Exploring the potential of artificial intelligence based flywheels as energy-saving devices in industrial settings
A flywheel with a changeable moment of inertia is known as variable Inertia flywheel (VIF) can be proposed to overcome complexity on moment of inertia that causes difficulty during rotating machine start-up. While there is an extensive amount of literature on VIF control strategies, very little ad...
محفوظ في:
| المؤلفون الرئيسيون: | , , , |
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| التنسيق: | Proceeding Paper |
| اللغة: | English English |
| منشور في: |
AIP publishing
2024
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://irep.iium.edu.my/115368/7/115368_Exploring%20the%20potential.pdf http://irep.iium.edu.my/115368/8/115368_Exploring%20the%20potential_Scopus.pdf http://irep.iium.edu.my/115368/ https://pubs.aip.org/aip/acp/article-abstract/3161/1/020125/3310614/Exploring-the-potential-of-artificial-intelligence?redirectedFrom=fulltext |
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| الملخص: | A flywheel with a changeable moment of inertia is known as variable Inertia flywheel (VIF) can be proposed to
overcome complexity on moment of inertia that causes difficulty during rotating machine start-up. While there is an
extensive amount of literature on VIF control strategies, very little addresses practical considerations. Depending on the
parameters of the application system, a VIF system may be designed and built using a relatively simple control approach.
To determine how a semi-active VIF control system and the input parameters of a rotating electrical machine relate to one another in minimizing energy losses, this study collects data from a VIF linked motor system. The last step in developing an intelligent semi active control for the rotating machine linked with VIF is to utilize a machine learning method to predict the parameters of the control application system. |
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