Skip to main content
padlock icon - secure page this page is secure

A connectionist model for lock coil rope fault prediction

Buy Article:

$22.00 + tax (Refund Policy)

In this paper, a neural network-based method of wire rope fault prediction in a system is proposed. This method is developed based on past observations on various wire rope parameters for lock coil rope, for example number of rope used in the system, period of test, number of faults, etc. To capture the data from various systems, with a view to improving the prediction accuracy, we have designed a multi-layer perceptron network (MLP) to realise better performance.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Wire rope; back propagation; multi-layer perceptron; neural networks

Document Type: Research Article

Affiliations: 1 Electrical Laboratory, Central Institute of Mining and Fuel Research, Barwa Road, Dhanbad 826001, India. deba65yahoo.com.

Publication date: October 1, 2008

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more