Network Rail IT bosses plan to test a network of sensors
that will predict when rail equipment needs maintenance as part of
aprogramme to cut the company's costs by a fifth by
2014.
The project, which will be rolled out across the UK if it is
successful, will help the company replace defective parts before
they fail.
The company has pressed ahead with the scheme following
criticism in January by the Office of Rail Regulation (ORR) for
engineering delays over Christmas. The ORR has told the company it
must increase the percentage of trains that run on time from 90.6%
to 92.6% by 2014.
Network Rail plans to pilot the project, dubbed
intelligent infrastructure, on the Edinburgh to Glasgow line by
April next year.
Network Rail CIO Catherine Doran said, "We want to develop a
model that enables us to predict that a set of points, for example,
will need replacing or fixing in the next month. When an asset
fails, it causes disruption and late trains. We want to eliminate
that failure.
The company plans to install 250 senors to collect data on the
performance of equipment on the line. They will detect whether
points are opening and closing correctly, and measure temperature
of electronic equipment to detect overheating.
Network rail plans to collect the data by sending it to wireless
nodes on the track, or by collecting it from a wireless enabled
train.
It plans to analyse the data to identify patterns of behaviour
in equipment that fails. It will use these models to predict when
maintenance is needed and fix equipment before it breaks and causes
delays.
"I would hope we have some decent data to work with in the next
financial year, said Doran.
The company is selecting suppliers for measuring devices. It is
likely to start the pilot project in quarter three or four of the
current financial year.
How Network Rail plans to predict failure
before it happens
* Thermometers detect overheating in equipment
* Movement sensors detect if points are working correctly
* Sensors send signals to wireless nodes on the track
* Data is fed from the nodes to a fixed telecoms network, and
then into the data centre
* Software looks for patterns and builds models that can be used
to predict future failure.