ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 3 No. 1-2 (2018): TTTP - APEIRON

Manojlović N. PhD, Talijan D. PhD, Bajić B. MSc.

The Impact of the Efficiency of the System for Vibrations Damping on the Efficiency of Vehicle Braking

Original scientific paper

DOI: 10.7251/JTTTP1801026M

Abstract

This paper presents the plan and results of the research of the efficiency of the braking sys- tem depending on the condition of the shock absorbers and the velocity of the vehicle movement at the moment of braking. As expected, it has been proven that the braking efficiency decreases with decreasing efficiency of the system for damping vibrations. The interdependence of these two systems is also represented by a mathematical model that can serve for practical purposes in the analysis of traffic accidents.

Keywords : shock absorber, braking system, efficiency.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.