The acoustic emission (AE) technique is one of the most widely used in the field of structural monitoring. Its popularity mainly stems from the fact that it belongs to the category of non-destructive techniques (NDT) and allows the passive monitoring of structures. The technique employs piezoelectric sensors to measure the elastic ultrasonic wave that propagates in the material as a result of the crack formation’s abrupt release of energy. The recorded signal can be investigated to obtain information about the source crack, its position, and its typology (Mode I, Mode II). Over the years, many techniques have been developed for the localization, characterization, and quantification of damage from the study of acoustic emission. The onset time of the signal is an essential information item to be derived from waveform analysis. This information combined with the use of the triangulation technique allows for the identification of the crack location. In the literature, it is possible to find many methods to identify, with increasing accuracy, the onset time of the P-wave. Indeed, the precision of the onset time detection affects the accuracy of identifying the location of the crack. In this paper, two techniques for the definition of the onset time of acoustic emission signals are presented. The first method is based on the Akaike Information Criterion (AIC) while the second one relies on the use of artificial intelligence (AI). A recurrent convolutional neural network (R-CNN) designed for sound event detection (SED) is trained on three different datasets composed of seismic signals and acoustic emission signals to be tested on a real-world acoustic emission dataset. The new method allows taking advantage of the similarities between acoustic emissions, seismic signals, and sound signals, enhancing the accuracy in determining the onset time.

We subjected the time series of quasi-rigid-body vibration pulses (elastic emissions) from laboratory fracture carried out by a piezoelectric accelerometer on concrete and rock specimens under uniaxial compression to statistical analysis. In both cases, we find that the waiting-time distribution can be described by a scaling law extending over several orders of magnitude. This law is indistinguishable from a universal scaling law recently proposed for the waiting-time distributions of acoustic emissions in heterogeneous materials and earthquakes, suggesting its general validity for fracture processes independent of modes and magnitude scales. DOI: http://dx.doi.org/10.1103/PhysRevE.82.046115 © 2010 The American Physical Society

Piezonuclear reactions, which occur in inert and nonradioactive elements, are induced by high pressure and, in particular, by brittle fracture phenomena in solids under compression. These low energy reactions generally take place in nuclei with an atomic weight that is lower or equal to that of iron (Fe). The experimental evidence, obtained from repeatable measurements of neutron emissions, can be also recognized considering the anomalous chemical balances of the major events that have affected the Earth’s crust, oceans and atmosphere, over the last four billion years. These anomalies include: (i) the abrupt variations in the most abundant elements in correspondence to the formation of tectonic plates; (ii) the Great Oxidation Event (2.7 to 2.4 billion years ago), with a sharp increase in atmospheric oxygen and the subsequent origin of life; (iii) the increase of carbon and nytrogen concentrations in the primordial atmosphere. Natural piezonuclear reactions are induced by fault sliding and plate subduction phenomena.

Historical churches, tall ancient masonry buildings, and bell towers are structures subjected to high risks due to their age, elevation, and small base-area-to-height ratio. In this paper, the results of an innovative monitoring technique for structural integrity assessment applied to a historical bell tower are reported. The emblematic case study of the monitoring of the Turin Cathedral bell tower (northwest Italy) is herein presented. First of all, the damage evolution in a portion of the structure localized in the lower levels of the tall masonry building is described by the evaluation of the cumulative number of acoustic emissions (AEs) and by different parameters able to predict the time dependence of the damage development, in addition to the 3D localization of the AE sources. The b-value analysis shows a decreasing trend down to values compatible with the growth of localized micro and macro-cracks in the portion of the structure close to the base of the tower. These results seem to be in good agreement with the static and dynamic analysis performed numerically by an accurate FEM (finite element model). Similar results were also obtained during the application of the AE monitoring to the wooden frame sustaining the bells in the tower cell. Finally, a statistical analysis based on the average values of the b-value are carried out at the scale of the monument and at the seismic regional scale. In particular, according to recent studies, a comparison between the b-value obtained by AE signal analysis and the regional activity is proposed in order to correlate the AE detected on the structure to the seismic activity, discriminating foreshock, and aftershock intervals in the analyzed time series.