Machine Learning Techniques for Automatic Sensor Fault Detection in HUMS Systems
|Title:||Machine Learning Techniques for Automatic Sensor Fault Detection in HUMS Systems||Authors:||Melia, Thomas
|Permanent link:||http://hdl.handle.net/10197/9023||Date:||28-Feb-2017||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.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||Engineers Australia||Keywords:||Machine Learning & Statistics;Sensors;Self-diagnostics;Machine-learning;Instrumentation;Built-in-test||Language:||en||Status of Item:||Peer reviewed||Conference Details:||17th Australian International Aerospace Congress: AIAC 2017, Melbourne|
|Appears in Collections:||Insight Research Collection|
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