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Springer Nature
Lecture Notes in Computer Science
,  pages 179-193

A Fault Diagnostic Tool Based on a First Principle Model Simulator

Publication type: Book Chapter
Publication date: 2017-08-01
Springer Nature
scimago Q2
SJR: 0.352
CiteScore: 2.4
Impact factor: —
ISSN: 03029743, 16113349, 18612075, 18612083
Abstract
We develop a First Principle Model (FPM) simulator of a solenoid micro-valve of the control system of a train braking system. This is used for failure diagnostic when field data of normal and abnormal system behaviors are lacking. A procedure is proposed to adjust the diagnostic model once field data are available.
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GOST Copy
Cannarile F. et al. A Fault Diagnostic Tool Based on a First Principle Model Simulator // Lecture Notes in Computer Science. 2017. pp. 179-193.
GOST all authors (up to 50) Copy
Cannarile F., Compare M., Zio E. A Fault Diagnostic Tool Based on a First Principle Model Simulator // Lecture Notes in Computer Science. 2017. pp. 179-193.
RIS |
Cite this
RIS Copy
TY - GENERIC
DO - 10.1007/978-3-319-64119-5_12
UR - https://doi.org/10.1007/978-3-319-64119-5_12
TI - A Fault Diagnostic Tool Based on a First Principle Model Simulator
T2 - Lecture Notes in Computer Science
AU - Cannarile, Francesco
AU - Compare, Michele
AU - Zio, Enrico
PY - 2017
DA - 2017/08/01
PB - Springer Nature
SP - 179-193
SN - 0302-9743
SN - 1611-3349
SN - 1861-2075
SN - 1861-2083
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@incollection{2017_Cannarile,
author = {Francesco Cannarile and Michele Compare and Enrico Zio},
title = {A Fault Diagnostic Tool Based on a First Principle Model Simulator},
publisher = {Springer Nature},
year = {2017},
pages = {179--193},
month = {aug}
}