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Our publications in 2022

List of publications in 2022, in which our employees participated:

V. Barat, A. Marchenkov, V. Bardakov, D. Zhgut, M. Karpova, T. Balandin, S. Elizarov. Assessment of the Structural State of Dissimilar Welded Joints by the Acoustic Emission Method. Appl. Sci. 2022, 12(14), 7213. https://www.mdpi.com/2076-3417/12/14/7213 (full text). DOI: 10.3390/app12147213

Abstract In this study, we investigated defect detection in dissimilar welded joints by the acoustic emission (AE) method. The study objects were carbide and decarburized interlayers, which are formed at the fusion boundary between austenitic and pearlitic steels. Diffusion interlayers, as a structural defect, usually have microscopic dimensions and cannot be detected using conventional non-destructive testing (NDT) methods. In this regard, the AE method is a promising approach to diagnose metal objects with a complex structure and to detect microscopic defects. In this paper, the AE signatures obtained from testing defect-free specimens and specimens with diffusion interlayers are analyzed. We found that the AE signature for defective and defect-free welded joints has significant differences, which makes it possible to identify descriptors corresponding to the presence of diffusion interlayers in dissimilar welded joints.


V. Barat, A. Marchenkov, V. Bardakov, D. Zghut, M. Karpova, S. Elizarov. Diagnostics of Dissimilar Weld Joints of Austenitic to Pearlitic Steels by Acoustic Emission. J. Inst. Eng. India Ser. D. 2022. DOI: 10.1007/s40033-022-00409-y

Abstract Dissimilar welded joints are widely used nowadays in power engineering industry for manufacturing of pipelines and other power equipment elements. Diagnostics of welding defects in these joints by nondestructive testing (NDT) is quite difficult, since high gradients of chemical composition and microstructure reduce the sensitivity of traditional NDT scanning methods. The paper is devoted to the study of the possibility of AE method application for diagnostics of dissimilar welded joints of pearlitic to austenitic steel. The identification of defects lack of penetration and microstructure defects in the form of diffusion interlayers under cyclic tensile loading of flat specimens with welded joints is considered. As a result of the research, it was found that dissimilar welded joints containing defects are characterized by a specific AE signature. It was established that for welded specimens with lack of penetration and diffusion interlayers, the AE activity turned out to be significantly higher than for defect-free ones. Herewith, specimens with diffusion interlayers are characterized by large amplitude values (up to 70–80 dB), and specimens with lack of penetration are characterized by higher AE activity, while the amplitudes of AE hits did not exceed 60–65 dB. The results obtained can be used for determination of diagnostic criteria for detecting defects by AE method and subsequent development of an industrial NDT technique for dissimilar welded joints under study.


V. Barat, A. Marchenkov, S. Ushanov, V. Bardakov, S. Elizarov. Investigation of Acoustic Emission of Cracks in Rails under Loading Close to Operational. Appl. Sci. 2022, 12(22), 11670. https://www.mdpi.com/2076-3417/12/22/11670 (full text). DOI: 10.3390/app122211670

Abstract The paper is devoted to the study of the possibility of detecting cracks in railway rails by the acoustic emission (AE) method. An experimental study of AE signals under cyclic compression loading of rail fragments, which simulates the rail operating load, has been carried out. Fragments of rails without defects, as well as fragments containing pre-grown fatigue cracks, were studied. It was found that AE signals generated by a rail with a crack have higher activity compared to signals from defect-free specimens. It is shown that the AE signals during the loading of defect-free specimens have a short duration and low amplitude and may be caused by the deformation of non-metallic inclusions. The crack presence leads to an increase in the AE hits rate and changes the nature of the distribution of the AE hits amplitudes. It is shown that the crack location has no effect on the reliability of its detection by the AE method. Criteria of crack detection by AE testing are offered as a result of this study.


A. Machikhin, A. Poroykov, V. Bardakov, A. Marchenkov, D. Zhgut, M. Sharikova, V. Barat, N. Meleshko, A. Kren. Combined Acoustic Emission and Digital Image Correlation for Early Detection and Measurement of Fatigue Cracks in Rails and Train Parts under Dynamic Loading. Sensors 2022, 22(23), 9256. https://www.mdpi.com/1424-8220/22/23/9256 (full text). DOI: 10.3390/s22239256

Abstract Fatigue crack in rails and cyclic-loaded train parts is a contributory factor in multiple railroad accidents. We address the problem of crack detection and measurement at early stages, when total failure has not yet occurred. We propose to combine acoustic emission (AE) testing for prediction of crack growth with digital image correlation (DIC) for its accurate quantitative characterization. In this study, we imitated fatigue crack appearance and growth in samples of railway rail and two train parts by cyclic loading, and applied these two techniques for inspection. Experimental results clearly indicate the efficiency of AE in the early detection of fatigue cracks, and excellent DIC capabilities in terms of geometrical measurements. Combination of these techniques reveals a promising basis for real-time and non-destructive monitoring of rails and train parts.


Y. A. Eliovich, V. A. Barat, V. V. Bardakov, A. Y. Marchenkov, D. D. Khokhlov and D. A. Zhgut. Predictive Analysis of Structural Changes in Paratellurite Crystals Using the Acoustic Emission Method. International Conference on Information, Control, and Communication Technologies (ICCT), 2022, pp. 1-5. DOI: 10.1109/ICCT56057.2022.9976555

Abstract Paratellurite TeO 2 crystals of various degrees of defectiveness were studied under external mechanical loading. The results of structural changes in crystals were obtained by capturing acoustic emission data and polarized optical microscopy observation. Peculiarities of acoustic emission corresponding to defects of various types in crystals are revealed. It has been experimentally shown that acoustic emission monitoring of a mechanically loaded paratellurite makes it possible to assess its structure degree of defectiveness even in the elastic zone. Thus, the possibility of irreversible deformation process also can be predicted.


Sagaidak A.I., Bardakov V.V. Method for determining strength of concrete by acoustic emission method. Russian patent №2807868 (2022). eLibrary ID: 56017020

АннотацияОбласть применения изобретения относится к строительству, а именно кконтролю бетонных смесей различных составов методом сигналов акустической эмиссии при формировании их структуры. Раскрывается способ определения прочности бетона с химическими и минеральными добавками методом акустической эмиссии, включающий определение параметров сигналов акустической эмиссии и фиксацию времени их появления в режиме реального времени. Для осуществления способа в бетонную смесь помещают глубинный волновод с закрепленным преобразователем акустической эмиссии. На бетонных кубах размером не менее 200×200×200 мм различных составов осуществляют контроль структурообразования, причем каждый состав дублируется два-три раза, и для каждого состава проводят контроль непрерывно не менее двадцати восьми суток. Далее проводят контроль прочностных характеристик бетона, причем прочность контрольных кубов контролируют в 1-е, 3-и, 7-е, 14-е и 28-е сутки твердения. После этого устанавливают соотношения и зависимости информативных параметров сигналов акустической эмиссии между прочностными характеристиками бетона. Затем рассматривают информативные параметры сигналов акустической эмиссии, тесно коррелирующие с прочностью бетона, устанавливают оптимальные временные интервалы измерений акустической эмиссии, позволяющие наиболее точно вести прогнозирование кинетики дальнейшего набора прочности бетона методом акустической эмиссии. После этого проводят регистрацию импульсов акустической эмиссии в режиме реального времени, выделяют три стадии структурообразования, характеризующиеся различной степенью интенсивности акустической эмиссии. Время начала и конца второго периода уточняют в автоматизированном режиме, при котором используют информационный критерий Акаике где AIC – значение коэффициента критерия Акаике; – зависимость числа импульсов акустической эмиссии от времени; N – длительность интервала наблюдения; k – номер отсчета. При этом в качестве критерия детектирования используется изменение знака производной функции Акаике, который соответствует разладке процесса, а в качестве времени выбирается момент, когда критерий достигает минимума, при этом в рамках данного алгоритма критерий Акаике применяется дважды – для определения начала и конца второй стадии. Далее устанавливают время начала и конца каждой из трех стадий, определяют параметры и , параметр определяют как разность между полученными значениями начала и конца второго периода, и тангенс угла наклона третьего периода по зависимости – сумма импульсов акустической эмиссии от времени, а параметр определяют методом наименьших квадратов во временном окне, начало которого совпадает с началом третьей стади, и на основании оцененных параметров и . После чего осуществляют прогнозирование прочности бетона в соответствии с прогностическими моделями. В качестве химических добавок используются СП-180 по ТУ 20.59.59-003-26025492-2018 или CENTRIPOR TFM 411R, а в качестве минеральной добавки – доменный гранулированный молотый шлак. Техническим результатом изобретения является возможность определения прочности бетона с химическими и минеральными добавками методом акустической эмиссии, причем относительная погрешность применения автоматизированного алгоритма при прогнозировании прочности не превышает 4,0%
Abstract Field: construction; concrete mixtures. Substance: scope of the invention relates namely to the control of concrete mixtures of various compositions using the method of acoustic emission signals during the formation of their structure. A method for determining the strength of concrete with chemical and mineral additives using the acoustic emission method is disclosed, which includes determining the parameters of acoustic emission signals and recording the time of their appearance in real time. To implement the method, a deep waveguide with an attached acoustic emission transducer is placed in the concrete mixture. On concrete cubes of different compositions measuring at least 200×200×200 mm the structure formation is monitored, and each composition is duplicated two to three times, and for each composition monitoring is carried out continuously for at least twenty-eight days. Next, the strength characteristics of the concrete are monitored, and the strength of the control cubes is monitored on the 1st, 3rd, 7th, 14th and 28th days of curing. After this, the relationships and dependencies of the informative parameters of the acoustic emission signals between the strength characteristics of concrete are established. Then, the informative parameters of acoustic emission signals, which closely correlate with the strength of concrete, are considered, and the optimal time intervals for measuring acoustic emission are established, which makes it possible to most accurately predict the kinetics of further strength gain of concrete using the acoustic emission method. After this, acoustic emission pulses are recorded in real time, and three stages of structure formation are distinguished, characterized by varying degrees of acoustic emission intensity. The start and end times of the second period are specified in an automated mode, in which the Akaike information criterion is used where AIC is the value of the Akaike criterion coefficient; – dependence of the number of acoustic emission pulses on time; N – duration of the observation interval; k – reference number. In this case, the change in the sign of the derivative of the Akaike function, which corresponds to the disorder of the process, is used as a detection criterion, and the moment when the criterion reaches a minimum is selected as the time. Within the framework of this algorithm, the Akaike criterion is applied twice - to determine the beginning and end of the second stage. Next, set the start and end times of each of the three stages, the parameters and are determined. The parameter is determined as the difference between the obtained values of the beginning and end of the second period, and the slope of the third perioddepending on the sum of acoustic emission pulses versus time. The parameter is determined by the least squares method in a time window, the beginning of which coincides with the beginning of the third stage, and based on the estimated parameters and . Then the strength of concrete is predicted in accordance with predictive models. SP-180 according to TU 20.59.59-003-26025492-2018 or CENTRIPOR TFM 411R are used as chemical additives, and ground and granulated blast furnace slag is used as a mineral additive. Effect: ability to determine the strength of concrete with chemical and mineral additives using the acoustic emission method, and the relative error of using an automated algorithm when predicting strength does not exceed 4.0%.