An experimental research program, designed to detect acoustic emissions (AE) produced during propagation of discrete Mode I and Mode II fractures in large rock specimens, is underway at the Rock Mechanics Laboratory at The University of Texas at Austin. Equipment developed, and signal processing techniques used, are described in detail. Preliminary results of testing granite and dolostone rock specimens are presented. Results indicate that very similar signals may be produced by very different rocks, suggesting a similarity of internal mechanism during crack propagation.
Acoustic emissions (AE) are elastic waves generated in conjunction with energy release during crack propagation and internal deformations in materials. This release of energy is manifested as transient stress waves which propagate from the locus of a structural change associated with material failure and changes in the local stress field. Micro-structural changes or displacements occur very rapidly and can be produced by a wide variety of material responses to stress changes, from small scale changes within a crystal lattice structure to growth of macro-cracks. Each AE event is a signature of an actual mechanism, a discrete event directly reflecting material response. Information about material properties and failure mechanism is contained in each AE waveform. The aim of this experimental study is to learn to "read" the AE signature, to identify characteristics and correlate with mechanisms, assisting in establishing the basis for systematic AE record interpretation. The study of AE has developed into an increasingly popular form of nondestructive testing. The technique has long been employed in pressure vessel testing, and an American Society for Testing and Materials (ASTM) method is widely used in the nuclear industry for this purpose. Metallurgists have successfully used AE to identify discrete molecular level events. AE events have been used, especially in Japan, to model earthquake activity. In the field of rock mechanics, AE methods have been implemented to address problems such as rock burst predictions, hydraulic fracturing, mine pillar stress and deformation, rock mass stability, and the velocity of groundwater movement. Detection and analysis of AE signals are made difficult for several reasons. Following each event, the originally produced signal is filtered as the emitted stress waves propagate through the surrounding material. The filtered stress waves are detected by observing and measuring material response only at an accessible surface. Such surface displacements related to AE events are extremely small, necessitating the use of elaborate electronic transducers and analytical devices. In addition, simple AE events are not instantaneous, and the duration of these events can be from microseconds to many milliseconds depending on the material, the loading, and the nature of the source. Each detected waveform may be very complicated and difficult to analyze, with some of the complexity introduced as energy is released over the duration of the event. In the near-field, wave modes are not easily defined, while in the far-field different wave modes can be discriminated. Local geometry and boundary condition effects will combine to introduce reflections which complicate the latter portions of detected signals.