AI Metro – Delhi Metro Expands Smart Monitoring Across Key Rail Corridors
AI Metro – The Delhi Metro Rail Corporation (DMRC) has expanded the use of artificial intelligence-based monitoring systems across several of its corridors to detect faults in critical infrastructure before they affect train operations. The initiative covers components such as overhead electrical wires, train wheels, axle bearings and track circuits, with the aim of improving reliability and reducing service disruptions.
New systems support predictive maintenance
According to a DMRC official, the newly introduced technologies are being used on multiple metro lines as part of a broader move towards predictive maintenance. Instead of relying only on conventional inspections, the systems continuously collect and analyse operational data to identify potential problems at an early stage.
One of the key additions is an Overhead Wire System Health Monitoring solution that uses the Pantograph Collision Detection System (PCDS). The technology has been installed on the Red, Yellow and Blue lines to keep a close watch on the interaction between the pantograph and the overhead electrical wire.
Pantograph sensors monitor overhead wires
The PCDS uses accelerometers and drop-off sensors fitted to train pantographs. These devices monitor the contact between the pantograph, which draws electricity from the overhead system, and the wire while the train is running.
The information gathered by the system can help identify irregularities in wire alignment and other conditions that may require attention. Early detection of such issues can allow maintenance teams to investigate problems before they develop into operational faults.
AI cameras inspect overhead infrastructure
DMRC has also introduced AI-powered video monitoring for the overhead wire network on the Pink and Magenta lines. Under this system, cameras installed on trains capture footage of the infrastructure as trains travel along the route.
AI-based image analytics then processes the recorded images to identify and classify visible abnormalities in the overhead equipment. This provides maintenance personnel with an additional method of inspecting infrastructure over long stretches of track without depending solely on manual checks.
Laser technology checks train wheels
Another system introduced by the metro operator focuses on the condition of train wheels. An automatic wheel profile monitoring system has been deployed on the Pink Line, where high-precision laser sensors examine wheel profiles while trains remain in motion.
Regular monitoring of wheel condition is important for maintaining safe and dependable train operations. The automated system is designed to provide detailed measurements that can help maintenance teams identify changes in wheel condition and determine when further inspection may be necessary.
Bearing temperature monitoring added
DMRC has additionally deployed an Automatic Axle Bearing Temperature Monitoring System on the Pink and Magenta lines. The technology tracks the temperature of axle bearings during train movement.
Monitoring bearing temperatures can help identify unusual heat levels that may indicate a developing mechanical issue. Such information can support maintenance decisions and contribute to safer train operations by allowing potential problems to be examined at an earlier stage.
AI-based track circuit maintenance
The corporation has also introduced an AI-based predictive maintenance system for track circuits on the Green and Violet lines. Track circuits are an important part of railway signalling and help determine the occupancy status of sections of track.
By applying predictive technology to this infrastructure, DMRC is seeking to strengthen its ability to identify possible faults and maintenance requirements in advance. The latest systems form part of the corporation’s wider efforts to use technology for more efficient monitoring, maintenance planning and dependable metro services.