Real-Time Wireless Acoustic Emission Monitoring for High-Cycle-Fatigue Behavior of High-Strength Stainless Steel Under Different Stress Ratio

Ultra-high-strength stainless steel (UHSSS) is widely used in aviation and aerospace. Its fatigue behavior, especially the fatigue characteristics, with stress concentration factor <inline-formula> <tex-math notation="LaTeX">${K}_{t}$ </tex-math></inline-formula> is not fully investigated. As an advanced sensor technology, acoustic emission (AE) nondestructive testing is able to accurately monitor the critical failure of the test piece to avoid rapid and unforeseeable fracture. In this article, first, a wireless AE technology is proposed to monitor the fatigue behavior of UHSSSs. Then, the interactions between AE versus fatigue stage and <inline-formula> <tex-math notation="LaTeX">${S}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> curves under different stress ratios are investigated. The AE algorithm based on Shannon entropy is designed to evaluate the performance of UHSSS HCF, avoiding the dependence of the traditional AE parameter method on the threshold. Finally, the quantitative relationship between cumulative information entropy versus fatigue cycles of notched UHSSS specimens with the stress ratio (<inline-formula> <tex-math notation="LaTeX">${R}$ </tex-math></inline-formula>) value of −1 and 0.06 is verified. This research is conducted to provide new insights into constructing the interactions among the <inline-formula> <tex-math notation="LaTeX">${S}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> curve, fatigue limit, and AE signal parameters, further giving a new approach to predict fatigue limit and recognize the fatigue status of steel structure only depending on the AE signal.