Abstract
This paper presents a new scheme for the estimation of the mean values of parameters in multi-degree-of-freedom structural systems. It is based on a combination of a differential operator transform of the measured data with the extended Kalman filter method. The proposed method can deal with a wide variety of estimation problems including those which are of the non-linear-in-the parameter type. On combining this method with a technique for estimating the variance of the parameters, discussed detailly in part two of this paper, a complete stochastic structural system identification technique can be formulated. Results from simulation studies indicate that the new method can yield reliable estimates of the system parameters even when the noise level in the measurement records is significant.
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