Transrapid - Shanghai

Siemens and Thyssen Krupp developed and installed the first commercial MagLev train system in Shanghai, China. The Transrapid started service in Shanghai, China in 2003 and utilizes magnetic levitation and linear synchronous motors to propel it on its track at speeds of up to 500 km/h (312 mph).

Imagine this scenario A train is flying along at 450 km/h (280 mph). The cooling system for one of the converters that supply the power springs a leak, resulting in a loss of power and damage to expensive components if not fixed immediately. Before the passengers are aware of the situation, the realtime diagnostic system alerts the service department of the problem and within minutes the service engineers are on their way to the converters 30km from the maintenance area with the required components and tools and repair the problem immediately. How is this possible? iTech - Remy’s artificial intelligence diagnostic system - is connected to Siemens’ monitoring system through which it receives error messages from the BIT (built-in-test) for over 120,000 components in real-time. iTech uses its diagnostic logic to interpret and make sense of all these messages and arrive at a root cause or an ambiguity group. Normally an engineer would have to read through all the error messages and try to make sense of the specific combination of errors to arrive at the root cause of the failure. However iTech does this automatically and within seconds purely by understanding the system logic and dependencies. iTech also has a learning capability and as the number of failures increases, it becomes faster at diagnosing faults. iTech can also be used as an off-line diagnostic and does not necessarily have to be embedded or connected to a system. It can be used as a troubleshooting guide for a field engineer on a PC or even over the internet on a mobile device. iTech makes use of statistical theory, probabilistic reasoning, dependency modeling and other techniques to optimize diagnostics and troubleshooting approaches thereby resulting in the following proven benefits: • 70-80% reduction of downtime • MTTD(Mean-Time-To-Diagnose) reductions of up to 97%. • Improved troubleshooting accuracy • Improved learning curves for technicians