Visualization of multi-channel sensor data from aero jet engines for condition monitoring and novelty detectionReportar como inadecuado




Visualization of multi-channel sensor data from aero jet engines for condition monitoring and novelty detection - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Reference: Peter R. Bannister, Visualization of multi-channel sensor data from aero jet engines for condition monitoring and novelty detection.Citable link to this page:

 

Visualization of multi-channel sensor data from aero jet engines for condition monitoring and novelty detection

Abstract: The work presented in this paper seeks to determine if it is possible to determine if an aero gas jet engine is behaving normally by learning the expected variation of its Feature Detector (FD) scores and comparing subsequent flight data against a model of the expected scores.We want to be able to characterize the engine by monitoring combinations of FD scores so that it is possible to quickly and intuitively ascertain if an engine is behaving normally according to the previously learned model. This paper demonstrates that it is possible to fuse vibration data from multiple channels into ‘score vectors’ and then determine an optimal mapping that can represent these high-dimensional features in 2-D for visualization.We show that this low-dimensional representation of the score data can adequatelycapture differences between sets of flight data that allow instances of abnormal engine behaviour to be identified. This paper proposes a number of different models, each associated with a sub-set of engine scores that represent the condition of a particular engine shaft in a three-shaft gas aero jet engine and demonstrates the proposed method on data from the intermediate pressure (IP) shaft of an engine.

Publication status:Not PublishedPeer Review status:Not peer reviewedVersion:Author's Original

Bibliographic Details

Copyright Date: 2007-05 Identifiers

Urn: uuid:90783179-00b1-4fab-989c-9ddf82f2b1ab Item Description

Type:

Language: en

Version: Author's OriginalKeywords: sensors multi-channel sensor data jet engines feature detection score engine behaviour feature detectors abnormal engine behaviour engine condition monitoring vibration analysisSubjects: Mechanical engineering Information engineering Tiny URL: ora:1873

Relationships





Autor: Peter R. Bannister - institutionUniversity of Oxford facultyMathematical,Physical and Life Sciences Division facultyMathematical,

Fuente: https://ora.ox.ac.uk/objects/uuid:90783179-00b1-4fab-989c-9ddf82f2b1ab



DESCARGAR PDF




Documentos relacionados