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A connectionist model for lock coil rope fault prediction

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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.
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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.

Publication date: October 1, 2008

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