Журнал Российского общества по неразрушающему контролю и технической диагностике
The journal of the Russian society for non-destructive testing and technical diagnostic
 
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30 | 04 | 2024
2022, 06 June

DOI: 10.14489/td.2022.06.pp.038-047

Altay Ye., Fedorov A. V., Stepanova K. A.
ESTIMATION OF RELATIONSHIP BETWEEN INFORMATION COMPONENTS AND NOISE OF ACOUSTIC EMISSION SIGNALS
(pp. 38-47)

Abstract. In this article, a method for processing acoustic information is presented to assess the correlation relationship of information components and noise of acoustic emission (AE) signals. The method is based on a polynomial approximation of bidirectional Butterworth high and low pass filters. The operability of the processing method on full-scale samples of the noisy AE signal is analyzed and the evaluation of the received processing is carried out on the basis of quantitative indicators. Bidirectional implementation of high-pass filters improves the quality of processing when compared with a low-pass filter. To assess the correlation relationship using the considered processing method, fragments of the information component and noise are isolated from the noisy signal. Based on the selected components, a high correlation relationship between AE information signals and noise has been established.

Keywords: аcoustic control, acoustic emission signals processing, correlation relationship, signal-to-noise ratio.

Ye. Altay, A. V. Fedorov, K. A. Stepanova (National Research ITMO University. Saint-Petersburg, Russia) Е-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.  

1. He Y. (2021). An Overview of Acoustic Emission Inspection and Monitoring Technology in the Key Components of Renewable Energy Systems. Mechanical Systems and Signal Processing, Vol. 148.
2. Zhao L., Kang L., Yao S. (2019). Research and Application of Acoustic Emission Signal Processing Technology. IEEE Access, Vol. 7, pp. 984 – 993.
3. Stepanova L. N. (Ed.), Bekher S. A., Bobrov A. L. (2013). Fundamentals of non-destructive testing by acoustic emission. Novosibirsk: SGUPS. [in Russian language]
4. Bekher S. A. (2017). Methods for monitoring dynamically loaded rolling stock elements during repair and operation based on the integrated use of strain gauge and acoustic emission. Tomsk. [in Russian language]
5. Stepanova K. A. (2020). Development of a Method for Acoustic Emission Control of Defect Formation in the Process of Joint Formation by Friction Stir Welding. Saint Petersburg. [in Russian language]
6. Kuz'min A. N., Inozemtsev V. V., Prohorovskiy A. S. et al. (2018). Technology of non-threshold registration of acoustic emission data in the control of industrial facilities. Himicheskaya tekhnika, (3), pp. 10 – 17. [in Russian language]
7. Izmaylova E. V. (2013). Information-measuring system and pipeline control method based on wavelet filtering of acoustic emission signals. Kazan'. [in Russian language]
8. Kharrat M. А. (2016). A Signal Processing Approach for Enhanced Acoustic Emission Data Analysis in High Activity Systems: Application to Organic Matrix Composites. Mechanical Systems and Signal Processing, Vol. 70, pp. 1038 – 1055.
9. Il K. K., Hwan R. U., Pil C. B. (2018). An Appropriate Thresholding Method of Wavelet Denoising for Dropping Ambient Noise. International Journal of Wavelets, Multiresolution and Information Processing, Vol. 16.
10. Beale C., Niezrecki C., Inalpolat M. (2020). An Adaptive Wavelet Packet Denoising Algorithm for Enhanced Active Acoustic Damage Detection from Wind Turbine Blades. Mechanical Systems and Signal Processing, Vol. 142.
11. Barat V., Borodin Y., Kuzmin A. (2010). Intelligent AE Signal Filtering Methods. Journal of Acoustic Emission, Vol. 28, pp. 109 – 119.
12. Ferrando C., Juan L. (2021). A Novel Machine Learning-Based Methodology for Tool Wear Prediction Using Acoustic Emission Signals. Sensors, Vol. 21.
13. Barile C. (2020). Acoustic Emission Descriptors for the Mechanical Behavior of Selective Laser Melted Samples: An Innovative Approach. Mechanics of Materials, Vol. 148.
14. Makhutov N. A., Vasiliev I. E., Chernov D. V. et al. (2019). Influence of the passband of frequency filters on the parameters of acoustic emission pulses. Russian Journal of Nondestructive Testing, Vol. 55, pp. 173 – 180.
15. Ito K. (2021). Detection and Location of Microdefects During Selective Laser Melting by Wireless Acoustic Emission Measurement. Additive Manufacturing, Vol. 40.
16. Altay Y. A., Fedorov A. V., Stepanova K. A. (2022). Acoustic emission signal processing based on polynomial filtering method. Proceedings of the 2022 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, pp. 1320 – 1326.
17. Stepanova L. N., Ramazanov I. S., Kabanov S. I. (2007). Using Wavelet Filtering to Localize Acoustic Emission Signals. Kontrol'. Diagnostika, (9), pp. 27 – 31. [in Russian language]
18. Rakshit M., Das S. (2018). An Efficient ECG Denoising Methodology Using Empirical Mode Decomposition and Adaptive Switching Mean Filter. Biomedical Signal Processing and Control, Vol. 40, pp. 140 – 148.
19. Altay Y.A., Kremlev A. S. (2021). Signal-to-Noise Ratio and Mean Square Error Improving Algorithms Based on Newton Filters for Measurement ECG Data Processing. Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, pp. 1590 – 1595. Moscow.
20. Shchegol'skiy I. A. (2004). Synthesis of Recursive Digital Filters by Optimization Methods Based on Polynomial Approximation. Tomsk. [in Russian language]
21. Paarman L. D. (2001). Design and Analysis of Analog Filters: a Signal Processing Perspective. New-York: Kluwer Academic Publishers.
22. Egorov R. A. (2021). Development of algorithmic and software-hardware support for primary signal processing during dynamic indentation. Saint Petersburg. [in Russian language]
23. Matveev Yu. N., Simonchik K. K., Tropchenko A. Yu., Hitrov M. V. (2013). Digital signal processing. Saint Petersburg: SPbNIU ITMO. [in Russian language]
24. Richard L. G. (2006). Digital signal processing. Upper Saddle.
25. Salin V. N., Churilova E. Yu. (2002). Workshop on the course "Statistics". Moscow: Perspektiva. [in Russian language]

 

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