Abstract
The subject of the article are the methods of detection and recognition of explosive objects. The aim of the work is to develop the main provisions of the concept of guaranteed detection and recognition of explosive objects. The following tasks were solved in the article: an analysis of existing approaches to the use of traditional single and combined, as well as non-traditional (biological) methods of detecting explosive objects, development of a classification table of methods of detection of explosive objects according to physical principles, analysis of advantages and disadvantages of the considered methods of detection of explosive objects, development of comparative table methods of detecting explosive objects, formulation of the introductory provisions of the concept of guaranteed detection and recognition of explosive objects. The following methods are used – methods of comparison, methods of abstraction, methods of analysis and synthesis, methods of scientific induction. The following results were obtained – an analysis of the features of the existing traditional and non-traditional (biological) methods of detecting explosive objects was carried out. A classification of methods for detecting explosive objects is proposed, taking into account the parameters that affect the probability of detection and productivity. The results of a comparative analysis of explosive object detection methods are presented in tabular form according to the following indicators: type of interaction with explosive objects, platform type, potential productivity, information technology support, quality parameters, and economic indicators. The main provisions of guaranteed detection and recognition of explosive objects are formulated. Conclusions: the low productivity of the existing methods does not allow for quick and effective clearing of the territory contaminated by explosive objects, which leads to a large number of injuries and deaths of people due to the detonation of explosive objects. The use of individual detection methods alone cannot significantly increase the probability of detecting explosive objects. To increase the productivity and safety of the search and disposal of explosive objects, it is advisable to use unmanned intelligent platforms to deliver information and measurement tools.
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