Non-Crack-Growth Acoustic Emission Observed in Controlled-Stress-Intensity-Factor High-Cycle-Fatigue Tests

Author:

Joseph Roshan1,Giurgiutiu Victor2ORCID

Affiliation:

1. Acellent Technologies Inc., Sunnyvale, CA 94085, USA

2. Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA

Abstract

Acoustic emission (AE) was monitored during stress intensity factor (SIF)-controlled high-cycle fatigue (HCF) tests on an aluminum 2024-T3 specimen with a fatigue crack growing at its center. The SIF control was implemented in such a manner that crack growth could be slowed down and even inhibited while the fatigue experiment continued. In the beginning, a specific type of AE signal was observed while the crack was allowed to grow to up to approximately 9.4 mm in length. Subsequently, the load was reduced in order to control the SIF value at the crack tip and to inhibit the crack growth. AE signals were recorded even when the crack stopped growing, although the specific signature of these AE signals was different from those observed when the crack was growing, as discussed in the text. The gist of the phenomenon reported in this article is that strong AE signals could still be observed even when the crack stopped growing. These latter AE signals could be due to rubbing and clapping of the crack faying surfaces. Travel analysis was consistently performed to ensure that these AE signals were originating from the crack, though not necessarily from the crack tip. In addition, absorbing clay wave dams were built around the crack region to inhibit boundary reflections and grip noise. Fast Fourier Transform (FFT) and Choi–Williams Transform (CWT) analysis were performed to classify the AE signals. It was observed that the AE signals related to crack growth were clearly different from the AE signals originating from the crack while the crack was not growing. Strong S0-mode Lamb wave components were observed in the crack-growth AE signals, whereas strong A0-mode Lamb wave components dominated the non-crack-growth AE signals. Pearson correlation clustering analysis was performed to compare the crack-growth and non-crack growth AE signals. We propose that the fatigue-crack faying surfaces may undergo rubbing and/or clapping during fatigue cyclic loading and thus produce strong AE signals that are registered by the AE system as hits, although the crack is not actually growing. The understanding of this phenomenon is very important for the design of the structural health monitoring (SHM) system based on AE-hit signal capture and interpretation.

Funder

Office of Naval Research

Publisher

MDPI AG

Subject

Control and Optimization,Control and Systems Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Artificial Intelligence-Enabled Crack Length Estimation From Acoustic Emission Signal Signatures;Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems;2023-12-11

2. Piezoelectric Wafer Active Sensor Transducers for Acoustic Emission Applications;Sensors;2023-08-11

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