Playing a vital role in the global economy, by providing a reliable and efficient transportation system for both passengers and goods, the safety of railroads is of utmost importance. Built up of thousands of miles of tracks and numerous moving components, it is crucial to identify potential safety hazards and prevent accidents.
The rail system in the UK is at the heart of driving the UK economy, the total rail industry expenditure for 2021-22 was £22.8 billion and provides more than 240,000 UK jobs. The UK is at the forefront of railway development with aims to make the railway system safer, more reliable and more punctual with the use of innovative solutions and a data-driven approach.
In recent years, data collection and analytics have emerged as powerful tools in the rail industry, enabling the identification of safety risks and the implementation of proactive measures. This article explores how data and analytics are revolutionising rail safety, from predictive maintenance to real-time monitoring.
Making the case for the use of data and analytics to drive rail safety, the Global Railway Review recognise that its use can help identify opportunities for safety improvements, increase operational efficiencies, enhance the ability to track operational metrics and ultimately strengthen reliability and delivery of service.
One of the key aspects of utilising data and analytics in rail safety is predictive maintenance. Traditionally, maintenance in the rail industry has followed a reactive approach, where repairs are made after a component fails or shows signs of degradation. This approach not only leads to higher maintenance costs but also increases the risk of accidents. By collecting data from various sensors and systems installed on trains and tracks, it becomes possible to identify patterns and predict failures before they occur.
For example, by analysing data collected from wheel sensors, maintenance crews can detect signs of excessive wear or wheel defects that may lead to derailments. By proactively addressing these issues, rail operators can prevent accidents and reduce downtime caused by unexpected failures. Predictive maintenance not only enhances safety but also improves the overall efficiency and reliability of rail operations.
Real-time monitoring is another critical aspect of data-driven rail safety. With advancements in sensor technology and the Internet of Things (IoT), it is now possible to monitor various aspects of rail systems in real-time. For instance, track conditions can be continuously monitored using sensors embedded in the rails. This allows operators to detect and address issues such as track misalignment, excessive vibrations or track defects promptly.
Real-time monitoring also extends to train operations. By collecting and analysing data from onboard systems, operators can identify deviations from normal operating parameters, such as abnormal speeds or braking patterns, which may indicate potential safety risks. Immediate alerts can be sent to train operators and maintenance crews, enabling them to take corrective actions and prevent accidents.
The power of data analytics lies in its ability to uncover hidden patterns and trends that might not be apparent through traditional methods. By analysing vast amounts of data, machine learning algorithms can identify correlations between various parameters and predict failures or safety hazards. These predictions allow rail operators to optimise maintenance schedules and focus their resources on the most critical areas.
Predictive analytics in rail safety has already showcased impressive success stories. For instance, a major railway operator in Europe implemented a data-driven predictive maintenance program for its rolling stock. By analysing historical maintenance records and sensor data, the company was able to identify specific components prone to failure and predict their remaining useful life accurately. As a result, the operator reduced unexpected failures by 50% and realised significant cost savings.
In another case, a railway network in Asia implemented a real-time monitoring system that analysed data from various sensors installed on tracks and trains. By detecting and analysing patterns related to track misalignment and excessive vibrations, the system alerted maintenance crews to potential safety risks. This proactive approach reduced the number of track-related incidents by 40%, enhancing both safety and operational efficiency.
RailSense is a leading provider of data-driven solutions for analysing track conditions and identifying safety risks in real-time. With RailSense’s advanced analytics platform, rail operators gain valuable insights into their infrastructure’s health, enabling them to make data-driven decisions for maintenance and safety improvements.
By harnessing the power of artificial intelligence and machine learning algorithms, RailSense empowers rail operators to proactively address safety hazards, minimise downtime and enhance overall rail system performance.
Data collection and analytics have revolutionised the way rail safety is identified and addressed. By leveraging real-time monitoring, predictive maintenance and optimised maintenance schedules, rail operators can proactively identify safety hazards and prevent accidents.
Success stories from around the world demonstrate the effectiveness of predictive analytics in enhancing rail safety. As rail transportation continues to evolve, it is crucial for operators to embrace data-driven solutions like RailSense to gain early insights into asset condition and ensure the utmost safety and efficiency in their operations.
RailSense products:
VoidSense®, a technology that senses voids and under-track movement. By continuously monitoring the stability of tracks, it helps identify potential track bed issues that could compromise rail safety.
With TempSense®, rail operators can track critical rail temperature (CRT) in real-time, allowing them to take necessary precautions in extreme weather conditions.
BuckleSense® is designed to detect possible hot-weather buckle occurrences, which can cause severe accidents if not addressed promptly.
GaugeSense® is a remote monitoring solution that measures changes in gauge and track geometry. By keeping a close eye on these parameters, rail operators can identify anomalies and take corrective measures to prevent accidents.
MultiSense® allows for multiple wireless sensor configurations over a wide area of rail, providing comprehensive coverage for enhanced safety monitoring.
TrackWater® is a groundbreaking solution that offers flooding alerts and monitors silt levels to ensure proper drainage. Flooding poses a significant threat to rail infrastructure, and timely alerts can help operators take necessary precautions and prevent damage.
By leveraging RailSense’s advanced technologies, rail operators can improve rail safety and enhance reliability, while reducing maintenance costs. Remote, real-time monitoring allows for early detection of potential issues, enabling proactive maintenance interventions. This approach minimises service disruptions, optimises asset longevity, and ultimately saves lives.
The importance of rail safety cannot be overstated. Protecting lives and valuable assets is a shared responsibility that requires a proactive approach to addressing the challenges faced by rail networks. By investing in innovative solutions and leveraging cutting-edge technologies like those offered by RailSense, rail operators can create a safer, more reliable transportation system that benefits everyone.
Source: https://dataportal.orr.gov.uk/media/2162/rail-industry-finance-uk-statistical-release-202122.pdf
Source: https://www.globalrailwayreview.com/article/97670/four-benefits-data-analytics-safety-modern-rail/