Kistler launches next-generation Rail Weigh In Motion system

Winterthur, August 2021 – As the outcome of an intensive test phase that also included physical modeling, Kistler now offers a completely redesigned Weigh In Motion (WIM) system for rail applications. Simple and fast to install – with only minimal track closures required, or none at all – the new solution delivers multiple parameters of passing rail vehicles based on integrated calculation of accurate piezoelectric force measurements.

With over a million kilometers of rail track installed throughout the world, monitoring of rail traffic is a challenge that cannot be underestimated. Soaring traffic volumes on roads as well as railways are generating unprecedented demand for automatic systems such as those used to monitor freight trains. Based on decades of experience and success with its WIM solutions for roads, Kistler has now launched the redesigned Rail WIM system 9192B – covering a wide range of possible applications:

  • Bridge and infrastructure protection (overload, dynamic impact, wheel defects)
  • Fraud and theft protection (car number, presence and weight verification)
  • Derailment protection (imbalances, axle distance/parallelism)
  • Track and train monitoring (traffic data collection, e.g. speed, braking capacity, spacing)
  • Condition of rolling stock (flat spots, bogie twist)
Kistler rail technology uses Kistler sensors to enhance safety and help guarentee availability in rail transport applications
The new Rail Weigh In Motion system 9192B from Kistler enables efficient freight train monitoring, delivering a wide range of train characteristics over the long term.

Automatic collection of comprehensive train data

The new solution comes with a piezoelectric force sensor 9008B that was optimized with the help of a validated simulation model – so the design is even more robust than before, and the manufacturing process has been greatly improved. The new sensor layout consists of 12 sensors in six pairs. Data acquisition and processing take place in a cabinet near the sensor installation site: Kistler provides the complete backpanel for the WIM system as well as the web interface for data visualization.

Powered by highly accurate sensor technology and sophisticated electronics, the new Kistler Rail WIM system 9192B delivers precise measurements of a wide range of train characteristics: weight (wheel, axle, bogie, vehicle and train load) as well as additional data (train speed, number and type of cars, lateral vehicle imbalance rate, and longitudinal vehicle imbalance rate). The solution is virtually maintenance-free thanks to advanced self-monitoring features. And the list of customer benefits goes on:

  • No sensor fatigue, no ageing of the sensor integration
  • No temperature dependency (in the range from ‒40 to +60°C)
  • Long-term stability and minimized influence of vehicle dynamics
  • Very high sensitivity and wide measuring range (from empty wagons to heavy mine cars)
  • Advanced functions such as flat spot detection and system self-diagnostics

Universal application, low maintenance effort

Before installing a system, it is advisable to measure and analyze the track – usually with the help of a system integrator. This procedure will determine the best sensor layout for maximum WIM performance with accuracy of ±2% GVW. The new Rail Weigh In Motion system from Kistler covers a measuring range of 2 to 25 t per wheel, while train speeds can vary between 5 and 200 km/h. With a temperature range from ‒40 up to +60°C, the WIM solution 9192B is ready for operation in almost all climates on every continent.

A calibration campaign is needed to ensure that every WIM system user benefits from the highest standards of operational excellence. Ideally, this should include selected cars with adjusted bogies that are measured both statically and at different speeds. Depending on the availability of cars, the quality and accuracy of the initial calibration will optimize overall WIM performance. 

To find out more about the new solution from Kistler, visit our page.