EKE-Electronics, in collaboration with VR FleetCare, have developed a unique solution that uses sensor data from in-service rolling stock to provide real-time monitoring of the condition of track and track assets.
SmartVision™ Track Condition Monitoring measures the smoothness of ride experienced by a normal in-service train passing in full load and with full speed over the track. These frequent measurements complement less frequently produced track geometry measurements from measurement trains. Sudden and quickly developing problems, such as broken rails or damage caused by wheel slip are detected. Early detection can result in a cheaper cost of repair and reduces the risk of secondary damage.
A key enabler for the condition monitoring of track assets is the SmartVision™ Rail Asset Database. This records the type and location of track assets so that the degradation of the asset’s condition can be followed. The user receives notifications of critical changes so that the correct action can be taken in the correct location at the correct time.
Field validation tests have been performed with our collaboration partner, VR FleetCare, to locate track irregularities, detect faulty insulation joints, monitor switch health and identify hunting.
We have an open data policy giving you access to the measured data via the SmartVision™ user interface.
The SmartVision™ Rail Asset Database is a key enabler for the condition monitoring of track assets. This records the type and location of track assets so that the degradation of the asset’s condition can be followed. The user receives notifications of critical changes so that the correct action can be taken in the correct location at the correct time.
The information required for the SmartVision™ Rail Asset Database can be taken from either:
SmartVision™ Track Condition Monitoring’s easy-to-use web-based user interface turns data into actionable information to make informed business decision about when to perform maintenance based on the condition of your track and track assets. Our system allows you to view the status of your whole network in one place. SmartVision™ Track Condition Monitoring increases line availability, helps avoiding unexpected faults and enables transition towards condition-based maintenance.
Our open data policy gives you access to the measured data via the SmartVision™ user interface. Users can download this data to enable further analysis using your own tools.
SmartVision™ is accessible via a standard web browser. EKE recommends performing user authentication via integration into the operator’s single sign-on environment.
The SmartVision™ Track Condition Monitoring the vibration generated by the track and generates a number of condition indicators that detect changes related to degradation within the track and for track assets.
Some examples of where the monitoring system has been given indications of rail defects are:
Data collection is performed by Televic Rail’s industry leading COSAMIRA sensor gateway, equipped with signal processing software developed by EKE. It contains a central configurable processing and storage unit, and inertial measurement sensors.
The sensor gateway is installed on one bogie and performs continuous measurement of the track and movements of the bogie. It sends data of detected anomalies, as well as from defined track elements, to the SmartVision™ cloud via wireless data transmission for further analysis.
The SmartVision™ Track Condition Monitoring system is made up of a standard configuration of:
We have a number of underground position solutions available.
|SmartVision™ Track Condition Monitoring||Measurement Train||Optical and Laser Measurement|
|Data Collection Frequency||*****||**||***|
|Suitable for winter conditions with snow & ice||*****||****||**|
|Detecting track support and ballast problems||*****||*****||**|
|Detecting track sections causing hunting of trains||*****||*||**|
|Detecting corrugation on rail surface||*****||****||**|
|Response of track to passing train||*****||***||**|
|Measuring geometry of track||**||*****||****|
|Detecting obstacles around track||*||**||*****|
Source: EKE’s internal analysis