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Machine Learning Techniques for Automatic Sensor Fault Detection in HUMS Systems
Author(s)
Date Issued
2017-02-28
Date Available
2017-11-01T11:53:57Z
Abstract
In this paper we describe the problem of developing sensor fault detection within HUMS instrumentation systems, and solutions based upon machine-learning techniques. We conclude with a report on our proof-of-concept demonstrator, and outline next-steps towards implementation of a autonomous self diagnostic sensor solution.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Conference Publication
Publisher
Engineers Australia
Language
English
Status of Item
Peer reviewed
Conference Details
17th Australian International Aerospace Congress: AIAC 2017, Melbourne
This item is made available under a Creative Commons License
File(s)
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Name
insight_publication.pdf
Size
429.38 KB
Format
Adobe PDF
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