Realtime diagnostic prognostic solution for life cycle management of thermomechanical system

Author

Saxena, Bhavaye ; Kumar, Ajit ; Srivastava, Anurag ; Goe, Alok

Author_Institution

Univ. of Ottawa, Ottawa, ON, Canada

fYear

2011

fDate

8-11 May 2011

Abstract

Data based approach and methodology for real time diagnosis and prognosis solutions for thermomechanical systems is discussed. Coated turbine blade operation is emulated to sensor online temperature data as the real-time inputs for the software code developed. An algorithm is presented first and extended sampling based statistical hypothesis tests are used for anomaly detection tests. Paired t-test and rank sum hypotheses test are found to be appropriate for different data set combinations. Matlab statistical package is used for the software code. The algorithm and methodology work well with laboratory temperature data and seeded faults. Few limitations of the developed system code are identified.

Keywords

blades; condition monitoring; fault diagnosis; mathematics computing; mechanical engineering computing; product life cycle management; sampling methods; software engineering; turbines; Matlab statistical package; anomaly detection tests; databases; rank sum hypotheses test; realtime diagnostic prognostic solution; sampling; sensor online temperature data; software code development; statistical hypothesis tests; t-test hypotheses; thermomechanical system life cycle management; turbine blade operation; Algorithm design and analysis; Engines; Real time systems; Temperature distribution; Temperature measurement; Temperature sensors; Turbines; Temperature; anomaly; diagnosis; prognosis; reference; t-test;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference on

Conference_Location

Niagara Falls, ON

ISSN

0840-7789

Print_ISBN

978-1-4244-9788-1

Electronic_ISBN

0840-7789

Type

conf

DOI

10.1109/CCECE.2011.6030610

Filename

6030610