EXPERIMENTAL AND ANALYTICAL STUDY OF LOW AMPLITUDE AE SIGNALS DUE TO RUBBING/CLAPPING OF CRACK FAYING SURFACES
Abstract
1 OBJECTIVEThe objective of this project is to develop the science and understanding related to low amplitudeacoustic emission (AE") wave signals generated by micro-fractures during the rubbing, clacking,clapping of the crack faying surfaces due to operational c"yclic loading and vibration.The ultimate scope of the proposed research is (i) to identify a direct correlation between cracklength and AE signal and (ii) to develop a method extracting the crack length information fromthe AE signal features.2 BACKGROUNDAcoustic emission is well established as a nondestructive evaluation for monitoring the structuralhealth by listening to the ~pops~ generated by the energy released by incremental crack growth.Existing AE equipment records these pops as so-called ~hits~ identified every time the recordedstructural wave signals exceed a predefined threshold. Experimental evidence accumulated overseveral decades of AE practice indicates that the generation of hits accelerates as the crack entersits terminal stage close to ultimate failure ("Figure 1). Thus an increased hit rate could beinterpreted as ~proximity of failure~ and would require immediate action. However, th""edetection of hits is strongly influenced by how the threshold level is set: (i) if the threshold is toolow, then ~environmental n"oise~ may trigger a large number of false hits and generate a largeType I error and generate crew annoyance with too many false pos"itives; whereas (ii) if thethreshold is set too high to prevent noise triggering, then the result would be a large Type IIerror, i"".e., failure to detect an actual dangerous crack growth with the accompanying potentiallycatastrophic consequences. Thus setting th"e ~correct~ AE threshold remains an ~art form~dependent of the subjective interpretation of experienced AE technicians.By dependin"g on hit rates, the current AE practice does not possess an early warningcapability. Such early warning capability, if existed, wou"ld greatly assist the effectivemanagement of structural fatigue in coordination with mission profile allocation andmaintenance sch"eduling.To impart an early warning capability to the AE process, several investigators, including thecurrent author, have posit th"at the AE signals captured during the AE monitoring contain awealth of information that is not properly exploited by the current AE" practice which is solelybased on recording ~hits~. To extract more information from the AE signals, some authors haveadopted a da"ta-driven approach and tried to apply existing statistical signal processing methodsthat would extract standardized signal features" such as amplitude, rise time, duration, MARSE(measured area of the rectified signal envelop), counts, moments, kurtosis, etc. (Fig""ure 2)Other authors, including the current one, preferred a physics-based approach and directed theirattention to understanding th"e origin and causation of the wave signals recorded by the AEsensors and developing the computational models to assist this process.Two major phenomena that generate crack-related AE signals can be distinguished (Figure 3):(a) AE generation at the crack tip as" the crack advanced during cyclic fatigue or extreme-loadevents; and (b) AE generation by micro-fractures during the rubbing, clack""ing, clapping of thecrack faying surfaces due to operational cyclic loading and vibration. the AE signals of Type (a) make the obje""ct of conventional hit-based AE practice, whereas the AE signals of Type (b) areless studied because they are of much lower amplitu""de and are usually discarded as ~noise~ bythe conventional AE equipment.However, practical fleet operation, provides more conditio"ns for the generation of low-amplitudeType (b) AE signals that for the generation of high-amplitude Type (a) AE signals which requireload levels more easily encountered during accelerated laboratory fatigue testing than actualoperational practice (with the exce"ption of ~hard landings~ or ~extreme flight maneuvers~).He
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 29, 2017
- Source ID
- N000141712829
Entities
People
- Victor Giurgiutiu
Organizations
- Office of Naval Research
- United States Navy
- University of South Carolina