Track damage and its evolution depend on the vehicle track interaction, and different vehicles have a different impact on the track. Track maintenance, to be effective, should be planned considering the impact of the vehicles running on that track. Modern maintenance procedure includes an inspection process that allows to define position and typology of the defects and to activate timely the appropriate corrective actions. Unfortunately, defects of different typology requires specific inspection procedures, and track monitoring is an important part of the maintenance costs; therefore, it cannot be performed continuously but must also be programmed to achieve a good compromise between cost of the inspections and efficiency of damage detection. A possibility to improve the monitoring process can be the use of a statistical approach to optimize the inspection scheduling on specific sections of the track depending on the frequency of defects detected in the past in that section of track. This method can be interesting because different sections of the track are subject to different track defects with different damage rate: for example, sections with narrow curve are subject to accelerated wear rate, and sections where the vehicle brakes or activates traction are subject to crack propagation. A statistical approach is efficient only if the activity along the considered sections is homogeneous during time and requires storing large amount of data and their computation. Data analysis can be difficult if it comes out from different inspection methods; those results are not immediately comparable. This work proposes a different approach to improve monitoring scheduling for track inspection, which allows considering the activity variation on that track. The idea is to create numerical models of the different vehicles that usually run on that track; those models, designed using multibody codes, are used to analyze the different impact of the vehicles on the different sections of the track. Because each vehicle typology usually has a specific mission profile on that track (velocity in each section), it can be assumed that the vehicles always brake and accelerate in the same point of the track. Under this assumption, it is possible to define for each vehicle type an “impact profile” for each section of the track, and the overall damage estimation can be performed by adding the contribute of each vehicle running on the track on the reference period. Of course, the most critical issue is to define the relationship between the “impact profile,” which represents the unitary damage contribution for the considered vehicle typology, and the damage level required to plan an inspection. This relationship can be refined only according to direct experience performed on the track, but once the relationship is defined, the system can be used automatically, and it is independent from number and vehicle typology because the effect of different vehicles is reported in terms of equivalent track damage.
|Titolo:||A Comprehensive Strategy to Estimate Track Condition and its Evolution|
|Data di pubblicazione:||2012|
|Digital Object Identifier (DOI):||10.4203/ijrt.1.2.1|
|Appare nelle tipologie:||1.1 Articolo in rivista|
File in questo prodotto: