PSI - Issue 47

Mikhail Bannikov et al. / Procedia Structural Integrity 47 (2023) 685–692 Author name / Structural Integrity Procedia 00 (2019) 000–000

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of the sensors was 5 grams. The microphones were connected to the signal processing unit through standard preamplifiers from Vallensysteme, model AEP4, with a gain of 34 dB. The preamplifier supply voltage was +24V DC (25 mA) supplied via the signal cable. Preamplifier bandwidth ranged from 2.5 kHz to 3 MHz. The microphones were affixed to the rear surface of the sample using adhesive tape, with acoustic gel serving as an interface between the receiving surface of the microphone and the sample. AMSY-6 systems allowed the measurement and analysis of discrete AE signals that crossed a pre-set fixed or floating threshold level. 3. Cluster and multifractal analysis of acoustic emission data The algorithms for cluster and multifractal analysis of acoustic emission data used in this work were previously justified and verified for unidirectional composites [9-10]. The calculation of the dependence of the energy of acoustic emission events on the rate of its change consisted of calculating the derivative of the function E(t) using a difference analogue (Eq. 1). Typical dependences of the energy of acoustic emission events on the rate of its change, calculated using this algorithm and presented using a modified Euclidean metric for cluster analysis, are shown in Fig. 2 c and d. �� � �� � | � | � � � | � | �� � � � �� �� � �� � �� � �� �� � �� � ��� � , (1)

( а )

(b)

(c) (d) Fig. 2, Typical energy distributions of acoustic emission events for unidirectional composites under uniaxial quasi-static (a) and cyclic loading (b) and the dependence of the energy of acoustic emission events on its rate of change for unidirectional composites under uniaxial quasi-static (c) and cyclic loading (d) [9]