Multiple Sensor Fault Diagnosis for Non-Linear and Dynamic System by Evolving Approach Conference Paper

abstract

• Reliability of sensor measurement is vital to assure the performance of complex and nonlinear industrial operation. In this paper, the problem of designing and development of a data-driven multiple sensor fault detection and isolation (MSFDI) algorithm for nonlinear processes is investigated. The proposed scheme is based on an evolving multi-Takagi Sugeno framework in which each sensor output is estimated using a model derived from the available input-output measurement. Our proposed MSFDI algorithm is applied to continuously stirred tank reactor sensor fault detection and isolation. Simulation results demonstrate and validate the performance capabilities of our proposed MSFDI algorithm. 2012 IEEE.

name of conference

• Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing)

authors

• Langari, Gholamreza

published proceedings

• Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing)

author list (cited authors)

• El-Koujok, M., Benammar, M., Meskin, N., Al-Naemi, M., & Langari, R.

citation count

• 2

complete list of authors

• El-Koujok, Mohamed||Benammar, Mohieddine||Meskin, Nader||Al-Naemi, Mohamed||Langari, Reza

publication date

• January 2012

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

Digital Object Identifier (DOI)

• 10.1109/phm.2012.6228969

start page

• 1

end page

• 10

URL

• http://dx.doi.org/10.1109/phm.2012.6228969