Research output: Contribution to journal › Article › peer-review
СРАВНЕНИЕ ЭНЕРГЕТИЧЕСКИХ СПЕКТРОВ СИГНАЛОВ АКУСТИЧЕСКОЙ ЭМИССИИ ПО ФРАКТАЛЬНЫМ РАЗМЕРНОСТЯМ И СРАВНИТЕЛЬНЫМ ДИАГРАММАМ. / Волков, Александр Евгеньевич; Черняева, Елена Васильевна; Казаринов, Никита Андреевич; Волкова, Н.А.
In: Вестник Пермского национального исследовательского политехнического университета. Механика., No. 1, 07.05.2025, p. 129-138.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - СРАВНЕНИЕ ЭНЕРГЕТИЧЕСКИХ СПЕКТРОВ СИГНАЛОВ АКУСТИЧЕСКОЙ ЭМИССИИ ПО ФРАКТАЛЬНЫМ РАЗМЕРНОСТЯМ И СРАВНИТЕЛЬНЫМ ДИАГРАММАМ
AU - Волков, Александр Евгеньевич
AU - Черняева, Елена Васильевна
AU - Казаринов, Никита Андреевич
AU - Волкова, Н.А.
N1 - Сравнение энергетических спектров сигналов акустической эмиссии по фрактальным размерностям и сравнительным диаграммам / А.Е. Волков, Е.В. Черняева, Н.А. Казаринов, Н.А. Волкова. – DOI: 10.15593/perm.mech/2025.1.10 // Вестник Пермского национального исследовательского политехнического университета. Механика. – 2025. – № 1. – С. 129–138.
PY - 2025/5/7
Y1 - 2025/5/7
N2 - The article analyzes acoustic emissions (AE) aimed at studying changes in the state of the material caused by deformation. It is very difficult to obtain information directly about characteristics of AE sources because of signal distortions caused by dispersion, unequal attenuation at different frequencies, reflections from free surfaces of the sample, distortions created by the sensor, wave-guide and amplifier of electrical oscillations. This paper proposes to compare the characteristics of signals obtained from "fresh" (control) samples and samples that have experienced mechanical testing. Differences between signals are identified with a comparative diagram of spectra repre-senting the modulus of the ratio of Fourier images of signals. Another method used in this work for analyzing signals is based on searching for such characteristics that do not change under the influence of many of the listed distortions. The graph of the spectral power density has a complex serrated shape and, thus, can be considered as a fractal curve which important attribute is the fractal dimension. It is affected by the signal formation conditions and, therefore, can serve as a characteristic for their classification. As an example, a sample of steel 20 was studied. It was sub-jected to cyclic loading from stress σ = 0 to σmax = 1.2σy, (σy is the yield strength) and unloading, with a frequency of f = 20 Hz. The test was stopped at the 8851st cycle, when the "neck" was formed, and the relative elongation was 15%. We compared the AE signals generated during sample indentation in areas located at different distances from the neck. The fractal dimension of the power spectra decreased from 0.72 to 0.62 when approaching the neck zone. Peaks near the frequency of 270 kHz and 680 kHz were distinguished on the comparative diagrams of the spectra. Thus, the considered methods of signal comparison allow us to estimate the degree of change in the state of samples occurred because of mechanical tests.
AB - The article analyzes acoustic emissions (AE) aimed at studying changes in the state of the material caused by deformation. It is very difficult to obtain information directly about characteristics of AE sources because of signal distortions caused by dispersion, unequal attenuation at different frequencies, reflections from free surfaces of the sample, distortions created by the sensor, wave-guide and amplifier of electrical oscillations. This paper proposes to compare the characteristics of signals obtained from "fresh" (control) samples and samples that have experienced mechanical testing. Differences between signals are identified with a comparative diagram of spectra repre-senting the modulus of the ratio of Fourier images of signals. Another method used in this work for analyzing signals is based on searching for such characteristics that do not change under the influence of many of the listed distortions. The graph of the spectral power density has a complex serrated shape and, thus, can be considered as a fractal curve which important attribute is the fractal dimension. It is affected by the signal formation conditions and, therefore, can serve as a characteristic for their classification. As an example, a sample of steel 20 was studied. It was sub-jected to cyclic loading from stress σ = 0 to σmax = 1.2σy, (σy is the yield strength) and unloading, with a frequency of f = 20 Hz. The test was stopped at the 8851st cycle, when the "neck" was formed, and the relative elongation was 15%. We compared the AE signals generated during sample indentation in areas located at different distances from the neck. The fractal dimension of the power spectra decreased from 0.72 to 0.62 when approaching the neck zone. Peaks near the frequency of 270 kHz and 680 kHz were distinguished on the comparative diagrams of the spectra. Thus, the considered methods of signal comparison allow us to estimate the degree of change in the state of samples occurred because of mechanical tests.
KW - акустическая эмиссия, сравнение сигналов, индентирование, спектральная плотность мощности, фрактальная размерность, сравнительная диаграмма спектров
KW - acoustic emission
KW - comparative diagram of spectra
KW - comparison of signals
KW - fractal dimension
KW - indentation
KW - spectral power density
UR - https://www.mendeley.com/catalogue/9db98d7b-46c5-3cc6-ad75-0f06604edda4/
U2 - 10.15593/perm.mech/2025.1.10
DO - 10.15593/perm.mech/2025.1.10
M3 - статья
SP - 129
EP - 138
JO - Вестник Пермского национального исследовательского политехнического университета. Механика.
JF - Вестник Пермского национального исследовательского политехнического университета. Механика.
SN - 2224-9893
IS - 1
ER -
ID: 134641792