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EN
The process of railway track adjustment is a task which includes bringing, in geometrical terms, the actual track axis to the position ensuring safe and efficient traffic of rail vehicles. The initial calculation stage of this process is to determine approximately the limits of sections of different geometry, i.e. straight lines, arcs and transition curves. This allows to draw up a draft alignment design, which is subject to control the position relative to the current state. In practice, this type of a project rarely meets the requirements associated with the values of corrective alignments. Therefore, it becomes necessary to apply iterated correction of a solution in order to determine the final project, allowing to introduce minor corrections while maintaining the assumed parameters of the route. The degree of complexity of this process is defined by the quality of determining a preliminary draft alignment design. Delimitation of the sections for creation of creating such a design, is usually done by using the curvature diagram (InRail v8.7 Reference Guide [1], Jamka et al [2], Strach [3]), which is, however, sensitive to the misalignment of the track and measurement errors. In their paper Lenda and Strach [4] proposed a new method for creating curvature diagram, based on approximating spline function, theoretically allowing, inter alia, to reduce vulnerability to interference factors. In this study, the method to determine a preliminary draft alignment design for the track with severe overexploitation was used, and thus in the conditions adversely affecting the accuracy of the conducted readings. The results were compared to the ones obtained using classical curvature diagram. The obtained results indicate that the method allows to increase the readability of a curvature graph, which at considerable deregulation of a track takes an irregular shape, difficult to interpret. The method also favourably affects the accuracy of determining the initial parameters of the project, reducing the entire process of calculation.
PL
Opracowanie skupia się na metodach rozpoznawania geometrii odcinków trasy kolejowej, przeprowadzanego na potrzeby regulacji torów. Wymieniono metody klasyczne z opisem ich ograniczeń, zaproponowano również nowy algorytm, bazujący na skalowalnym wykresie krzywizn, tworzonym w oparciu o aproksymacyjne funkcje sklejane opisujące oś toru. Analizowany nowy typ wykresu różni się od stosowanego powszechnie wykresu krzywizn tym, że pozwala na zredukowanie wrażliwości na błędy pomiarowe i deformacje geometrii toru. Ułatwia także klasyfikowanie poszcze-gólnych odcinków krzywoliniowych tworzących regulowany tor.
EN
The study focuses on methods of recognition of the geometry of the railway sections, carried out for the adjustment of railway tracks. It is proposed a new algorithm, based on scalable curvature graph, created based on the approximating spline functions describing the axis of the track. The article presents the classical method of identifying the geometry, using angle graphs, cant graphs, curvature graphs, and the arrows of the arc graph (Fig. 1, 2, 3), discussing their characteristic features. Emphasis was put on the curvature graph, which allows accurate readings. However this graph is sensitive to measuring errors and deformations of track geometry, making it difficult to perform readings. In addition, although greater in comparison with other methods of precision, with his help differentiate segments of the small differences in curvature (segmental arcs) can raise doubts. To reduce these limitations proposed new way of creating a scalable curvature graph (chapter 3), which is determined to track described by the approximating spline functions with a given damping ratio distortion. In order to present the possibility of the method, constructed with the help of it curvature graphs for two independent sections of the track, comparing them to the classical curvature graphs (chapter 4). Towards them, the new method allows to reduce the sensitivity of the measurement errors and deformations of track geometry (Figures 8 and 9), facilitating the readings. It also increases the precision of the demarcation of segments of the small differences in curvature (Figures 10 and 11).
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