Title :
Identification of time-varying non-linear systems with application to knock detection in combustion engines
Author :
Boland, M.D. ; Zoubir, A.M.
Author_Institution :
Signal Process. Res. Centre, Brisbane, Qld., Australia
Abstract :
Knock is a serious problem affecting internal combustion engines, and not only causes unwanted noise from the motor vehicle, but may also cause engine damage. In this paper, the reconstruction of the pressure signal in the combustion chamber from vibration sensors on the engine block is examined. A non-linear model, the Volterra series, is used as the basis for this purpose. A linear model is also utilized and a comparison made. A method of Volterra series kernel estimation based upon the singular value decomposition of the observation matrix is discussed. This method is validated using simulated data
Keywords :
Volterra series; estimation theory; identification; internal combustion engines; matrix decomposition; nonlinear systems; signal reconstruction; singular value decomposition; time-varying systems; vibrations; Volterra series; Volterra series kernel estimation; engine block; engine damage; internal combustion engines; knock detection; linear model; motor vehicle; nonlinear model; observation matrix; pressure signal; reconstruction; singular value decomposition; time-varying non-linear systems; unwanted noise; vibration sensors; Combustion; Computational modeling; Equations; Gaussian noise; Kernel; Mean square error methods; Signal to noise ratio; Speech; Telecommunication computing; Time varying systems;
Conference_Titel :
TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-7803-4365-4
DOI :
10.1109/TENCON.1997.648544