New Opportunities in Data Management for Railway Infrastructure Companies
10.05.2021 | Increasing dynamics in the development of technologies, use of IoT, new measurement methods, sensor technology and the performance of innovative service providers is rapidly increasing the range of usable information sources in the field of railway infrastructure.
Railway infrastructure companies are offered completely new opportunities to obtain a significantly improved and continuously updated overall view of the condition of the infrastructure and to be able to predict its development. They can have such opportunities thanks to an increasing number of data obtained from measurement runs, inspections, and possibly also regular runs and repairs. Comprehensive analyses and forecasts can be used. It is a particular challenge to ensure a consistent database, when integrating extended condition/measurement data into existing systems. Some infrastructure service providers offer their own solutions for storage, visualisation and evaluation of their recorded data, which, as isolated solutions, make overall analyses much more difficult.
Big Data in Infrastructure Management
ZEDAS GmbH offers with zedas®asset infrastructure operators and owners the opportunity to connect innovative measurement service providers with new measurement methods, devices and sensors, and to combine and correlate obtained data. This offers the great advantage of being able to easily test, evaluate and, if necessary, integrate new procedures. The opportunities of the rapidly advancing digitalisation become usable.
Digitisation of the Railway Infrastructure
The overall view of the railway infrastructure requires the integration of all essential components, such as tracks, switches, stops, catenary wire, tunnels, control and safety technology and traction power systems. Via standard interfaces, infrastructure object data can be easily and quickly imported and automatically positioned and visualised in map systems. Condition information and measured values are graphically displayed in relation to the exact location and are kept in their history for further evaluations.
Weak Point Analysis: Predictive Maintenance thanks to clever Data Management
A comparison of current measurement series with measurement data from the past identifies deviations as well as their change rate; track sectionsor objects/components that require a more detailed examination or which have already reached a critical state become visible. Considering the expected load, it is for example possible to predict the object condition. Based on this knowledge, predictive maintenance strategies can be mapped.