Deep Learning for Induction Motor Drives
Yuki Ivanov
Nanyang Technological University
Omar Tran
Middle East Technical University
Abstract
Accurate prediction of induction motor drives can substantially reduce the lifecycle cost of telecommunication infrastructure. Scenarios reflecting typical conditions in telecommunication infrastructure are constructed and evaluated in turn. Applying the method to 4 real-world sites yielded consistent and reproducible results. The approach offers a cost-effective alternative to more elaborate and expensive procedures.
Keywords:
induction motor drivesdeep learningimage segmentationmachine learning
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