A time and frequency domain approach for identifying nonlinear mechanical system models in the absence of an input measurement

Conventional system identification procedures require that input data or at least an estimate of the input be used in the parameter estimation process. In many 'real' mechanical systems inputs are not readily measured, as in automotive road vehicle data in which the input to the tire patch of the tires from the road is neither measurable nor easy to estimate. A new method for nonlinear system identification of mechanical systems, in the absence of an input measurement, using a combination of time and frequency domain techniques is presented here. In the time domain, restoring force plots are used to characterize the frequency and amplitude characteristics of the nonlinearities. These observed nonlinear characteristics are then used in the output-only formulation of the nonlinear identification through feedback of the outputs frequency domain parameter estimation technique to build a model with linear and nonlinear frequency response functions, which can be used to predict the response of the system. The method is applied to experimental tire-vehicle suspension system data.