Predictive analysis of the state of objects as a new strategy for the technical operation of electrified railways
Abstract
Predictive analysis of the state of objects as a new strategy for the technical operation of electrified railways
Incoming article date: 09.07.2021Stable reliability characteristics are a guarantee of non-emergency operation of electrified railways, undoubtedly, the profitability of transportation processes is growing. The article proposes an innovative method for determining the characteristics of reliability, with a decrease in the risk of failure or emergency. Electric traction used in most of the railroad landfill. It is necessary to consider the issues of reliability of the power supply system to predict the state of the system and study the patterns of interaction that affect system and non-system communications. Therefore, we will pay special attention to the reliability of the power supply system; in order to predict failures, first of all, it is necessary to know the patterns of interaction and patterns that affect system and non-system communications. The danger of risk directly depends on the number and duration of failures. In the power supply system, a huge number of heterogeneous and differently distributed objects, nodes and elements operate in different modes and are susceptible to different operational influences.Therefore, the work summarizes the existing methods of probabilistic forecasting, and gives recommendations on their application to solve the existing problematic of the issue. Further, the paper shows a method for determining the probability of failure of a constituent structural element of any, arbitrarily complex, stochastic system, to which the contact network of electrified railways belongs. In the conclusion of the work, an elementary method-oriented software tool with the functional purpose of automating statistical methods for solving problems of primary data processing and calculating elementary statistics in the process of risk management is proposed, as well as loading and maintaining a database that is subsequently oriented to the principles of machine learning.
Keywords: electrified railways, predictive analysis, operational reliability, probability of failure, forecasting