Application Of Image Processing To
Maintenance Of Signalling Facilities
Author(s)
N. Nagamine & M. Ukai
Abstract
Signalling facilities are important for ensuring safety and stability of train
operation, and, the maintenance of signalling facilities have direct relevance to
safe and stable train operation. Remote sensing and database management have
increased efficiency of maintenance of signalling facilities. Nevertheless, there
still remain many types of inspection work requiring human resources in
maintenance, such as the visual inspection of facilities, checking the visibility of
signals, in particular. These types of inspections still require a large amount of
human resources, are highly expensive, lacking in objectivity, and do not have
sufficient accuracy. Therefore, we have developed several inspection methods
for the maintenance of signalling facilities using image processing technologies,
in order to reduce the cost and increase inspection precision. As one example of
the developed methods, we have developed a visibility check method of
inspection for obstruction warning signals. The signals are important signalling
facilities used at level crossings. In addition, the light of the signal is turned off
in normal situations, and blinking in abnormal situations. Therefore, as for the
inspection of the signals they must be checked with respect to the direction of
light emission and conditions of the weeds around them. However, it is not
possible to check the visibility of such facilities during train operating hours,
because blinking the signal would require interruption of train service. In this
paper, we propose a method that employs near infrared LEDs, checking of the
visibility of the signals without the interruption of the train operation, and
tracking and detecting specific blinking of the signal correctly. Finally, we report
Keywords
image processing technologies, signalling facilities, obstructionwarning signal, level crossing, visibility check, near infrared LED
Related Book
Other papers in this volume
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