Identifying structural defect geometric features from acoustic emission waveforms
The current disclosure determines if structural faults exist and extracts geometric features of the structural faults from acoustic emission waveforms, such as crack length and orientation, and can evaluate the structural faults online, during normal operation conditions.
1. A method for identifying features of a fatigue crack, comprising:
analyzing emission waves from a fatigue crack;
applying external excitation to the fatigue crack;
capturing at least one echo emanating from the fatigue crack caused by the external excitation;
generating at least one secondary emission wave that emanates from the fatigue crack; and
analyzing amplitude and frequency of the at least one secondary emission wave.
2. The method of claim 1 , further comprising identifying at least one geometric feature of the fatigue crack from analysis of the at least one secondary emission wave.
3. The method of 2 , further comprising identifying fatigue crack length and crack tip locations as part of the at least one geometric feature.
4. The method of 2 , wherein frequency dependent patterns in polar plots identify the at least one geometric feature of the fatigue crack.
5. The method of claim 1 , further comprising establishing a library of signal signatures paired with fatigue crack geometries.
6. The method of claim 5 , wherein modeling and scanning laser vibrometry are used in association with time signal analysis are used to establish the library of signal signatures.
7. Creating a library of acoustic emission waveforms linked to crack geometric features comprising:
generating structural vibrations in a test material;
generating excitation signals and applying same to the test material;
collecting first acoustic emission signals generated by the test material;
measuring surface vibration and displacement in the test material;
obtaining a frequency response of the test material to the excitation signals;
extracting surface relative displacement to determine multiple candidate frequencies for acoustic wave detection;
exciting the test material with at least one candidate frequency and collecting at least one second acoustic emission signals from the test material;
analyzing the at least one second acoustic emission signal to extract at least one signal signature associated with fatigue crack geometric features; and
forming a library of features wherein the at least one signal signature is associated with fatigue crack geometric features.
8. The method of claim 7 , wherein the structural vibrations are generated by internal and external excitation sources.
9. The method of claim 8 , wherein the internal excitation is provided by piezoelectric wafer active sensors.
10. The method of claim 8 , wherein the external excitation is created by a mechanical shaker.
11. The method of claim 7 , further comprising identifying at least one geometric feature of a fatigue crack from analysis of the at least one second acoustic emission.
12. The method of claim 11 , further comprising identifying fatigue crack length and fatigue crack tip locations as part of the at least one geometric feature of the fatigue crack.
13. The method of claim 12 , wherein frequency dependent patterns in polar plots identify geometric features of the fatigue crack.