Improved method of processing the output parameters of the diesel locomotive engine for more efficient maintenance

Abstract

Modernization of aged rolling stock is one of the possibilities to adapt it to the current requirements for better environmental friendliness and economy of railway transport. However, some vehicle upgrades lead to new failures that were not observed in the original vehicles. The cause is the so-called “hybrid design”, built on a combination of original and selected new components. The aim of the work was to improve the situation with frequent failures and unavailability that occur on the modernized locomotive where a new diesel engine and new electronic control system was installed. Within the work, a simplified methodology for evaluating the outputs of diagnostic equipment was developped based on and applied to specific locomotive type and its diesel engine. The methodology resulted in a significant reduction of the time for assessing the condition of the vehicle’s diesel engine and more effective maintenance. The paper also presents other possibilities in the analysis of big data in the maintenance of rolling stock e.g. using fuzzy logic.