Abstract
Examination of the technical condition of capital construction objects is a key task for management companies, organizations that ensure the proper functioning of objects and executive authorities - the balance holders of most of the social infrastructure of cities. The boundary state of an object, corresponding to critical changes in the structure forming the contour of its structural safety and functional reliability, is detected and diagnosed by a number of external signs (defects), the quantitative assessment and qualitative interpretation of which determine both the general results of the object examination and specific structural and technological measures to ensure its continued safe operation. Associated with a large number of field and desk studies conducted in conditions that adversely affect the quality of the result, organizational difficulties in archiving, documenting and dynamic analysis of the identified defects in buildings make the examination process expensive, inefficient and irrational in the overall content balance of the object. An effective and promising solution to the problem of reducing the resource intensity of the production of examinations of buildings in terms of diagnostics and defects and the formation of the foundations for further advising analytics, which greatly simplifies the choice of the best and economically rational management decisions in the technical operation of buildings, is proposed on the basis of the introduction of elements of neural network analysis and information modeling into expert activities. . The authors propose separate provisions for the intellectualization of building flaw detection, which are implemented and tested at the objects of ongoing construction and technical expertise in the region
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More From: Bulletin of Belgorod State Technological University named after. V. G. Shukhov
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