Fault Detection in a Mechatronic Switch

Our latest work on fault detection in a mechatronic switch has been published in the Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. The title of the paper is “Fault-tolerant control for sensor faults affecting an electromechanical railway track switch” and is freely available to read and download. We did this work as part of the REPOINT project.

Paper Overview (TL;DR)

We used Kalman filters and residuals to determine whether there was a problem with the REPOINT mechatronic switch for railways. After prototyping this in simulation, we found that it worked. Then, we applied this to a scale model of a mechatronic switch to check if it worked there too. And it did!


Most railway switches (or points) are purely mechanical and use super-old technology to switch between tracks. This would be fine, except that they are the #1 cause of delay minutes on the UK rail network! The REPOINT project aimed to reduce these failures by replacing these with mechatronic switches that had in-built sensors and which were easily lineside replaceable.

But, it wasn’t clear how these mechatronic switches would deal with a sensor failure. Or how it might recover from one.

overview of the mechatronic switch, showing where faults can be introduced.
An overview of the mechatronic switch, showing where the faults could occur.

Mechatronic Switch Simulation

We focussed on disconnect failures, where one of the signals (either position or velocity) was disconnected from the controller. To see what effect this would have, we first built a software simulation of the mechatronic switch.

A figure showing the layout of the mechatronic switch simulation, and the location of the Kalman filters and sensors.
An overview of the fault detection system for the mechatronic switch

Then, we used the Kalman filters to estimate what the states of the system should have been. In the figure below, you can see that the signal from the sensor (in blue dashes) drops to zero, but the filter’s estimate of the signal (in red) tracks correctly. That’s pretty cool!

figure showing the results of a simulation test of the switch. The test shows that the 'accommodated signal' generated by the Kalman filter responds correctly even if the sensor is disconnected.
Showing how the Kalman filter estimate (red in top axes) continues to track the motion of the system even when the position sensor (blue dashes in top axes) is turned off.

The Real Deal
(AKA: The Real Mechatronic Switch)

Then, we took this scheme and applied it to our small-scale model of the REPOINT switch:

A figure showing the small-scale model of the REPOINT mechatronic switch. It shows the experimental setup and relevant sensors.
Overview of the small-scale model of the REPOINT switch

Long story short – it worked! When we used some logic to determine when to trust the Kalman filters over the sensor signals, the system was able to continue to work when the position or velocity sensors were disconnected. (This approach uses thresholding of the residuals – more information is available in the paper.)

Showing the results of applying the fault detection algorithm to the physical model of the switch. It shows that the Kalman filter correctly 'fills in the blanks' when the sensor is switched off.
Showing the response of the physical model, and the ability of the Kalman filters to correctly estimate the mechatronic switch’s position.


It worked! Using Kalman filters and residual logic, we were able to ensure the switch could continue working even if one of the sensors failed. Pretty neat eh!

Acknowledgements to Dr Precious Kaijuka Mwongera who did the experimental work for this paper!

You can read the whole paper online, for free if you want more information.

If you want more information on my recent papers, you can check out the summary of our work on torque ripple control and systems engineering for waste management.

By Will

Senior Lecturer in mechatronics and control systems engineering at Loughborough University.