DEVELOPMENT OF A SOFTWARE PLATFORM FOR COMPUTER MODELING, ANALYSIS AND VERIFICATION OF SPECTROMETRIC SIGNALS
DOI:
https://doi.org/10.32689/maup.it.2025.3.20Keywords:
computer analysis of spectrometric signals, software platform, computer modeling, recognition algorithms, computer system, data visualization, verification algorithmsAbstract
Purpose of the work. The article is devoted to the development of a software platform that allows for the comprehensive study and use of methods of computer analysis of digitized spectrometric signals. The functionality of the developed software application includes modeling of digital signal images with fully known, adjustable parameters, computer data processing using existing or newly developed analysis methods, as well as software verification and visualization of the results of such methods. In addition, the program supports the ability to load data obtained during real experiments and their further analysis to construct spectra. Methodology. The article provides a detailed description of the capabilities of the software platform and its internal architecture. The functionality and graphical interface of the program are created using methods and technologies of software development in the C++ programming language based on the QT framework. This framework is cross-platform, allowing you to compile and run the developed application on different operating systems, such as Windows and Linux. Mathematical and computer modeling methods are used to generate digital images of spectrometric signals. In the process of computer data analysis, digital signal processing methods, methods and algorithms for intelligent analysis of large data sets are used. At the end, a comparative analysis of the results of several existing and new computer analysis methods obtained using the created software is presented.Scientific novelty. For the first time, a platform (software tool) has been developed that provides the ability tocomprehensively study the accuracy and speed of both known and newly developed methods of computer analysis ofspectrometric signal parameters. Clear criteria for assessing the accuracy of work (the concept of verified accuracy) of a particular computer processing method on simulated data, which is verified using a software-implemented verificationalgorithm, have been introduced.Conclusions. The software application created during the research allows for computer modeling of a spectrometric signalwith specified, adjustable parameters, as well as analysis of simulated or loaded from real experiments data using software-implemented existing and proposed computer processing methods. The results of the study show that the program allows you to calculate and compare the main metrics of the work of computer analysis methods, such as data processing speed and accuracy of recognition of the main pulse parameters, as well as visualize the results. In the future, the platform’s functionality can be expanded by adding support for a larger number of computer analysis methods, which will allow for better research into the effectiveness of both known and new methods of computer processing of spectrometric signals.
References
Грабовський В. А. Прикладна спектрометрія йонізуючих випромінювань: Навчальний посібник. Видавни- чий центр ЛНУ імені Івана Франка. 2008. 296 с.
Рева С. М., Циблієв Д. О. Комп’ютерне моделювання спектрометричних сигналів з підвищеною деталізацією. Вісник Харківського національного університету імені В. Н. Каразіна, серія «Математичне моделювання. Інформаційні технології. Автоматизовані системи управління». 2024. Том 65. С. 64–73. https://doi.org/10.26565/2304-6201-2025-65-06
Рева С. М., Циблієв Д. О. Математичні моделі та алгоритми комп’ютерного моделювання спектрометричних сигналів. Вісник Харківського національного університету імені В.Н. Каразіна, сер. «Математичне моделювання. Інформаційні технології. Автоматизовані системи управління». 2023. Том 58. С.64–74. URL: https://periodicals.karazin.ua/mia/article/view/23502
Averill M. Law, W. David Kelton. Simulation Modeling and Analysis. Third edition. McGraw-Hill. 2000. 760 pages.
Khilkevitch E. M., Shevelev A. E., Chugunov I. N., Iliasova M. V., Doinikov, D. N., Gin D. B. et al. Advanced algorithms for signal processing scintillation gamma ray detectors at high counting rates. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2020. Volume 977, 164309. URL: https://doi.org/10.1016/j.nima.2020.164309
Knoll G. F. Radiation Detection and Measurement. John Wiley & Sons. 2010. 864 pages.
Lopatin M., Moskovitch N., Trigano T., Sepulcre Y. Pileup attenuation for spectroscopic signals using a sparse reconstruction. IEEE 27th Convention of Electrical and Electronics Engineers in Israel. 2012. P. 1–5. URL: https://doi.org/10.1109/eeei.2012.6377045
QT Framework Official Website. URL: https://www.qt.io/product/framework
Reva S. M., Tsybliyev D. O. Computer methods of recognition and analysis of X-ray and gamma radiation parameters. Bulletin of V. N. Karazin Kharkiv National University, series “Mathematical modeling. Information technology. Automated control systems”. 2022. Volume 55, pp.38–48. URL: https://periodicals.karazin.ua/mia/article/view/22593
Reva S. M., Tsybliyev D. O. Devising a computer method to recognize and analyze spectrometric signals parameters. Eastern-European Journal of Enterprise Technologies. 2024. 6(9 (132)), 86–96. URL: https://doi.org/10.15587/1729-4061.2024.318558
Shevelev A. E., Khilkevitch E. M., Lashkul S. I., Rozhdestvensky V. V., Altukhov A. B., Chugunov I. N. et al. High performance gamma-ray spectrometer for runaway electron studies on the FT-2 tokamak. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2016. Volume 830, pp. 102–108. URL: https://doi.org/10.1016/j.nima.2016.05.075
Wolszczak W., Dorenbos P. Time-resolved gamma spectroscopy of single events. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2018. Volume 886, pp. 30–35. URL: https://doi.org/10.1016/j.nima.2017.12.080






