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Erschienen in:
Probabilistic Prognostics and Health Management: A Brief Summary Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Monitoring and Fault Identification in Aeronautical Structures Using an Wavelet-Artificial Immune System Algorithm

verfasst von : Fernando P. A. Lima, Fábio R. Chavarette, Simone S. F. Souza, Mara L. M. Lopes

Erschienen in: Probabilistic Prognostics and Health Management of Energy Systems

Verlag: Springer International Publishing

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Abstract

This chapter presents a Wavelet-Artificial Immune System (WAIS) algorithm to diagnose failures in aeronautical structures. Basically, after obtaining the vibration signals in the structure, the wavelet module is used to transform the signals into the wavelet domain. Afterward, a negative selection artificial immune system performs the diagnosis via identifying and classifying the failures. The main application of this methodology is in the auxiliary structures inspection process in order to identify and characterize the flaws as well as assist in the decision making process that is aiming at avoiding accidents or disasters. In order to evaluate this methodology, we carried out the modeling and simulation of signals from a numerical model of an aluminum beam that represent an aircraft structure such as a wing. The proposed algorithm presented good results, with 100% matching in detecting and classifying of the failures tested. The results demonstrate the robustness and accuracy of the methodology.

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Vorheriges Kapitel The Derivative as a Probabilistic Synthesis of Past and Future Data and Remaining Useful Life Prediction
Nächstes Kapitel An Illustration of Some Methods to Detect Faults in Geared Systems Using a Simple Model of Two Meshed Gears
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Metadaten
Titel
Monitoring and Fault Identification in Aeronautical Structures Using an Wavelet-Artificial Immune System Algorithm
verfasst von
Fernando P. A. Lima
Fábio R. Chavarette
Simone S. F. Souza
Mara L. M. Lopes
Copyright-Jahr
2017
Buch
Probabilistic Prognostics and Health Management of Energy Systems

Print ISBN: 978-3-319-55851-6

Electronic ISBN: 978-3-319-55852-3

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-55852-3_13