Abstract

The article presents abstract theorems and practical options for monitoring and regulating the technological process implementation of building a railway track object using artificial intelligence methods and tools. Railway construction as a complex dynamic system requires certain resources for its maintenance. Under these conditions, effective control over the construction work technology is of decisive importance. This can be achieved by improving the existing engineering and technical support system for railway construction through the introduction of an engineering and intellectual support subsystem for technological processes for railway facilities construction. One of the tasks of the subsystem is the effective use of automation tools with artificial intelligence elements. The deviations occurrence from planned requirements during construction work, due to the stochastic nature of railway construction, leads to violations of technology, an increase in labor costs, prime cost, an increase in duration, and as a result, a deterioration in the operational railway facility characteristics. To avoid such a development of events, a prompt review of the adopted technological solutions is necessary. To this end, within the scope of the methodology formation for engineering and intellectual support of railway construction technological processes, a system for monitoring and regulating work production has been developed. Intellectualization of monitoring the technological process implementation consists of the use of an expert system at the evaluation stage, built on a probabilistic inference model. The main purpose of the system is to process the monitoring results of the work progress during the railway track facility construction. The data obtained at the evaluation stage serve as the basis for predicting the implementation of the technological process. The essence of the forecast is based on the solution of general methodological issues of applying Markov processes. The regulation of the process implementation is based on the monitoring results. Adjusting the technological process to changing conditions of work provides flexibility in railway track facilities construction. This is achieved through rapid decision-making using the capabilities of an artificial neural network and subsequent adjustment of the work progress. Based on the theoretical study results, the article presents the practical aspects of monitoring and regulating the production of works in railway construction using intelligent technologies by the example of the construction of a flooded embankment section of a railway subgrade. The results presented in the article were obtained in the course of dissertation research carried out by the author.

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