@article{khosravi_modification_2022,
	title = {Modification of correlation optimized warping method for position alignment of condition measurements of linear assets},
	volume = {201},
	issn = {0263-2241},
	url = {https://www.sciencedirect.com/science/article/pii/S0263224122009149},
	doi = {10.1016/j.measurement.2022.111707},
	abstract = {This paper proposes a modification to a well-known alignment method, correlation optimized warping (COW), to improve the efficiency of the method and reduce the positional errors in the measurements of linear assets. The modified method relaxes the restrictions of COW in aligning the start and end of datasets and decreases the computational time. Furthermore, the method takes advantage of the interdependencies between simultaneously measured channels to overcome the missing data problem. A case study on railway track geometry measurements was conducted to implement the proposed method and assess its performance in reducing the positioning inaccuracy of the measurements. The findings revealed that the modified method could decrease the positional errors of defects to below 25 cm in 94 \% of the trials.},
	urldate = {2023-10-03},
	journal = {Measurement},
	author = {Khosravi, Mahdi and Soleimanmeigouni, Iman and Ahmadi, Alireza and Nissen, Arne and Xiao, Xun},
	month = sep,
	year = {2022},
	keywords = {Condition measurements, Correlation optimized warping, Data quality, Linear assets, Position alignment, Positional error},
	pages = {111707},
}

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