Using continuous data capture, Condition Monitoring is improving safety, reducing maintenance costs and lowering noise complaints for rail operators around the world. Here’s how.

By Frans Pienaar, Technical Sales Manager

 

The video above is pretty scary, especially when you think of how much damage was done before the tram eventually disconnected from the power source. The damage to the infrastructure was severe and it can be safely said that this route must have been closed for some time for repair. The extent of the damage could almost certainly have been prevented if the rail operator was using continuous Condition Monitoring.

When the pantograph was first damaged, the Condition Monitoring system would have detected the change in the data it received and alerted the relevant people to act (e.g. the driver would have stopped the train). Without a monitoring system in place, the cost and time to repair the infrastructure and the rolling stock increased exponentially as the train kept moving.

This is one reason why rail operators are increasingly turning to continuous Condition Monitoring solutions to measure the performance of their rail network and rolling stock fleet.

Noise & vibration: The core of Condition Monitoring

We all know that rail noise is a nuisance. Excessive rail noise, such as rail squeal and flanging noise, leads to complaints that must be investigated at cost to the operator. But more importantly, rail noise is an indicator of emerging rail damage – making it a reliable measure of the state of your rail system.

By constantly assessing noise and vibration across a rail network, Condition Monitoring systems can identify emerging issues early, enabling you to perform preventative maintenance before they become a problem. This gives you multiple benefits.

• Improved safety, with less likelihood of accidents and derailments
• Lower costs, as preventative maintenance is cheaper and less disruptive than rail replacement or intrusive maintenance, such as grinding
• Fewer noise complaints, as targeted friction management can reduce noise at identified noise hotspots

How does noise and vibration help identify rail damage?

Each type of rail damage has its own noise frequency. Combining noise and vibration data with infrastructure and vehicle characteristics, as well as operational parameters, allows you to not just spot issues, but also identify the root cause. As a result, proactive maintenance can be planned to repair an issue or stop it from developing further.

Note the values shown are typical but in practice you can get an overlap between squeal and flanging frequencies depending on other factors, such as wheel size and rail profile.

The limitations of annual or periodic data capture

Today, many rail operators rely on periodic data capture – mostly once a year or when needed due to complaints. But this data is only valid for the vehicle, location and operating conditions at the time of the check.

Even if you capture data every month for 8 hours, you’re only measuring 1% of available time across the year, which simply isn’t enough for root cause analysis. It’s unlikely to detect defects or damage effectively and can’t show degradation over time, making it little use for planning preventative maintenance.

On a rail network, changes can occur very quickly. So, you have to ask yourself: “What are the odds that my periodic noise and vibration measurements will be enough when doing root cause analysis and finding a solution?” (Answer: “Not good”.)

How rail operators can harness big data through continuous Condition Monitoring

This is why more and more rail operators are turning to continuous Condition Monitoring solutions. Using vibration and noise sensors, as well as optional cameras, continuous data can be gathered from the rail network, in all operating/weather conditions. The possible uses of this data are many.

• Identify emerging noise and vibration issues
• Identify the root cause, such as emerging corrugation or other defects
• Document trends and hotspots to enable proactive maintenance and mitigation
• Get real-time warnings if limits are exceeded

The light rail network operator in Utrecht the Netherlands has used continuous Condition Monitoring to reduce noise complaints by 42%. But the advantages go much further, as the following examples show.

Example 1: Using Condition Monitoring to identify hotspots and issues

The bar chart shows data from one section of the track. Here, there were over 1.5 million data points at the most common sound level, but there were also thousands of recorded data points at much higher levels (shown in red). The accuracy is good enough to tell you whether the noise is from the left or right rail.

To fix the issue, the operator could experiment with various Friction Management systems, and would immediately see if they were effective through continuous Condition Monitoring.

Example 2: Using Condition Monitoring to measure mitigating effects

These graphs show maximum and SEL (sound exposure level) noise at a point in the rail network above. In this case, noise was caused by corrugation, which required annual grinding. As an alternative, the network operator decided to try Top of Rail Friction Management and used continuous Condition Monitoring to analyse the results – both before and after.

As you can see, grinding had a strong effect, but was temporary. Through the use of Top of Rail Friction Management, however, recurring corrugation growth was almost eliminated. For further analysis, the same Condition Monitoring setup could be used to assess the performance of different Top of Rail Friction Control Materials, at no extra trial cost.

Example 3: Using Condition Monitoring to assess fleet performance

This simple graph shows noise or vibration levels in the vertical axis. The vehicle fleet numbers are shown in the horizontal axis, with low fleet numbers on the left and high fleet numbers on the right.

There are three separate vehicle types in this fleet and the vehicle numbers correspond. (One vehicle type has low numbers, another has middle numbers, and the last group has high numbers.) The vehicles with middle numbers clearly perform more poorly when it comes to noise levels. This may be related to maintenance cycles, but it’s more likely due to the vehicle type.

The information can be used by the train company when assessing which type of vehicles to buy or when planning maintenance/upgrades on the current fleet.

Big data and Condition Monitoring is the future

Big data capture is growing in every industry, not just rail, and the systems that capture this data are becoming more advanced – giving companies access to millions of data points every day. But data alone is not enough. You also need software and inhouse expertise to analyse and use that data in a meaningful way for your business.

At RS Clare, we work with market leaders in the Condition Monitoring field, who are developing and manufacturing monitoring equipment to extract useful data from across rail networks. Equally importantly, we understand the software and expertise required to help you make data-driven decisions that can reduce your costs and noise levels, and improve safety across your rail network.

If you’d like to know more or would like advice, get in touch.