21-01-2021 дата публикации
Номер: US20210016811A1
Принадлежит:
In order to locate points or lines of interest A, B, C, D on a railway track by means of a railway locating system comprising a linear camera and an odometer progressing on the railway track in a direction of progression the odometer repeatedly acquires instantaneous positioning data of the linear camera with respect to the railway track in the direction of progression and the linear camera pointing at the railway track repeatedly acquires instantaneous linear optical data along an instantaneous measurement line Then, by processing at least the instantaneous linear optical data and the instantaneous positioning data, a bitmap image is constructed of a zone of the surface of the railway track and, in the bitmap image, at least one spatial indexing marker of predetermined signature and its positioning relative to a reference rail A of the railway track is identified. Points or lines of interest A, B, C, D are identified in the bitmap image, and the coordinates of the points or lines of interest are determined in a two-dimensional locating reference system O, x, y linked to the spatial indexing marker and to the reference line A. 122122622281222100. Method for locating a railway track () , carried out by a railway locating system () comprising at least one linear camera () pointing at the railway track () and one or more odometers () , the railway locating system () progressing on the railway track () in a direction of progression () , the locating method comprising the following actions:{'b': 28', '12', '22', '100, 'repeatedly acquiring, with the odometer(s) (), progression data of the railway locating system () on the railway track () in the direction of progression (),'}{'b': 26', '22', '50, 'repeatedly acquiring, with the linear camera () pointing at the railway track (), instantaneous linear optical data along an instantaneous measurement line (),'}{'b': '22', 'by processing at least the instantaneous linear optical data, and if appropriate the progression data, ...
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