Abstract
Acoustic emission (AE) as a non-destructive testing technique is used to identify structural fatigue damage through the evolution of AE characteristic parameters, aiming to prevent significant economic losses and catastrophic consequences caused by fatigue failure. Traditional AE characteristic parameters (counts, hit rate, duration, rise time) are susceptible to the influence of threshold and user-defined acquisition parameters (PDT, HDT, HLT). Inaccurate parameter settings can miss the AE signals of the structural damage, resulting in inaccurate assessment. To reduce the dependency on threshold and other user-defined parameters, the Kullback-Leibler relative entropy (KLRE) is proposed as a feature parameter for identifying structural fatigue damage and performing fatigue life analysis. The effectiveness and feasibility of KLRE were verified through the fatigue tension–compression test on medium carbon steel (MCS) 1045 V-notch specimens. Based on different waveform recording methods, KLRE is divided into the hit KLRE (HKLRE) and waveform stream KLRE (SKLRE). Experimental results demonstrate that:(1) SKLRE outperforms the traditional AE time–frequency domain features in assessing fatigue damage, exhibiting an inflection point in its evolution trend before reaching fatigue critical failure. (2) Node-independent wavelet packet denoising method improves the initial instability of SKLRE caused by work hardening and crack face friction. (3) Amplitude attenuation does not affect the evolution trends of Shannon entropy (SE) and SKLRE. (4) The evolution trend of HKLRE is similar to traditional AE time–frequency domain features, necessitating the use of multiple features together to reduce uncertainty.
Published Version
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