The Stockholm metro is one of the most heavily trafficked rail systems in Sweden. With high demands on safety, reliability, and minimal noise, SL has long worked to improve track quality. Initially, SL sought a solution to monitor noise levels and identify infrastructure-related factors influencing the acoustic environment in the metro system.

In 2017, QTMS (Quiet Track Monitoring System) was installed on seven metro trains as part of this effort. QTMS is a vehicle-based track monitoring system that continuously collects data on noise, vibrations, and irregularities. The initial focus was on noise emissions, but over time, the project's scope has gradually expanded to include broader applications of the data for improved maintenance and infrastructure planning.

Challenge

Traditional inspections of track conditions have been conducted manually or using dedicated measuring vehicles, which limits data collection. This made it difficult to detect trends or predict maintenance needs in time. SL needed a solution that could provide continuous and detailed decision-making support for more efficient action planning.

Solution

Through QTMS, SL gained access to continuous and automated data collection from trains in regular service. Initially, the following noise-related parameters were analyzed:

Rail corrugation – Irregularities that affect noise levels and ride comfort.

Grinding patterns – Marks left by rail grinding that can influence noise and wear.

Impacts and shocks – Irregularities that generate sharp noise peaks.

Slippery track areas – Often referred to as leaf contamination.

Wear in curves – Rapid material loss in the contact between wheel and rail.

As the project progressed, the focus shifted from environmental impact to include more aspects of track maintenance, such as:

Track geometry – Continuous monitoring of shifts to detect settlements and deformations.

Pumping track – Identifying vertical displacements that can cause irregularities and deteriorate track alignment.

Severe wear – Detection of wear patterns and surface damage on the rail.

In addition to data collection, SL and Tyréns have worked together to develop more accessible and user-friendly visualizations and reports to simplify interpretation and maintenance planning.

Results

After eight years of operation, QTMS has contributed significantly to SL's maintenance efforts with both insights and concrete improvements:

Improved decision-making – SL has gained a more detailed and comprehensive understanding of track conditions.

From reactive to proactive maintenance – Earlier detection of problems has enabled faster interventions and reduced the need for emergency repairs.

More effective noise reduction – SL has been able to identify and verify complaints and trace the source of elevated noise levels.

Extended track life – Data from QTMS has been used to plan where rail grinding is needed, leading to long-term cost savings and extended infrastructure lifespan.

Lessons Learned

Automated reports and visualizations are needed – To support day-to-day use of the data in operations.

Internal alignment is crucial – Clearer guidelines and goals can help more people within SL benefit from the insights.

Standardization facilitates implementation – Using standardized metrics makes it easier to integrate QTMS data into maintenance planning.

The Future

With eight years of collected data and a steadily growing application of QTMS, SL now has the opportunity to take the next step toward fully data-driven, predictive maintenance of its infrastructure.

Summary

The collaboration between SL and Tyréns has evolved from an initial focus on environmental impact to a broader application in track maintenance. QTMS has proven to be a valuable solution for monitoring track conditions and laying the groundwork for more proactive and data-driven maintenance. By building on the insights generated through QTMS, SL can continue developing a modern, efficient, and sustainable metro system.

SL