A Multi-objective approach for position alignment of track geometry measurements
| Autor: | Mahdi Khosravi, Alireza Ahmadi, Arne Nissen |
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| Rok vydání: | 2023 |
| Předmět: |
Position alignment
Annan maskinteknik Modified correlation optimised warping Railway track geometry Linear asset General Engineering Positional error General Materials Science Other Mechanical Engineering Electrical Engineering Electronic Engineering Information Engineering Elektroteknik och elektronik Recursive segment-wise peak alignment Condition monitoring |
| Zdroj: | Engineering Failure Analysis. 149:107260 |
| ISSN: | 1350-6307 |
| DOI: | 10.1016/j.engfailanal.2023.107260 |
| Popis: | This study aimed to develop a multi-objective approach for reducing the positional errors in geometry measurements of track as a linear asset. Accordingly, we evaluated and compared two alignment methods – recursive segment-wise peak alignment (RSPA) and modified correlation optimised warping (MCOW). Furthermore, a novel rule-based approach was introduced to avoid data loss while aligning the datasets of the measurements of linear assets. A case study was conducted to implement and assess the performance of these methods in reducing the positional errors in track geometry measurements. The results revealed that the rule-based method preserves all the single defects present in the datasets. Furthermore, RSPA outperforms MCOW when aligning peaks, whereas MCOW is more efficient when all the data points in the datasets have equal priority. Validerad;2023;Nivå 2;2023-05-05 (hanlid);Funder: EU-Rail FP3-IAM4Rail (101101966) |
| Databáze: | OpenAIRE |
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