Health risk assessment and prognosis of gas turbine blades by simulation and statistical methods

Author

Goel, N. ; Kumar, A. ; Narasimhan, V. ; Nayak, A. ; Srivastava, A.

Author_Institution

Tecsis Corp., Ottawa, ON

fYear

2008

fDate

4-7 May 2008

Abstract

Algorithmic approaches for failure risk assessment, anomaly detection and life prognosis of gas turbine blade are discussed. Modeling of blade tip clearance and Monte Carlo simulation considering creep, vibration and other damaging effects lead to two probabilistic distributions with blade tip clearance data. Failure risk can be determined during blade life usage based on blade tip tolerance limits. Statistical treatments considering percentile ranking of sample mean and regression analysis of blade tip clearance data for anomaly detection and usage life analysis respectively are also discussed.

Keywords

Monte Carlo methods; blades; creep; failure (mechanical); gas turbines; regression analysis; remaining life assessment; risk management; vibrations; Monte Carlo simulation; anomaly detection; blade tip clearance; blade tip tolerance limits; creep; failure risk assessment; gas turbine blades; health risk assessment; life prognosis; regression analysis; sample mean; statistical methods; vibration; Blades; Creep; Engines; Maintenance; Oxidation; Risk management; Statistical analysis; Temperature; Thermal stresses; Turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on

Conference_Location

Niagara Falls, ON

ISSN

0840-7789

Print_ISBN

978-1-4244-1642-4

Electronic_ISBN

0840-7789

Type

conf

DOI

10.1109/CCECE.2008.4564705

Filename

4564705