Abstract
This paper addresses the issues of data analysis and sensor fusion that are critical for information management leading to (real-time) fault detection and classification in distributed physical processes (e.g., shipboard auxiliary systems). The proposed technique utilizes a semantic framework for multi-sensor data modeling, where the complexity is reduced by pruning the sensor network through an information-theoretic (e.g., mutual information-based) approach. The underlying algorithms are developed to achieve high reliability and computational efficiency while retaining the essential spatiotemporal characteristics of the physical system. The concept is validated on a simulation test bed of shipboard auxiliary systems.
| Original language | English (US) |
|---|---|
| Title of host publication | 2013 American Control Conference, ACC 2013 |
| Pages | 3846-3851 |
| Number of pages | 6 |
| State | Published - Sep 11 2013 |
| Event | 2013 1st American Control Conference, ACC 2013 - Washington, DC, United States Duration: Jun 17 2013 → Jun 19 2013 |
Publication series
| Name | Proceedings of the American Control Conference |
|---|---|
| ISSN (Print) | 0743-1619 |
Other
| Other | 2013 1st American Control Conference, ACC 2013 |
|---|---|
| Country | United States |
| City | Washington, DC |
| Period | 6/17/13 → 6/19/13 |
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
Cite this
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Spatiotemporal information fusion for fault detection in shipboard auxiliary systems. / Sarkar, Soumalya; Virani, Nurali; Yasar, Murat; Ray, Asok; Sarkar, Soumik.
2013 American Control Conference, ACC 2013. 2013. p. 3846-3851 6580426 (Proceedings of the American Control Conference).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Spatiotemporal information fusion for fault detection in shipboard auxiliary systems
AU - Sarkar, Soumalya
AU - Virani, Nurali
AU - Yasar, Murat
AU - Ray, Asok
AU - Sarkar, Soumik
PY - 2013/9/11
Y1 - 2013/9/11
N2 - This paper addresses the issues of data analysis and sensor fusion that are critical for information management leading to (real-time) fault detection and classification in distributed physical processes (e.g., shipboard auxiliary systems). The proposed technique utilizes a semantic framework for multi-sensor data modeling, where the complexity is reduced by pruning the sensor network through an information-theoretic (e.g., mutual information-based) approach. The underlying algorithms are developed to achieve high reliability and computational efficiency while retaining the essential spatiotemporal characteristics of the physical system. The concept is validated on a simulation test bed of shipboard auxiliary systems.
AB - This paper addresses the issues of data analysis and sensor fusion that are critical for information management leading to (real-time) fault detection and classification in distributed physical processes (e.g., shipboard auxiliary systems). The proposed technique utilizes a semantic framework for multi-sensor data modeling, where the complexity is reduced by pruning the sensor network through an information-theoretic (e.g., mutual information-based) approach. The underlying algorithms are developed to achieve high reliability and computational efficiency while retaining the essential spatiotemporal characteristics of the physical system. The concept is validated on a simulation test bed of shipboard auxiliary systems.
UR - http://www.scopus.com/inward/record.url?scp=84883545776&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883545776&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84883545776
SN - 9781479901777
T3 - Proceedings of the American Control Conference
SP - 3846
EP - 3851
BT - 2013 American Control Conference, ACC 2013
ER -