Signal frequency distribution and natural-time analyses from acoustic emission monitoring of an arched structure in the Castle of Racconigi

Niccolini, Gianni; Manuello, A.; Marchis, Elena Teresa Clotilde; Carpinteri, Alberto

doi:10.5194/nhess-17-1025-2017

Cited by 10 publications

(15 citation statements)

References 37 publications

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“…From Figure 15, it results 1/f γ noise with γ ~ 0.0, that characterizes white sources, generated by small defects random diffused in the structural volume. Finally, the log-log plot of the AE power spectrum versus frequency for a monitored masonry arch [33], belonging to the Racconigi Castle (Figure 14a,b) in Piedmont (Italy) is proposed. This last example has been presented in order to demonstrate that a "white" response is obtained on a masonry structural element in which the post-peak loading phase is far from being achieved.…”

Section: /F Noise In Damaging Structures: In-situ Ae Monitoringmentioning

confidence: 99%

Fluctuations of 1/f Noise in Damaging Structures Analyzed by Acoustic Emission

2018

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It is well known in literature that frequency fluctuations of different physical quantities clearly show 1/f noise power spectra. In the present work, the authors observe that in some brittle materials, such as concrete, masonry, and mortar, Acoustic Emission (AE) signals, generating from brittle fracture phenomena, exhibit a frequency fluctuation approaching to 1/f. Acoustic Emission data obtained from laboratory tests on concrete samples, and from in-situ monitoring of some important Italian historical buildings are reported in terms of spectral density vs. frequency. It is shown that in structural elements subjected to different load conditions, the frequency fluctuations are 1/f like. The study and interpretation of these phenomena through the use of the AE technique can be therefore very useful for identifying the transition from the critical conditions of a structure to those that involve an incipient collapse.

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Section: /F Noise In Damaging Structures: In-situ Ae Monitoringmentioning

confidence: 99%

Fluctuations of 1/f Noise in Damaging Structures Analyzed by Acoustic Emission

2018

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“…The natural time analysis (NTA) was introduced in the early 2000s [1][2][3], and revealed hidden properties in the time series of complex systems that cannot be observed in conventional time; for a review, see, e.g., [4]. It has found applications in various disciplines ranging from statistical physics [5][6][7][8], solid state physics [9] and, rock physics [10] to environmental physics [11][12][13], cardiology [14][15][16][17][18], and engineering [19][20][21]. The NTA has also found various applications in the context of seismology and physics of earthquakes (EQs); see, e.g., [3,.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Epicenter of an Impending Strong Earthquake by Combining the Seismicity Order Parameter Variability Analysis with Earthquake Networks and Nowcasting: Application in the Eastern Mediterranean

et al. 2021

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The variance κ1 of the natural time analysis of earthquake catalogs was proposed in 2005 as an order parameter for seismicity, whose fluctuations proved, in 2011, to be minimized a few months before the strongest mainshock when studying the earthquakes in a given area. After the introduction of earthquake networks based on similar activity patterns, in 2012, the study of their higher order cores revealed, in 2019, the selection of appropriate areas in which the precursory minima βmin of the fluctuations β of the seismicity order parameter κ1 could be observed up to six months before all strong earthquakes above a certain threshold. The eastern Mediterranean region was studied in 2019, where all earthquakes of magnitude M≥7.1 were found to be preceded by βmin without any false alarm. Combining these results with the method of nowcasting earthquakes, introduced in 2016, for seismic risk estimation, here, we show that the epicenter of an impending strong earthquake can be estimated. This is achieved by employing—at the time of observing the βmin—nowcasting earthquakes in a square lattice grid in the study area and by averaging, self-consistently, the results obtained for the earthquake potential score. This is understood in the following context: The minimum βmin is ascertained to almost coincide with the onset of Seismic Electric Signals activity, which is accompanied by the development of long range correlations between earthquake magnitudes in the area that is a candidate for a mainshock.

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“…The analysis in the natural time domain allows identifying when a complex system enters a critical state [50]. For a time series comprising N events, the natural time k  of the k-th event is defined as this event normalized, divided by the total number of the considered events, k kN  = [2], see Figure 4.…”

Section: Natural-time Analysismentioning

confidence: 99%

Long-Range Correlations and Natural Time Series Analyses from Acoustic Emission Signals

Friedrich¹,

Cezar²,

Colpo³

et al. 2021

Preprint

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This work focuses on analyzing acoustic emission (AE) signals as a means to predict failure in structures. Two main approaches are considered: (i) long-range correlation analysis using both the Hurst (H) and the Detrended Fluctuation Analysis (DFA) exponents, and (ii) natural time domain (NT) analysis. These methodologies are applied to the data collected from two application examples: a glass fiber reinforced polymeric plate and a spaghetti bridge model, where both structures were subjected to increasing loads until collapse. A traditional (AE) signal analysis is also performed to reference the study of the other methods. Results indicate that the proposed methods yield a reliable indication of failure in the studied structures.

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Signal frequency distribution and natural-time analyses from acoustic emission monitoring of an arched structure in the Castle of Racconigi

Cited by 10 publications

References 37 publications

Fluctuations of 1/f Noise in Damaging Structures Analyzed by Acoustic Emission

Fluctuations of 1/f Noise in Damaging Structures Analyzed by Acoustic Emission

Estimating the Epicenter of an Impending Strong Earthquake by Combining the Seismicity Order Parameter Variability Analysis with Earthquake Networks and Nowcasting: Application in the Eastern Mediterranean

Long-Range Correlations and Natural Time Series Analyses from Acoustic Emission Signals

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