Semantic sensor fusion for fault diagnosis in aircraft gas turbine engines

Soumik Sarkar; Dheeraj Sharan Singh; Abhishek Srivastav; Asok Ray

doi:10.1109/acc.2011.5991168

Semantic sensor fusion for fault diagnosis in aircraft gas turbine engines

Soumik Sarkar, Dheeraj Sharan Singh, Abhishek Srivastav, Asok Ray

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Data-driven fault diagnosis of a complex system such as an aircraft gas turbine engine requires interpretation of multi-sensor information to assure enhanced performance. This paper proposes feature-level sensor information fusion in the framework of symbolic dynamic filtering. This hierarchical approach involves construction of composite patterns consisting of: (i) atomic patterns extracted from single sensor data and (ii) relational patterns that represent the cross-dependencies among different sensor data. The underlying theories are presented along with necessary assumptions and the proposed method is validated on the NASA C-MAPSS simulation model of aircraft gas turbine engines.

Original language	English (US)
Title of host publication	Proceedings of the 2011 American Control Conference, ACC 2011
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	220-225
Number of pages	6
ISBN (Print)	9781457700804
DOIs	https://doi.org/10.1109/acc.2011.5991168
State	Published - 2011

Publication series

Name	Proceedings of the American Control Conference
ISSN (Print)	0743-1619

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

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10.1109/acc.2011.5991168

Cite this

Sarkar, S., Singh, D. S., Srivastav, A., & Ray, A. (2011). Semantic sensor fusion for fault diagnosis in aircraft gas turbine engines. In Proceedings of the 2011 American Control Conference, ACC 2011 (pp. 220-225). Article 5991168 (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/acc.2011.5991168

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Semantic sensor fusion for fault diagnosis in aircraft gas turbine engines. / Sarkar, Soumik; Singh, Dheeraj Sharan; Srivastav, Abhishek et al.
Proceedings of the 2011 American Control Conference, ACC 2011. Institute of Electrical and Electronics Engineers Inc., 2011. p. 220-225 5991168 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Data-driven fault diagnosis of a complex system such as an aircraft gas turbine engine requires interpretation of multi-sensor information to assure enhanced performance. This paper proposes feature-level sensor information fusion in the framework of symbolic dynamic filtering. This hierarchical approach involves construction of composite patterns consisting of: (i) atomic patterns extracted from single sensor data and (ii) relational patterns that represent the cross-dependencies among different sensor data. The underlying theories are presented along with necessary assumptions and the proposed method is validated on the NASA C-MAPSS simulation model of aircraft gas turbine engines.

AB - Data-driven fault diagnosis of a complex system such as an aircraft gas turbine engine requires interpretation of multi-sensor information to assure enhanced performance. This paper proposes feature-level sensor information fusion in the framework of symbolic dynamic filtering. This hierarchical approach involves construction of composite patterns consisting of: (i) atomic patterns extracted from single sensor data and (ii) relational patterns that represent the cross-dependencies among different sensor data. The underlying theories are presented along with necessary assumptions and the proposed method is validated on the NASA C-MAPSS simulation model of aircraft gas turbine engines.

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Semantic sensor fusion for fault diagnosis in aircraft gas turbine engines

Abstract

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