SBS Transit announces initiatives to improve reliability of train services
SBS Transit, a leading bus and rail operator in Singapore, has signed a Memorandum of Understanding (MOU) with the Taipei Rapid Transit Corporation (TRTC) and Metro Consulting Service Ltd (MCS) to strengthen its engineering and maintenance capabilities and improve the reliability of its train services. It has also invested in a number of predictive maintenance systems, which will be rolled out over the next few months.
SBS Transit operates the North East Line (NEL), Downtown Line (DTL) and the Sengkang Punggol LRT (Light Rail Transit) system in Singapore. TRTC oversees the Taipei Metro System and it has been operating metro systems for the past 23 years. MCS is a subsidiary of TRTC with 13 years of consultancy expertise in railway operations, maintenance and management. It has participated in rail consultation projects in Taiwan, China, Eastern Europe and Central Asia.
This MOU signed by SBS Transit Chief Executive Officer, Mr Gan Juay Kiat, President of TRTC, Mr B.C. Yen and President of MCS, Mr Ying-Chung Chuie, deepens the already existing strong ties between the parties. It enables the three organisations to leverage on each other’s competencies and experiences in operations and maintenance through mutual exchanges, study visits, training and the sharing of best practices.
It is aimed towards achieving SBS Transit’s 1,000,000 train-km Mean Kilometre Between Failures (MKBF) target. MKBF is a reliability measure used internationally in the rail industry. SBS Transit’s lines have operated at MKBFs of 663,000 train-km, 650,000 train-km and 115,000 car-km respectively in 2017.
Predictive Maintenance Monitoring Systems
SBS Transit has invested in Predictive Maintenance Monitoring Systems to identify and flag out component deterioration for rectification before they develop into a fault. The areas of focus include power, train and track as failures in their equipment are likely to affect passengers’ travel.
High Voltage Power Cable Partial Discharge Monitoring System
Power faults, which have significant impact on train operations, are now monitored via a system which continually scans the high voltage power cables for power discharge. The High Voltage Power Cable Partial Discharge monitoring system monitors and detects intense partial discharge activities in power cables, sending warning alerts to the maintenance team for follow up action before an actual fault occurs. It also able to detect and locate incipient faults to assist the team to quickly rectify the cable fault.
Dissolved Gas Analysis
Dissolved Gas Analysis detects any thermal or electrical fault by providing a real-time measurement of Hydrogen, Carbon Monoxide, Methane, Ethylene, Acetylene and moisture contents in insulating oil of the transformer.
Faults are identified according to the gas compositions as various types of faults emit gases of different levels. This system improves the reliability of the power intake transformers by diagnosing incipient faults before they lead to serious incidents and allows the engineers to protect the transformers in a cost-effective, reliable and continuous manner.
Automatic Track Inspection
As a first line of detection for track defects or faults, SBS Transit has successfully tested and commissioned the Automatic Track Inspection (ATI) system on the DTL with the Land Transport Authority (LTA) last year.
Using cameras, lasers and sensors, the ATI system is able to instantly detect any track anomalies such as cracks, missing fasteners, wheel burns, corrugation and third rail sag. Alerts are sent to keep key personnel informed so that the issue can be rectified promptly.
Systems to be rolled out with funding support from LTA
Over the next few months, these systems will be rolled out with funding support from LTA. The Diagnostic Expert System, which synchronises all the train system logs for analysis, plotting all data into a single timeline and using pre-defined parameters, will flag out anomalies in the various system components such as brakes and propulsion of the train and highlight the probable root cause based on the analysis of the data.
“We are working hard to achieve the 1,000,000 train-km MKBF for NEL and DTL and will keep pushing ourselves to doing better to improve train reliability,” said Mr Gan.