Title :
Subspace-based fault detection - Multiplicative and additive fault
Author_Institution :
Saginaw Valley State Univ., Saginaw, MI, USA
Abstract :
In this research, a technique is developed to separate an additive fault from a multiplicative fault of a system which is disturbed by integrated white noise. First, Predictor-based System Identification (PBSID) is formulated in a differenced form (DPBSID) in order to filter out the integrated white noise. Second, the differenced PBSID is reformulated in a recursive form (DRPBSID) which is for separating an additive fault from a multiplicative fault. If the fault type is multiplicative, the Frobenius norm of the difference between the identified system matrix and a changed one becomes greater than a threshold. By recursively updating the system matrix, the difference goes below the threshold hence, a multiplicative fault is separated from an additive one. This technique is applied to a complex system and its effectiveness is demonstrated using Matlab simulation.
Keywords :
fault diagnosis; identification; matrix algebra; white noise; DPBSID; DRPBSID; Matlab simulation; additive fault; complex system; differenced form; integrated white noise; multiplicative fault; predictor-based system identification; recursive form; subspace-based fault detection; system matrix; Atmospheric modeling; Biographies; Biological system modeling; Mathematical model; White noise;
Conference_Titel :
Aerospace Conference, 2015 IEEE
Conference_Location :
Big Sky, MT
Print_ISBN :
978-1-4799-5379-0
DOI :
10.1109/AERO.2015.7119184