Abstract

When the structures or parts are subjected to fatigue damage, its nonlinear characteristics will be characterized sensitively. The nonlinear characteristics of the system can be well described by the nonlinear output frequency response function deduced by the Volterra series. The nonlinear output frequency response function is the collection of frequency functions of various orders which contain different nonlinear information about the system. In other words, it is not intuitive when it is used directly for the detection of fatigue damage to structures or parts. Therefore, how to build an intuitive detection index will be the key to the application of the nonlinear output frequency response function in engineering practice. In this paper, based on the concept of information entropy, complexity and divergence, 4 detection indexes were proposed and the definition and estimation methods were given. Fatigue tests were carried out on the specimens by a fatigue test machine, and a series of specimens with different fatigue cycle times were obtained. The nonlinear output frequency response function was estimated by using the data of the hammer excitation measurement. The detection effect of 4 detection indexes and traditional detection index Fe was analyzed and compared. The results show that the proposed detection indexes are more sensitive and effective for detecting fatigue damage before microcracks formed.

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