise measurements and reliable operations in these sectors. The National Metrology Laboratory of Morocco (LPEE-LNM) excels in DC resistance calibration, addressing the needs of the Moroccan industry. However, its current capabilities in AC resistance calibration are insufficient, leading to reliance on international metrology institutes for primary calibrations. This highlights an urgent need for developing advanced AC calibration methods at LPEE-LNM to meet increasing industrial demands.As a review article, this work explores the current state of the art in AC resistance calibration, both in Africa and internationally. It presents the main calibration techniques and practices implemented by national metrology institutes. Beyond this overview, the article outlines a forward-looking perspective on the integration of artificial intelligence in calibration processes in general, highlighting its potential to support automation and enhance accuracy. It also introduces a development perspective for a new AC resistance calibration bridge at the Moroccan National Metrology Laboratory (LPEE-LNM), aiming to position the institute as a continental leader in this domain.
Authors
- Hassan Samri (ORCID: https://orcid.org/0009-0000-4276-0348)
- Abdellah Zamma (ORCID: https://orcid.org/0000-0002-0390-4158)
- Soufiane El Ouardi
- Said Amzil
Institutions
- École Normale Supérieure de l'Enseignement Technique de Mohammedia (MA)
- Université Hassan II Mohammedia (MA)
Publication Details
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1109/iraset64571.2025.11008343
- Citations
- 1
- Primary Topic
- Advanced Electrical Measurement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.73