FPGA-based entropy neural processor for online detection of multiple combined faults on induction motors. Cabal-Yepez, E., Valtierra-Rodriguez, M., Romero-Troncoso, R. J., Garcia-Perez, A., Osornio-Rios, R. A., Miranda-Vidales, H., & Alvarez-Salas, R. Mechanical Systems and Signal Processing, 30:123–130, July, 2012. ![FPGA-based entropy neural processor for online detection of multiple combined faults on induction motors [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex For industry, a faulty induction motor signifies production reduction and cost increase. Real-world induction motors can have one or more faults present at the same time that can mislead to a wrong decision about its operational condition. The detection of multiple combined faults is a demanding task, difficult to accomplish even with computing intensive techniques. This work introduces information entropy and artificial neural networks for detecting multiple combined faults by analyzing the 3-axis startup vibration signals of the rotating machine. A field programmable gate array implementation is developed for automatic online detection of single and combined faults in real time.
@article{cabal-yepez_fpga-based_2012,
title = {{FPGA}-based entropy neural processor for online detection of multiple combined faults on induction motors},
volume = {30},
issn = {0888-3270},
url = {https://www.sciencedirect.com/science/article/pii/S0888327012000222},
doi = {10.1016/j.ymssp.2012.01.021},
abstract = {For industry, a faulty induction motor signifies production reduction and cost increase. Real-world induction motors can have one or more faults present at the same time that can mislead to a wrong decision about its operational condition. The detection of multiple combined faults is a demanding task, difficult to accomplish even with computing intensive techniques. This work introduces information entropy and artificial neural networks for detecting multiple combined faults by analyzing the 3-axis startup vibration signals of the rotating machine. A field programmable gate array implementation is developed for automatic online detection of single and combined faults in real time.},
language = {en},
urldate = {2021-09-30},
journal = {Mechanical Systems and Signal Processing},
author = {Cabal-Yepez, E. and Valtierra-Rodriguez, M. and Romero-Troncoso, R. J. and Garcia-Perez, A. and Osornio-Rios, R. A. and Miranda-Vidales, H. and Alvarez-Salas, R.},
month = jul,
year = {2012},
keywords = {3-axis vibration signals, Artificial neural networks, Field programmable gate array, Induction motors, Information entropy, Multiple combined faults},
pages = {123--130},
}
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