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Publications (10 of 87) Show all publications
Söderholm, P. & Ahmadi, A. (2024). Integrated Enterprise Risk Management and Industrial Artificial Intelligence in Railway. In: International Congress and Workshop on Industrial AI and eMaintenance 2023: . Paper presented at 7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023 (pp. 569-583). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Integrated Enterprise Risk Management and Industrial Artificial Intelligence in Railway
2024 (English)In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 569-583Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2024
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-103878 (URN)10.1007/978-3-031-39619-9_42 (DOI)2-s2.0-85181980834 (Scopus ID)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023
Funder
Vinnova
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-01-23Bibliographically approved
Khosravi, M., Ahmadi, A. & Kasraei, A. (2024). Pre-processing of Track Geometry Measurements: A Comparative Case Study. In: Uday Kumar; Ramin Karim; Diego Galar; Ravdeep Kour (Ed.), International Congress and Workshop on Industrial AI and eMaintenance 2023: . Paper presented at 7th International Congress and Workshop on Industrial AI and eMaintenance (IAI2023), Luleå, Sweden, June 13-15, 2023 (pp. 355-366). Springer Nature
Open this publication in new window or tab >>Pre-processing of Track Geometry Measurements: A Comparative Case Study
2024 (English)In: International Congress and Workshop on Industrial AI and eMaintenance 2023 / [ed] Uday Kumar; Ramin Karim; Diego Galar; Ravdeep Kour, Springer Nature, 2024, p. 355-366Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Mechanical Engineering (LNME), ISSN 2195-4364, E-ISSN 2195-4356
National Category
Other Mechanical Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-101232 (URN)10.1007/978-3-031-39619-9_26 (DOI)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance (IAI2023), Luleå, Sweden, June 13-15, 2023
Projects
In2Smart II
Funder
Swedish Transport AdministrationEU, Horizon 2020, 881574 Shift2RailLuleå Railway Research Centre (JVTC)
Note

ISBN for host publication: 978-3-031-39618-2, 978-3-031-39619-9

Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2024-01-12Bibliographically approved
Khosravi, M., Ahmadi, A. & Nissen, A. (2023). A Multi-objective approach for position alignment of track geometry measurements. Engineering Failure Analysis, 149, Article ID 107260.
Open this publication in new window or tab >>A Multi-objective approach for position alignment of track geometry measurements
2023 (English)In: Engineering Failure Analysis, ISSN 1350-6307, E-ISSN 1873-1961, Vol. 149, article id 107260Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Condition monitoring, Linear asset, Modified correlation optimised warping, Position alignment, Positional error, Railway track geometry, Recursive segment-wise peak alignment
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Other Mechanical Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-97020 (URN)10.1016/j.engfailanal.2023.107260 (DOI)2-s2.0-85152632115 (Scopus ID)
Funder
Swedish Transport AdministrationLuleå Railway Research Centre (JVTC)
Note

Validerad;2023;Nivå 2;2023-05-05 (hanlid);

Funder: EU-Rail FP3-IAM4Rail (101101966)

Available from: 2023-05-05 Created: 2023-05-05 Last updated: 2023-10-03Bibliographically approved
Khosravi, M., Kasraei, A. & Ahmadi, A. (2023). Assessment of Railway Track Preventive and Corrective Tamping Recovery. In: : . Paper presented at 12th International Heavy Haul Conference 2023 (IHHA 2023), Rio De Janeiro, Brazil, August 27-31, 2023.
Open this publication in new window or tab >>Assessment of Railway Track Preventive and Corrective Tamping Recovery
2023 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

Railway track, as a critical infrastructure, plays a significant role in freight transportation. However, Railway track degrades with age and usage and can impact negatively track availability and safety. Tamping actions are used to rejuvenate the degradation and recover the functionality of the track to an acceptable level. Tamping actions are performed in a form of preventive and corrective regimes. In performing an effective tamping regime, the recovery of both preventive and corrective tamping should be taken into account. In addition, the occurrence of isolated defects should be considered. By combining the recovery model with the degradation model, the long-term behavior of the track geometry can be predicted, and an accurate estimation of tamping needs can be provided, leading to optimum tamping scheduling. In this study, the effects of tamping recovery are modeled for both preventive and corrective strategies. For this aim, the values of both standard deviation (SD) and isolated defects have been predicted and their values before tamping are used as explanatory variables in a multivariable regression model. Finally, the effect of tamping recovery on the values of both SD and isolated defects is estimated. A case study is performed on a heavy haul line located in Sweden’s rail network to evaluate the performance of the proposed multivariable regression model. Observations showed that the model and its coefficients are significant with P-values close to zero, and the R-squared value suggests that the model explains approximately 70% of the variability in the response variable recovery.

Keywords
Track Geometry, Alignment, Preventive and Corrective Maintenance, Linear Assets
National Category
Infrastructure Engineering Transport Systems and Logistics Other Civil Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-101231 (URN)
Conference
12th International Heavy Haul Conference 2023 (IHHA 2023), Rio De Janeiro, Brazil, August 27-31, 2023
Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2023-09-06Bibliographically approved
Parsaei, S., Pirouzmand, A., Nematollahi, M. R., Ahmadi, A. & Hadad, K. (2023). Effect of test-caused degradation on the unavailability of standby safety components. Nuclear engineering and technology : an international journal of the Korean Nuclear Society
Open this publication in new window or tab >>Effect of test-caused degradation on the unavailability of standby safety components
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2023 (English)In: Nuclear engineering and technology : an international journal of the Korean Nuclear Society, ISSN 1738-5733, E-ISSN 2234-358XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

This paper proposes a safety-critical standby component unavailability model that contains aging effects caused by the elapsed time from installation, component degradation due to surveillance tests, and imperfect maintenance actions. An application of the model to a Motor-Operated Valve and a Motor-Driven Pump involved in the HPIS of a VVER/1000-V446 nuclear power plant is demonstrated and compared with other existing models at component and system levels. In addition, the effects of different unavailability models are reflected in the NPP's risk criterion, i.e., core damage frequency, over five maintenance periods. The results show that, compared with other models that do not simultaneously consider the full effects of degradation and maintenance impacts, the proposed model realistically evaluates the unavailabilities of the safety-related components and the involved systems as a plant age function. Therefore, it can effectively reflect the age-dependent CDF impact of a given testing and maintenance policy in a specified time horizon.

Place, publisher, year, edition, pages
Korean Nuclear Society, 2023
Keywords
Age-dependent unavailability, Imperfect maintenance, Probabilistic safety assessment (PSA), Standby-related failure rate, Test-caused degradation
National Category
Other Civil Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-102428 (URN)10.1016/j.net.2023.10.029 (DOI)2-s2.0-85175659005 (Scopus ID)
Note

Full text license: CC BY

Available from: 2023-11-13 Created: 2023-11-13 Last updated: 2023-11-13
Khosravi, M., Ahmadi, A. & Kasraei, A. (2023). Improving reliability assessment of degrading linear assets by aligning inspection measurement. In: Proceedings of the 8th International Conference on Recent Advances in Railway Engineering (ICRARE 2023): . Paper presented at 8th International Conference on Recent Advances in Railway Engineering (ICRARE 2023), Tehran, Iran, May 23-24, 2023. Central Office of Boom Sazeh Publication (Civilica)
Open this publication in new window or tab >>Improving reliability assessment of degrading linear assets by aligning inspection measurement
2023 (English)In: Proceedings of the 8th International Conference on Recent Advances in Railway Engineering (ICRARE 2023), Central Office of Boom Sazeh Publication (Civilica) , 2023Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Central Office of Boom Sazeh Publication (Civilica), 2023
National Category
Transport Systems and Logistics Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-99264 (URN)
Conference
8th International Conference on Recent Advances in Railway Engineering (ICRARE 2023), Tehran, Iran, May 23-24, 2023
Available from: 2023-08-07 Created: 2023-08-07 Last updated: 2023-09-06Bibliographically approved
Marchetta, V., Di Graziano, A., Soleimanmeigouni, I. & Ahmadi, A. (2023). Railway degradation behaviour analysis in narrow-gauge railways: A local-railway case study. Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, 237(6), 818-831
Open this publication in new window or tab >>Railway degradation behaviour analysis in narrow-gauge railways: A local-railway case study
2023 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 237, no 6, p. 818-831Article in journal (Refereed) Published
Abstract [en]

An efficient maintenance strategy is a key factor to ensure acceptable safety levels and manage the overall costs of a railway network. So far, research focused mainly on regional and high-speed rail networks, causing a knowledge and regulation gap between standard and narrow-gauge railways networks. These networks, like the local or isolated railways, have peculiar geometric and operational characteristics that play a key role on track geometry quality degradation process. For this reason, the maintenance knowledge gained in the context of standard railways when applied to systems such as narrow-gauge railways could lead to non-optimized use of the limited resources available. Therefore, the aim of this study is to analyse how the track geometry quality degradation behaviour is influenced by the key characteristics of narrow-gauge railways through the analysis of the track geometry data of an Italian local railway, laying the foundation for optimized maintenance strategies for these systems.

Place, publisher, year, edition, pages
Sage Publications, 2023
Keywords
local railways, narrow-gauge, track geometry, track degradation, maintenance, infrastructure management
National Category
Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-94309 (URN)10.1177/09544097221136912 (DOI)000883208000001 ()2-s2.0-85141807135 (Scopus ID)
Note

Validerad;2023;Nivå 2;2023-07-06 (sofila);

Funder: University of Catania (TIMUC “Piano della Ricerca Dipartimentale 2018–2020” )

Available from: 2022-11-28 Created: 2022-11-28 Last updated: 2023-07-06Bibliographically approved
Karim, R., Ahmadi, A., Soleimanmeigouni, I., Kour, R. & Rao, R. (Eds.). (2022). International Congress and Workshop on Industrial AI 2021. Paper presented at International Congress and Workshop on Industrial AI (IAI 2021), Luleå, Sweden, October 5-7, 2021. Springer
Open this publication in new window or tab >>International Congress and Workshop on Industrial AI 2021
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2022 (English)Conference proceedings (editor) (Refereed)
Place, publisher, year, edition, pages
Springer, 2022. p. 446
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-89312 (URN)10.1007/978-3-030-93639-6 (DOI)978-3-030-93638-9 (ISBN)978-3-030-93639-6 (ISBN)
Conference
International Congress and Workshop on Industrial AI (IAI 2021), Luleå, Sweden, October 5-7, 2021
Available from: 2022-02-16 Created: 2022-02-16 Last updated: 2022-10-27Bibliographically approved
Khosravi, M., Soleimanmeigouni, I., Ahmadi, A., Nissen, A. & Xiao, X. (2022). Modification of correlation optimized warping method for position alignment of condition measurements of linear assets. Measurement, 201, Article ID 111707.
Open this publication in new window or tab >>Modification of correlation optimized warping method for position alignment of condition measurements of linear assets
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2022 (English)In: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 201, article id 111707Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Position alignment, correlation optimized warping, data quality, linear assets, positional error, condition measurements
National Category
Software Engineering Other Mechanical Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-92409 (URN)10.1016/j.measurement.2022.111707 (DOI)000871195400003 ()2-s2.0-85135916407 (Scopus ID)
Funder
Swedish Transport AdministrationLuleå Railway Research Centre (JVTC)
Note

Validerad;2022;Nivå 2;2022-08-16 (sofila);

Funder: In2Smart II project (881574 EU Shift2Rail)

Available from: 2022-08-10 Created: 2022-08-10 Last updated: 2023-10-03Bibliographically approved
Khajehei, H., Ahmadi, A., Soleimanmeigouni, I., Haddadzade, M., Nissen, A. & Latifi Jebelli, M. J. (2022). Prediction of track geometry degradation using artificial neural network: a case study. International Journal of Rail transportation, 10(1), 24-43
Open this publication in new window or tab >>Prediction of track geometry degradation using artificial neural network: a case study
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2022 (English)In: International Journal of Rail transportation, ISSN 2324-8378, E-ISSN 2324-8386, Vol. 10, no 1, p. 24-43Article in journal (Refereed) Published
Abstract [en]

The aim of this study has been to predict the track geometry degradation rate using artificial neural network. Tack geometry measurements, asset information, and maintenance history for five line sections from the Swedish railway network were collected, processed, and prepared to develop the ANN model. The information of track was taken into account and different features of track sections were considered as model input variables. In addition, Garson method was applied to explore the relative importance of the variables affecting geometry degradation rate. By analysing the performance of the model, we found out that the ANN has an acceptable capability in explaining the variability of degradation rates in different locations of the track. In addition, it is found that the maintenance history, the degradation level after tamping, and the frequency of trains passing along the track have the strongest contributions among the considered set of features in prediction of degradation rate.

Place, publisher, year, edition, pages
Taylor & Francis, 2022
Keywords
Artificial neural network, prediction, degradation, track geometry, garson's algorithm
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-82710 (URN)10.1080/23248378.2021.1875065 (DOI)000613707500001 ()2-s2.0-85099801065 (Scopus ID)
Funder
Swedish Transport AdministrationLuleå Railway Research Centre (JVTC)
Note

Validerad;2022;Nivå 2;2022-02-21 (hanlid);

Finansiär: Bana Väg För Framtiden (BVFF)

Available from: 2021-01-29 Created: 2021-01-29 Last updated: 2022-04-27Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7083-4009

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