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Title:
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SENSOR BASED CONDITION MONITORING USING A SELF-ORGANIZING SPIKING NEURAL NETWORKS MAP |
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Author(s):
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Rui G. Silva |
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ISBN:
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978-972-8924-56-0 |
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Editors:
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Nuno Guimarães and Pedro Isaías |
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Year:
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2008 |
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Edition:
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Single |
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Keywords:
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Spiking Neuron Networks; Unsupervised Learning; Condition Monitoring; Tool Wear |
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Type:
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Full Paper |
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First Page:
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195 |
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Last Page:
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202 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper presents a new approach to sensor based condition monitoring using a self-organizing spiking neuron network
map. Experimental evidence suggests that biological neural networks, which communicate through spikes, use the timing
of these spikes to encode and compute information in a more efficient way. The paper introduces the basis of a simplified
version of the Self-Organizing neural architecture based on Spiking Neurons. The fundamental steps for the development
of this computational model are presented as well as some experimental evidence of its performance. It is shown that this
computational architecture has a greater potential to unveil embedded information in tool wear monitoring data sets and
that faster learning occurs if compared to traditional sigmoidal neural networks. |
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