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Acoustic emission is a phenomenon where external stimuli, such as stress or strain, cause small displacements within a material, releasing energy as elastic waves. This is used to monitor the sudden structural changes within materials.

AE signal features include amplitude, energy, frequency, and duration. These characteristics help in categorizing the type of source event, such as crack growth or fiber breakage.

AE sensors are devices that detect the elastic waves generated by acoustic emissions. They are often piezoelectric and convert these waves into electrical signals for analysis.

AE testing is used in monitoring the integrity of structures, detecting crack growth in materials, leakage detection, and evaluating the aging of infrastructure.

In pressure vessel monitoring, AE is used to detect crack propagation, fiber breakage in composites, and corrosion. This helps in predicting failure and scheduling maintenance.

AE is particularly useful for testing composite materials as it can detect interlaminar shear, fiber breakage, and delamination which might not be evident in visual inspections.

AE testing offers non-destructive evaluation, real-time monitoring, and can detect defects before they become critical. It's also sensitive to active defect growth.

Hit-driven AE systems trigger recording when the acoustic signal exceeds a predefined threshold. This allows for selective data acquisition and analysis.

Continuous AE systems record all acoustic emission data continuously. This provides a comprehensive dataset but requires significant storage and analysis capabilities.

AE source location involves determining the origin of acoustic emissions within a material using sensor triangulation, which is critical for pinpointing the site of structural defects.

The Felicity Ratio is the stress level at which acoustic emissions reappear after the Kaiser Effect divided by the previous stress level. Ratios less than 1 indicate damage has occurred.

The Kaiser Effect refers to the phenomenon wherein materials do not emit acoustic emissions until they are stressed beyond their previous maximum level, useful in assessing the loading history of materials.

Frequency analysis of AE signals can differentiate between different types of events, such as crack propagation and fiber breakage, by examining the frequency content of the detected emissions.

Waveform-based AE analysis involves studying the recorded waveform signatures to identify material behavior, using parameters such as peak amplitude and signal energy.