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2014 | OriginalPaper | Buchkapitel

Artificial Immune Systems for Data Classification in Planetary Gearboxes Condition Monitoring

verfasst von : Edyta Brzychczy, Piotr Lipiński, Radoslaw Zimroz, Patryk Filipiak

Erschienen in: Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Verlag: Springer Berlin Heidelberg

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Abstract

In the paper a problem of diagnostic data classification is discussed. The classic condition monitoring approach requires two examples of machines: one in a good and one in a bad condition. From the industrial perspective such a requirement is often very difficult to fulfill, especially in the case of machines with an unique design. To overcome it, we proposed to use the Artificial Immune System (AIS) based approach to classify multidimensional diagnostic data. AIS allows to recognize a change of the machine condition based on a training phase using the dataset related to a good condition. To validate the proposed procedure and assess efficiency of the condition recognition, an extra data set from another machine (of the same type) in a bad condition was used. In the paper several key issues related to the selection of parameters have been discussed.

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Titel: Artificial Immune Systems for Data Classification in Planetary Gearboxes Condition Monitoring
verfasst von: Edyta Brzychczy
Piotr Lipiński
Radoslaw Zimroz
Patryk Filipiak
Verlag: Springer Berlin Heidelberg
Buch: Advances in Condition Monitoring of Machinery in Non-Stationary Operations
Print ISBN: 978-3-642-39347-1

Electronic ISBN: 978-3-642-39348-8

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-642-39348-8_20

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