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Soleimanmeigouni, ImanORCID iD iconorcid.org/0000-0002-3266-2434
Publications (10 of 25) Show all publications
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
Khajehei, H., Soleimanmeigouni, I., Ahmadi, A., Nissen, A. & Kumar, U. (2021). Investigation of Track Geometry Defects on a Heavy-Haul Railway Line. Journal of Transportation Engineering, Part A: Systems, 147(9), Article ID 05021004.
Open this publication in new window or tab >>Investigation of Track Geometry Defects on a Heavy-Haul Railway Line
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2021 (English)In: Journal of Transportation Engineering, Part A: Systems, ISSN 2473-2907, Vol. 147, no 9, article id 05021004Article in journal (Refereed) Published
Abstract [en]

This paper presents an in-depth case study of a heavy-haul railway line in Sweden to analyze the twist and longitudinal level geometry defects. A linear model was applied to model the evolution of the amplitude of the longitudinal level defects and twist over time. Despite the effect of the defect shapes on the dynamic track loads, the amplitude of the defects still is the only criterion used for the assessment of geometry defect severity. The application of first- and second-order derivatives to capture information about the shape of defects was investigated in the case study. In addition, the RUSBoost algorithm was used to classify track sections into healthy and unhealthy sections using the imbalance class data set. In this algorithm, the standard deviation and the kurtosis of the geometry parameters were used as explanatory variables. Finally, the abnormal track geometry degradation patterns identified in the case study were explored in detail. The results of the analysis can be used directly in maintenance modeling and used for the purpose of maintenance scheduling. 

Place, publisher, year, edition, pages
American Society of Civil Engineers (ASCE), 2021
Keywords
Track geometry, Geometry defects, Degradation, Maintenance, First- and second-order derivatives, Classification
National Category
Infrastructure Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-86901 (URN)10.1061/JTEPBS.0000571 (DOI)000683836700002 ()2-s2.0-85108995784 (Scopus ID)
Funder
Swedish Transport AdministrationLuleå Railway Research Centre (JVTC)
Note

Validerad;2021;Nivå 2;2021-09-01 (alebob);

Forskningsfinansiär: Bana Väg För Framtiden (BVFF)

Available from: 2021-08-30 Created: 2021-08-30 Last updated: 2022-10-27Bibliographically approved
Khajehei, H., Haddadzade, M., Ahmadi, A., Soleimanmeigouni, I. & Nissen, A. (2021). Optimal opportunistic tamping scheduling for railway track geometry. Structure and Infrastructure Engineering, 17(10), 1299-1314
Open this publication in new window or tab >>Optimal opportunistic tamping scheduling for railway track geometry
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2021 (English)In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 17, no 10, p. 1299-1314Article in journal (Refereed) Published
Abstract [en]

This study has been dedicated to the optimization of opportunistic tamping scheduling. The aim ofthis study has been to schedule tamping activities in such a way that the total maintenance costs andthe number of unplanned tamping activities are minimized. To achieve this, the track geometry tampingscheduling problem was defined and formulated as a mixed integer linear programming (MILP)model and a genetic algorithm was used to solve the problem. Both the standard deviation of thelongitudinal level and the extreme values of isolated defects were used to characterize the trackgeometry quality and to plan maintenance activities. The performance of the proposed model wastested on data collected from the Main Western Line in Sweden. The results show that different scenariosfor controlling and managing isolated defects will result in optimal scheduling plan. It is alsofound that to achieve more realistic results, the speed of the tamping machine and the unused life ofthe track sections should be considered in the model. Moreover, the results show that prediction ofgeometry condition without considering the destructive effect of tamping will lead to an underestimationof the maintenance needs by 2%.

Place, publisher, year, edition, pages
Taylor & Francis, 2021
Keywords
Degradation, genetic algorithms, logistic regression, maintenance, optimal scheduling, railway track, tamping
National Category
Transport Systems and Logistics Infrastructure Engineering Reliability and Maintenance
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-80727 (URN)10.1080/15732479.2020.1809467 (DOI)000564982100001 ()2-s2.0-85090081276 (Scopus ID)
Funder
Swedish Transport AdministrationLuleå Railway Research Centre (JVTC)
Note

Validerad;2021;Nivå 2;2021-09-29 (alebob);

Funder: Bana Väg För Framtiden (BVFF) 

Available from: 2020-09-08 Created: 2020-09-08 Last updated: 2022-10-27Bibliographically approved
Khosravi, M., Soleimanmeigouni, I., Ahmadi, A. & Nissen, A. (2021). Reducing the Positional Errors of Railway Track Geometry Measurements Using Alignment Methods: a Comparative Case Study. Measurement, 178, Article ID 109383.
Open this publication in new window or tab >>Reducing the Positional Errors of Railway Track Geometry Measurements Using Alignment Methods: a Comparative Case Study
2021 (English)In: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 178, article id 109383Article in journal (Refereed) Published
Abstract [en]

To predict the occurrence of geometry defects and to achieve a reliable maintenance strategy, accurate positioning of track geometry measurements is of great importance. This paper aims to reduce the positional errors in track geometry measurements by finding an efficient alignment method. Therefore, five alignment methods, i.e. the cross-correlation function, recursive alignment by fast Fourier transform, dynamic time warping, correlation optimized warping, and a combined method, were evaluated and compared concerning their ability to align the measurements precisely, keep the original shape of the measurements, and minimise the use of time and memory. Furthermore, the influence of choosing a proper reference dataset was investigated. A case study based on track geometry data from the Main Western Line in Sweden was conducted to implement and assess the methods. Findings revealed that the combined method could decrease the positional errors of single defects to below 0.25 m in 90% of the trials.

Place, publisher, year, edition, pages
Elsevier, 2021
Keywords
Railway track geometry, data alignment, positional error, reference selection, relative position errors
National Category
Reliability and Maintenance
Research subject
Centre - Luleå Railway Research Center (JVTC); Operation and Maintenance; Centre - Center for Maintenance and Industrial Services (CMIS)
Identifiers
urn:nbn:se:ltu:diva-83623 (URN)10.1016/j.measurement.2021.109383 (DOI)000652488200004 ()2-s2.0-85104318934 (Scopus ID)
Funder
Luleå Railway Research Centre (JVTC)Swedish Transport Administration
Note

Validerad;2021;Nivå 2;2021-04-19 (alebob)

Available from: 2021-04-13 Created: 2021-04-13 Last updated: 2023-10-03Bibliographically approved
Ahmadi, A. & Soleimanmeigouni, I. (2021). Simulation of railway track geometry and intelligent maintenance planning: [Simulering av järnvägsspårgeometri och intelligent underhållsplanering]. Luleå University of Technology
Open this publication in new window or tab >>Simulation of railway track geometry and intelligent maintenance planning: [Simulering av järnvägsspårgeometri och intelligent underhållsplanering]
2021 (English)Report (Other academic)
Abstract [en]

Track is the fundamental part of railway infrastructure and represents a significant part of maintenance effort and cost. For example, in Sweden, the annual maintenance cost for only track geometry is between110 and 130 MSEK. The quality of the track, mostly, is represented by the track geometry properties. Track geometry degrades with age and usage; and loses its functionality over time. Poor quality of track geometry may result in safety problems, speed reduction, traffic disruption, greater maintenance cost, and higher degradation rate of the other railway components (e.g. rails, wheels, switches, and crossings). Railway track maintenance program development is challenging and requires appropriate modeling which reflects the real-life scenario and integrates influencing factors. In addition, there are several uncertainties in data collection, data analysis, modeling, and the prediction that are needed to be considered. Moreover, there is a lack of integrated platform that is able to access geometry data, extract associatedinformation, and retain this knowledge for supporting adaptive maintenance planning and scheduling. The above challenges necessitate the Infrastructure Manager (IM) to employ a maintenance management system that enables higher capacity for evaluation of track performance, learning from asset history, context-driven awareness, planning & scheduling, and transformation of this information to knowledge for decision making. The SIMTRACK project will facilitate simulation-based platform that enables development of a tools,methodologies and techniques for optimization of track geometry maintenance planning, scheduling andopportunistic maintenance. This will provide a basis to predict track geometry degradation, analyse therisk of failures and forecast the maintenance activities as well as renewal investment requirements. The results will enhance safety, maximize capacity utilization, and lead to an efficient and cost effective maintenance program. The project structure track is structured into 6 work packages. WP1 deals with the project management. WP2 presentsthe industrial scenarios, specifications and requirements that provide inputs to WP3 and WP4. WP3 andWP4 are defined as predictive modelling and analytics of track geometry condition and trackmaintenance optimization and decision support system respectively. WP5 is dedicated to evaluation ofabsolute track geometry condition. Finally, WP6 deals with dissemination and exploitation, is devotedfor formulating comprehensive plans for results assimilation by the partners and set the ground for theexploitation. Figure 1 shows the work packages and their relationships.

Place, publisher, year, edition, pages
Luleå University of Technology, 2021. p. 10
National Category
Reliability and Maintenance
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-84664 (URN)
Projects
Simtrack
Funder
Swedish Transport Administration
Available from: 2021-05-28 Created: 2021-05-28 Last updated: 2022-10-27Bibliographically approved
Khajehei, H., Soleimanmeigouni, I., Ahmadi, A., Nissen, A. & Haddadzade, M. (2020). Application of First- and Second-Order Derivatives of Track Irregularity to Plan Local Maintenance Activities. In: Piero Baraldi; Francesco Di Maio; Enrico Zio (Ed.), e-proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15): . Paper presented at 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15), Venice, Italy, November 1-5, 2020 (pp. 942-948). Research Publishing Services
Open this publication in new window or tab >>Application of First- and Second-Order Derivatives of Track Irregularity to Plan Local Maintenance Activities
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2020 (English)In: e-proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15) / [ed] Piero Baraldi; Francesco Di Maio; Enrico Zio, Research Publishing Services, 2020, p. 942-948Conference paper, Published paper (Refereed)
Abstract [en]

A large part of the railway track geometry maintenance burden concerns local maintenance activates conducted to rectify isolated defects. Isolated defects are short irregularities in the track geometry that can dramatically increase the dynamic forces between the wheel and rail, which in turn will accelerate the growth or occurrence of internal rail defects. The dynamic force between the wheel and rail is dependent on the shape of the isolated geometry defects. However, the severity of isolated defects is mainly defined only by their amplitude. Therefore, in addition to amplitude, other characteristics of geometry defects must be considered to analyze severity of defects and to prioritize local maintenance actions. This study aims to use the first- and second-order derivatives of the longitudinal level defects to plan local maintenance activities. The derivatives of geometry defects provide useful information about the shape of defects. The information is used to categorize the isolated defects based on their severities and prioritize maintenance actions. In this regard, K-means clustering technique is applied. The results of this study will support the decision-making process regarding the planning of local maintenance activities. The foot-by-foot track geometry data collected from Main Western Line in Sweden is used to implement and test the model.

Place, publisher, year, edition, pages
Research Publishing Services, 2020
Keywords
Railway, Track geometry, K-means clustering, Isolated defect, Maintenance planning, Second-order derivative
National Category
Infrastructure Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-84094 (URN)10.3850/978-981-14-8593-0_5054-cd (DOI)2-s2.0-85107311605 (Scopus ID)
Conference
30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15), Venice, Italy, November 1-5, 2020
Funder
Swedish Transport AdministrationLuleå Railway Research Centre (JVTC)
Note

ISBN för värdpublikation: 978-981-14-8593-0;

Finansiär: Bana Väg För Framtiden 

Available from: 2021-05-04 Created: 2021-05-04 Last updated: 2022-10-31Bibliographically approved
Soleimanmeigouni, I., Ahmadi, A., Khajehei, H. & Nissen, A. (2020). Investigation of the effect of the inspection intervals on the track geometry condition. Structure and Infrastructure Engineering, 16(8), 1138-1146
Open this publication in new window or tab >>Investigation of the effect of the inspection intervals on the track geometry condition
2020 (English)In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 16, no 8, p. 1138-1146Article in journal (Refereed) Published
Abstract [en]

In order to evaluate the railway track geometry condition and plan maintenance activities, track inspection cars run over the track at specific times to monitor it and record geometry measurements. Applying an adequate inspection interval is vital to ensure the availability, safety and quality of the railway track, at the lowest possible cost. The aim of this study has been to investigate the effect of different inspection intervals on the track geometry condition. To achieve this, an integrated statistical model was developed to predict the track geometry condition given different inspection intervals. In order to model the evolution of the track geometry condition, a piecewise exponential model was used which considers break points at the maintenance times. Ordinal logistic regression was applied to model the probability of the occurrence of severe isolated defects. The Monte Carlo technique was used to simulate the track geometry behaviour given different inspection intervals. The results of the proposed model support the decision-making process regarding the selection of the most adequate inspection interval. The applicability of the model was tested in a case study on the Main Western Line in Sweden.

Place, publisher, year, edition, pages
Taylor & Francis, 2020
Keywords
Inspection, track geometry, maintenance, multivariable linear regression, isolated defects, ordinal logistic regression
National Category
Civil Engineering Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-76798 (URN)10.1080/15732479.2019.1687528 (DOI)000497542100001 ()2-s2.0-85075369655 (Scopus ID)
Note

Validerad;2020;Nivå 2;2020-06-09 (alebob)

Available from: 2019-11-21 Created: 2019-11-21 Last updated: 2022-10-31Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-3266-2434

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