Acoustic emission entropy: An innovative approach for structural health monitoring of fracture-critical metallic components subjected to fatigue loading

Abstract

The paper presents an innovative approach for structural health monitoring of metallic components under fatigue crack phenomena. The methodology is based on the evaluation of the information entropy of the acoustic emission (AE) data. AE testing of fatigue crack growth (FCG) is performed on metallic components is performed within an extremely noisy testing environment. Basic AE data analysis is demonstrated to be inefficient with regard to the specific testing conditions. AE entropy is proven to be a reliable damage-sensitive feature for real-time assessment despite both significant noise disturbance and complexity/randomness of the acoustic phenomena. This was also confirmed for (time-)discontinuous monitoring processes over random-based data detections. An innovative monitoring protocol is finally developed according to the experimental evidence also considering the recommendations of the current monitoring. The protocol is found to be promising for structural health monitoring of metallic fracture-critical components of structures under fatigue.