On the Orthogonalised Reverse Path Method for Nonlinear System Identification

The problem of obtaining the underlying linear dynamic compliance matrix in the presence of nonlinearities in a general Multi-Degree-of-Freedom (MDOF) system can be solved using the Conditioned Reverse Path (CRP) method introduced by Richards and Singh (1998 Journal of Sound and Vibration, 213(4): p. 673-708). The CRP method also provides a means of identifying the coefficients of any nonlinear terms which can be specified a priori in the candidate equations of motion. Although the CRP has proved extremely useful in the context of nonlinear system identification, it has a number of small issues associated with it. One of these issues is the fact that the nonlinear coefficients are actually returned in the form of spectra which need to be averaged over frequency in order to generate parameter estimates. The parameter spectra are typically polluted by artefacts from the identification of the underlying linear system which manifest themselves at the resonance and anti-resonance frequencies. A further problem is associated with the fact that the parameter estimates are extracted in a recursive fashion which leads to an accumulation of errors. The first minor objective of this paper is to suggest ways to alleviate these problems without major modification to the algorithm. The results are demonstrated on numerically-simulated responses from MDOF systems. In the second part of the paper, a more radical suggestion is made, to replace the conditioned spectral analysis (which is the basis of the CRP method) with an alternative time domain decorrelation method. The suggested approach – the Orthogonalised Reverse Path (ORP) method – is illustrated here using data from simulated Single-Degree-of-Freedom (SDOF) and MDOF systems.