TY - JOUR
T1 - A more realistic scheme of deviation error representation for gas turbine diagnostics
AU - Loboda, Igor
AU - Yepifanov, Sergiy
AU - Feldshteyn, Yakov
PY - 2013/6
Y1 - 2013/6
N2 - Gas turbine diagnostic algorithms widely use fault simulation schemes, in which measurement errors are usually given by theoretical random number distributions, like the Gaussian probability density function. The scatter of simulated noise is determined on the basis of known information on maximum errors for every sensor type. Such simulation differs from real diagnosis because instead of measurements themselves the diagnostic algorithms work with their deviations from an engine baseline. In addition to simulated measurement inaccuracy, the deviations computed for real data have other error components. In this way, simulated and real deviation errors differ by amplitude and distribution. As a result, simulation-based investigations might result in too optimistic conclusions on gas turbine diagnosis reliability. To understand error features, deviations of real measurements are analyzed in the present paper. To make error presentation more realistic, it is proposed to extract an error component from real deviations and to integrate it in fault description. Finally, the effect of the new noise representation mode on diagnostic reliability is estimated. It is shown that the reliability change due to inexact error simulation can be significant.
AB - Gas turbine diagnostic algorithms widely use fault simulation schemes, in which measurement errors are usually given by theoretical random number distributions, like the Gaussian probability density function. The scatter of simulated noise is determined on the basis of known information on maximum errors for every sensor type. Such simulation differs from real diagnosis because instead of measurements themselves the diagnostic algorithms work with their deviations from an engine baseline. In addition to simulated measurement inaccuracy, the deviations computed for real data have other error components. In this way, simulated and real deviation errors differ by amplitude and distribution. As a result, simulation-based investigations might result in too optimistic conclusions on gas turbine diagnosis reliability. To understand error features, deviations of real measurements are analyzed in the present paper. To make error presentation more realistic, it is proposed to extract an error component from real deviations and to integrate it in fault description. Finally, the effect of the new noise representation mode on diagnostic reliability is estimated. It is shown that the reliability change due to inexact error simulation can be significant.
KW - Diagnostic algorithms
KW - Error features
KW - Gas turbine
KW - Real deviations
UR - http://www.scopus.com/inward/record.url?scp=84888635648&partnerID=8YFLogxK
U2 - 10.1515/tjj-2013-0006
DO - 10.1515/tjj-2013-0006
M3 - Artículo
SN - 0334-0082
VL - 30
SP - 179
EP - 189
JO - International Journal of Turbo and Jet Engines
JF - International Journal of Turbo and Jet Engines
IS - 2
ER -