Prediction of slip in cable-drum systems using structured neural networks

Date

2014-02-01

Author

KILIÇ, Ergin
Dölen, Melik

Metadata

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This study focuses on the slip prediction in a cable-drum system using artificial neural networks for the prospect of developing linear motion sensing scheme for such mechanisms. Both feed-forward and recurrent-type artificial neural network architectures are considered to capture the slip dynamics of cable-drum mechanisms. In the article, the network development is presented in a progressive (step-by-step) fashion for the purpose of not only making the design process transparent to the readers but also highlighting the corresponding challenges associated with the design phase (i.e. selection of architecture, network size, training process parameters, etc.). Prediction performances of the devised networks are evaluated rigorously via an experimental study. Finally, a structured neural network, which embodies the network with the best prediction performance, is further developed to overcome the drift observed at low velocity. The study illustrates that the resulting structured neural network could predict the slip in the mechanism within an error band of 100 mu m when an absolute reference is utilized.

Subject Keywords

Mechanical Engineering

URI

https://hdl.handle.net/11511/43323

Journal

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

DOI

https://doi.org/10.1177/0954406213487471

Collections

Department of Mechanical Engineering, Article

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Citation Formats

E. KILIÇ and M. Dölen, “Prediction of slip in cable-drum systems using structured neural networks,” PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, pp. 441–456, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43323.