An estimation method of normalized nonlinear output frequency response functions for fatigue damage detection using stochastic response signal

Author:

Tang Weili1,Mao Hanling12ORCID,Li Xinxin12,Huang Zhenfeng12,Mao Hanying3

Affiliation:

1. School of Mechanical Engineering Guangxi University Nanning China

2. Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology Nanning China

3. School of Mechanical and Transportation Engineering Guangxi University of Science and Technology Liuzhou China

Abstract

AbstractNonlinear output frequency response functions (NOFRFs) and its modified version, normalized NOFRFs (norm‐NOFRFs), are composed of multiple spectra, which can sensitively indicate the occurrence of fatigue damage in machinery. However, their application is restricted to a certain extent. Currently, neither NOFRFs nor norm‐NOFRFs can be estimated with only a single response signal. Aimed at this problem, the nonlinear auto‐regressive (NAR) model was introduced, and an estimation method of norm‐NOFRFs is proposed in this paper. Only one stochastic response signal is required in the proposed method, which removes the restrictions on the number and intensity of signals to identify norm‐NOFRFs, and expands the range of scenarios for using norm‐NOFRFs in damage detection. The feasibility and robustness of the proposed method are verified by the nonlinear model in numerical simulation. The effectiveness of revealing and quantifying the fatigue damage is verified by experimental study for three kinds of mechanical parts.

Funder

Specific Research Project of Guangxi for Research Bases and Talents

Natural Science Foundation of Guangxi Province

National Natural Science Foundation of China

Publisher

Wiley

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