Detection of acoustic emission signals in the polymer composite material by adaptive fiber-optic sensors

Author(s):  
Oleg V. Bashkov ◽  
Roman V. Romashko ◽  
Valeriy I. Zaykov ◽  
Alexander E. Protsenko ◽  
Michail N. Bezruk ◽  
...  
2016 ◽  
Vol 51 (5) ◽  
pp. 542-549 ◽  
Author(s):  
A. N. Anoshkin ◽  
A. A. Voronkov ◽  
N. A. Kosheleva ◽  
V. P. Matveenko ◽  
G. S. Serovaev ◽  
...  

Author(s):  
Oleg Bashkov ◽  
Anton Bryansky ◽  
Timofey Efimov ◽  
Roman Romashko

The work is devoted to the study of the mechanisms of damage accumulation in a polymer composite material (PCM) during fatigue loading. Mechanical testing of a fiberglass sample was carried out by cyclic tension accompanied by registration of acoustic emission (AE). For the recorded AE signals, the Fourier spectra were calculated and used for clustering with Kohonen self-organizing map. Relations between clusters and types of damage in the PCM structure were established. The analysis of the peak frequencies of the Daubechies D14-wavelet components of AE signals was carried out. Obtained results has allows one to describe the processes of destruction in the PCM sample. It has been established that, on the base of local formation of microdamages in the matrix and the fracture of the fibers detected during recording of the AE data, it is possible to predict the destruction of the polymer composite material, while the beginning of a material destruction can be registered if the damage identified as an adhesion failure is observed. Perspectives of application of adaptive fiber-optic AE sensors for structural monitoring of PCMs on the base of preliminary experimental results are considered and discussed.


2019 ◽  
Vol 946 ◽  
pp. 270-275
Author(s):  
O.V. Bashkov ◽  
H. Khon ◽  
V.I. Zaikov ◽  
I.O. Bashkov ◽  
A.I. Evstigneev

This paper presents the results of the analysis of acoustic emission signals registered by using fiber-optic sensors during the propagation of ultrasonic waves in a polymer composite material. Fiber-optical sensors for acoustic emission were constructed according to the scheme of an adaptive holographic interferometer. Unlike piezoelectric sensors, fiber-optic sensors are distributed type sensors. This imposes certain features on the detection of signals in plates in which fiber-optic sensors are embedded. It is established that the difference of the spectrum of acoustic emission signals is registered in different directions of wave propagation. The local maximums of the spectrum are determined by the mode of wave propagation in the plate in different directions and the location of fiber-optic sensors.


Author(s):  
О.В. Башков ◽  
А.А. Брянский ◽  
Т.И. Башкова

Данная работа посвящена исследованию механизмов накопления повреждений в полимерном композиционном материале (ПКМ) в ходе усталостного нагружения. Механическое испытание образца стеклопластика проводили циклическим растяжением в сопровождении регистрации акустической эмиссии (АЭ). Для зарегистрированных сигналов АЭ рассчитывались спектры Фурье и использовались для кластеризации самоорганизующейся картой Кохонена (SOM). Полученные центроиды, для снижения количества анализируемых кластеров, разделяли на кластеры методом k-средних. Кластеры второго этапа кластеризации соотносились с типами повреждений в структуре ПКМ. Рассчитывались периоды критической интенсивности регистрации различных типов образующихся повреждений. Дополнительно проведён анализ пиковых частот уровней вейвлет декомпозиции Добеши 14 сигналов АЭ. На основании проведенных методов анализа данных АЭ описаны протекающие процессы разрушения в образце ПКМ. This work is aimed the study the mechanisms of damage accumulation in a polymer composite material (PCM) during fatigue loading. Mechanical test of a fiberglass sample was done by cyclic tension with acoustic emission (AE) registration. The Fourier spectra were calculated for the recorded AE signals and used for clustering with a self-organizing Kohonen map (SOM). The obtained centroids, in order to reduce the number of analyzed clusters, were divided into clusters by the k-means method. Clusters of the second stage clustering correlated with the types of damage in the structure of the PCM. The periods of the critical intensity of registration of various types of formed damages were calculated. Additionally, the peak frequencies of the levels of Daubechies 14 wavelet decomposition of AE signals was analyzed. Based on the methods for analyzing the AE data, the processes of destruction in the PCM sample are described.


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