Multi-segment Line Research Articles

A novel Linetype Recognition Algorithm Based on Track Geometry Detection Data

Abstract The detection and recognition of track geometry are crucial for ensuring railway transportation safety and maintenance efficiency. Traditional linetype recognition algorithms struggle to effectively handle the complexities of variable track geometry and noise interference. To address these challenges, a novel linetype recognition algorithm (NLRA) is proposed, which thoroughly analyzes the characteristics of track curvature across straight lines, transition curves, and circular segments. By employing partial differential equations for data preprocessing, NLRA effectively filters out noise. Utilizing curve design parameters and integrating line anti-noise recognition with multi-segment line fitting techniques, the algorithm accurately identifies each line segment and incorporates a single-point recognition method for data gaps. Experimental results demonstrate that NLRA outperforms traditional algorithms in terms of real-time performance, recognition accuracy, anti-interference capability, and noise handling. Notably, NLRA enhances accuracy by at least 35.1% and recall by at least 17.4% on selected typical routes. This work underscores the algorithm's potential to provide efficient and accurate tools for track maintenance, facilitate advancements in track detection software, and significantly contribute to railway transportation safety.

Theoretically exact backprojection filtration algorithm for multi-segment linear trajectory

A theoretically exact backprojection filtration algorithm is proved and implemented for image reconstruction from a multi-segment linear trajectory assuming fan-beam geometry. The reconstruction formula is based on a concept of linear PI-line (L-PI) proposed in our previous work. The proof is completed in two consecutive steps. In the first step, it is proved that theoretically exact image reconstruction can be obtained on an arbitrary L-PI line from an infinite straight-line trajectory. In the second step, it is shown that accurate image reconstruction can be achieved from a multi-segment line trajectory by introducing a weight function to deal with the data redundancy. Numerical implementation and simulation results validate the correctness of our theoretical results.

Fabrication of highly ordered multi-segment line pattern over a large-area

We report on the fabrication of well-aligned multi-segment line patterns over large areas featuring dimensional and compositional exquisite tunability using a combination of photolithography and soft-lithography techniques. We show that thus this new top-down approach has great advantages and that it is beneficial by increasing the control of the multi-segment line width and pattern feature dimensions ranging from microns to a few hundred nanometres. Various combinations of multi-segment materials with full control over the periodic alignment, which include Au–Ni, Au–Cu and Au–Ag, were prepared by simply changing the metals evaporated before the lift-off process. Au–Ni multi-segment metal line patterns showed a linear current–voltage response, identical with that of a line pattern from a single material. Thus, one can take advantage of the simple electrical properties of the 1-dimensional nanostructure. Our approach provides great potential in practical fabrication of well-integrated multi-metal component devices for electrical and optical detection.