Bogie Monitoring Systems / 轉向架監測系統
The trains of the future need to be versatile and durable, which means that
facilitating repair planning is a direct way in which maintenance costs can be
reduced, all without sacrificing the ride safety and comfort. As such, it’s
important to monitor the health and usage of every component of a train car,
with the bogie being perhaps the most crucial out of them all.
Therefore, a bogie monitoring system is an essential component of the train’s
maintenance which makes sure that parameters such as the wear within the
bearings, shafts, brakes or wheels are identified and properly monitored in
order to efficiently schedule repair work, drive down maintenance costs and
prevent potential instabilities that might cause an accident.
The monitoring of Bogie Health & Rolling Stock Fatigue
A thorough monitoring of the crucial components within a bogie is essential for
ensuring that the train runs at full potential. A high-tech health monitoring
system based on MEMS sensors provides a steady feed of accurate readings even in
harsh environments, allowing train companies to constantly monitor the status of
the bogie and the health of the rolling stock so that they can effectively plan
out required maintenance work and, as a consequence, reduce maintenance costs.
The MEMS revolution
There are many sensing technologies (capacitive, piezoelectric, piezoresistive,
etc.) competing to provide the best solution for today’s bogie monitoring
systems, but none offer the same level of performance in terms of long-term
stability, temperature stability and precision as MEMS capacitive products,
which are not only qualified for safety critical applications, but are also
designed to operate in harsh environments and help drive down maintenance costs.
System architecture
The latest application for our MEMS sensors was the bogie monitoring system
designed and manufactured by Siemens Mobility. It uses 24 Colibrys sensors per
wagon, which operate under the harsh temperature and vibration conditions
specific to the bogie of a high-speed train in order to provide accurate
readings on the status of the bogie.
Advantages of our accelerometers
Our MEMS based accelerometers are stable and robust, characterized by low power
consumption, cost efficiency and the ability to operate successfully in harsh
environments. They are reliable solutions featuring a bulk micro-machined
silicon element, a low-power ASIC for signal conditioning and a temperature
sensor.
About Colibrys
We produce MEMS capacitive accelerometers renowned for high reliability under
harsh conditions, devices that have been successfully tested and implemented in
safety critical railway applications.
One of our most resonating achievements was the Colibrys sensors to be
successfully qualified for the latest generation of German ICE high speed
trains. The Velaro D train is the fourth generation of interoperable high-speed
trains made by Siemens using distributed traction and the first integrating
innovative bogie monitoring systems.
Colibrys accelerometers for bogie monitoring systems
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The new Colibrys VS1000 –
a new reference for low to medium frequency MEMS sensing (DC 0 Hz to 1500
Hz) – offers the best performance stability with shock resistance, as well
as the lowest non-linearity and noise in the marketplace. Each product is
fully tested and qualified to the highest Colibrys standards. It embeds a
self-test function for your confidence at all time.
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The legacy Colibrys VS9000 –
the trusted MEMS for the most demanding applications involving vibration
sensing since 2008 – it offers large frequency response and performance
stability, as well as low power consumption.
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MS9000 – the MS9000 family
encompasses extra-small accelerometers dedicated to inertial sensing
applications. Accelerometers in this family have an excellent long-term bias
stability and can operate under extreme shock, vibrations and temperature.
The full scale range of the accelerometers goes from ±1 to ±200g, but the 2g
range is excellent for the monitoring of bogie health and rolling stock
fatigue.
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