DETERMINATION OF FLAW DETECTOR IMPULSE RESPONSE TO ACHIEVE SUPERRESOLUTION OF REFLECTOR IMAGES FROM ECHO SIGNALS MEASURED BY ANTENNA ARRAY
- Authors: Bazulin E.G.1, Krylovich A.A.2
-
Affiliations:
- ECHO+ Research and Production Center LLC
- Moscow Power Engineering Institute
- Issue: No 8 (2025)
- Pages: 3-15
- Section: Acoustic methods
- URL: https://bakhtiniada.ru/0130-3082/article/view/294346
- DOI: https://doi.org/10.31857/S0130308225080019
- ID: 294346
Cite item
Abstract
In ultrasonic inspection, digital aperture focusing (DAF) is increasingly being used to reconstruct reflector images. The reliability of inspection is determined by the quality of the DFA image — signal-to-noise ratio, ability to reconstruct the image of the entire reflector boundary, and resolution. Various methods are used to achieve super-resolution of echoes: maximum entropy method, methods of building autoregressive signal models, compressive sensing (CS) method, etc. To use these methods, it is important to know the impulse response of the ultrasound system, which can be measured or obtained using “blind” deconvolution methods used in image and signal processing. In this paper we consider the Minimum Entropy Deconvolution (MED) method for estimating the impulse response of an ultrasonic flaw detector and achieving the effect of image super-resolution, where knowledge of the transfer function of the system is critical. The effectiveness of the proposed method is confirmed by the results of model experiments
About the authors
Evgeny Gennadievich Bazulin
ECHO+ Research and Production Center LLC
Author for correspondence.
Email: bazulin@echoplus.ru
Russian Federation, 123458 Moscow, Tvardovskiy str., 8, Strogino Technopark
Anna Andreevna Krylovich
Moscow Power Engineering Institute
Email: KrylovichAA@mpei.ru
Russian Federation, 111250 Moscow, Krasnokazarmennaya str., 14
References
- Bazulin E.G. Comparison of Systems for Ultrasonic Nondestructive Testing Using Antenna Arrays or Phased Arrays // Defectoskopiya. 2013. No. 7. P. 51—75.
- Bazulin A.E., Bazulin E.G. Deconvolution of Complex Echo Signals by the Maximum Entropy Method in Ultrasonic Nondestructive Testing // Akusticheskii Zhurnal. 2009. No. 6. P. 772—783.
- Marple Jr. S.L. Digital Spectral Analysis. Moscow: Mir., 1990. 584 p. (In Russian, translated from English).
- Box G.E., Jenkins G.M. Time serial analysis. Forecasting and control. San-Francisco: Holden-dey, 1970. 553 p.
- Bazulin E.G. Processing of TOFD Echo Signals for Superresolution Achievement // Defectoskopiya. 2021. No. 5. P. 13—21.
- Granichin O.N. Randomization of Measurements and l1-Optimization // Stochastic Optimization in Informatics. 2009. No. 5. P. 3—23.
- Bazulin E.G. Application of Recognition with Compression Method for Superresolution in Echo Signals // Defectoskopiya. 2022. No. 5. P. 24—36.
- Boget B.P., Healy M.J.R., Tukey J.W. The Quefrency Alanysis of Time Series for Echoes: Cepstrum, Pseudo-Autocovariance, Cross-cepstrum and Saphe Cracking / Proceedings of Symposium on Time Series Analysis by Rosenblatt. M., 1963. P. 209—243.
- Randall R.B. A history of cepstrum analysis and its application to mechanical problems // Mechanical Systems and Signal Processing. 2017. V. 97. P. 3—19.
- Bazulin E.G., Krylovich A.A. Cepstral Analysis of Ultrasonic Echo Signals Measured with an Antenna Array for Superresolution Imaging of Reflectors // Defectoskopiya. 2025. No. 4. P. 3—15.
- Wiggins R. A. Minimum entropy deconvolution // Geoexploration. 1978. V. 16. № 1—2. P. 21—35.
- Rabinovich E.V. Signal Processing Methods and Tools / Textbook. Novosibirsk: NSTU Publishing House, 2009.144 p. (In Russian).
- McDonald G.L., Qing Zhao. Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection // Mechanical Systems and Signal Processing. 2017. V. 82. P. 461—477.
- Cabrelli C. A. Minimum entropy deconvolution and simplicity: A noniterative algorithm // Geophysics. 1985. V. 50. No. 3. P. 394—413.
- Li T., Kou Z., Wu J., Yahya W., Villecco F. Multipoint optimal minimum entropy deconvolution adjusted for automatic fault diagnosis of hoist bearing // Shock and Vibration. 2021. V. 2021. No. 1. P. 1—15. DOI: doi: 10.1155/2021/6614633
- McDonald G.L., Zhao Q., Zuo M.J. Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection // Mechanical Systems and Signal Processing. 2012. V. 33. P. 237—255.
- Echo+ Company Official Website. URL: https://echoplus.ru (accessed: 25.05.2025).
- Shristi Mishra, Deepika Sharma. A review on curvelets and its applications / In: Raju Pal and Praveen Kumar Shukla (eds). SCRS Conference Proceedings on Intelligent Systems, SCRS, India, 2022. P. 213—220. doi: 10.52458/978-93-91842-08-6-20
- Naghizadeh M., Innanen K.A. Seismic data interpolation using a fast generalized Fourier transform // Geophysics. 2011. V. 76. doi: 10.1190/1.3511525
Supplementary files
