An optical‐electronic laser complex for the standoff detection of traces of explosives was developed with using of the Active Spectral Imaging. The tuning and automatization of the developed complex were performed. Experimental researches in detection of traces of various types of explosives on different substrates were carried out. On average, the probability of detection was 89 % and the probability of identification was 91 %.
В работе предлагаются два новых эффективных алгоритма, реализованных коротким программным кодом в MS Excel, предназначенных для идентификации и характеризации размеров нано– и микропорошков частиц в виде обобщенного гамма или логнормального распределений по данным опытных гистограмм. Предлагаемый метод представляет собой новый и достаточно общий подход к решению обратных задач идентификации параметров дифференциальных функций распределения по экспериментальным данным на основе на минимизации функционала, представляющего собой коэффициент детерминации.Алгоритм реализован формулами (менее 10) наиболее распространенного инструментария (электронных таблиц MS Excel без использования макросов), позволяющего исследователям, не обладающими навыками профессиональных программистов, простоту проверки и воспроизведения представленного материала, а также возможность модификации кода для решения более широкого круга задач. Текст статьи и комментарии на рабочих листах скриншотов представляют собой готовые инструкции по решению задач идентификация функций распределения и характеризации размеров нано– и микропорошков. The paper proposes two new efficient algorithms, implemented by a short program code in MS Excel, designed to identify and characterize the sizes of nano- and micropowders of particles in the form of generalized gamma or lognormal distributions according to experimental histograms. The proposed method is a new general approach to solving inverse problems of identifying the parameters of differential distribution functions from experimental data based on minimizing the functional that is the coefficient of determination.The algorithm is implemented with formulas (less than 10) of the most common tools (MS Excel spreadsheets without the use of macros), which allow researchers without the skills of professional programmers to easily check and reproduce the presented material, as well as the ability to modify the code to solve a wider range of problems. The text of the article and comments on the worksheets of screenshots represent ready-made instructions for solving problems of identification of distribution functions and characterization of the sizes of nano- and micropowders.
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