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A frequency domain analysis of the influence of non- linear distortions on linear frequency response function measurements performed using multisine test signals is presented in this paper. The aim is to provide a closer insight into the mechanisms at work when multisine signals are subjected to static power-series nonlinearities. Emphasis is given to the behavior of a class of nonlinear distortions, termed hype II contributions, when different types of multisine signals are applied to a cubic, fifth-, seventh-, and ninth-order static nonlinear element The original results presented in this paper are a development of work conducted by the current authors as well as other authors in this area. [ABSTRACT FROM AUTHOR]

This paper examines the output properties of static power-series nonlinearities driven by periodic multiharmonic signals with emphasis given to their effect on linear frequency response function (FRF) measurements. The analysis is based on the classification of nonlinear distortions into harmonic and interharmonic contributions. The properties of harmonic contributions are examined in detail and explicit formulae are derived, by which the number of harmonic contributions generated at the test frequencies can be calculated for odd-order nonlinearities up to, and including, the ninth order. Although an analytic solution for any odd-order nonlinearity is still under investigation, a heuristic methodology is developed that solves this problem. It is shown that the derived formulae provide a useful tool in the examination of the behavior of FRF measurements in the presence of nonlinear distortions. Based on these formulae, different approaches in classifying nonlinear distortions are then compared with respect to their suitability in assessing the influence of system nonlinearities on linear FRF measurements. [ABSTRACT FROM AUTHOR]

When measuring the best linear approximation of systems suffering nonlinear distortions, a specific class of periodic multiharmonic signals is normally used. These are signals with uniformly distributed random phases, termed random phase multisines. In this paper, it is shown that measurements of the best linear approximation of nonlinear systems can also be obtained by using a special type of low crest factor multisines. These signals are compared to random phase multisines and their properties are analyzed in detail. [ABSTRACT FROM AUTHOR]