Systems Approach to the Organization of Locomotive Maintenance on Ukraine Railways

Tartakovskyi, Eduard; Ustenko, Oleksander; Puzyr, Volodymyr; Datsun, Yurii

doi:10.1007/978-3-319-51502-1_5

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…The theoretical foundations and substantiation of the need to introduce the RCM methodology in the locomotive maintenance system are given in work [1]. The authors propose to use a differential approach to each element of the locomotive.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising a procedure for calculating the technical condition index of locomotive nodes based on monitoring results

Bodnar

Очкасов

Ochkasov

2021

EEJET

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The widespread introduction of information technologies in the systems that manage technical fleets, the use of maintenance and repair systems based on risk assessment, is based on the calculation of a large enough number of indicators. Modern locomotives are equipped with systems for monitoring and diagnosing technical condition. Combining these systems with the Internet of Things and Big Data technologies provides an opportunity to use completely new approaches to fleet management. At the initial stage of the construction of such systems, it is necessary to devise criteria that make it possible to automatically determine the technical condition of a locomotive and its components in order to identify the locomotive in the total fleet that requires maintenance or repair. A procedure has been proposed for calculating the technical condition index of locomotives and their components based on data from monitoring systems. The procedure is based on the formation of latent diagnostic parameters employing the principal component method and on the subsequent calculation of the weight coefficients of these parameters applying the method of hierarchy analysis. The special feature of the proposed procedure is that when calculating the index, those latent diagnostic parameters are used that are derived from the group of control parameters whose weight coefficients are computed using the method of hierarchy analysis without involving experts. This paper reports the results from calculating the informativeness of the diagnostic parameters of load, loss, input, as well as their weight coefficients. The highest information content, from 0.5 to 0.85, is demonstrated by the load parameter; the smallest (0.05‒0.26) ‒ the input parameter. The average value and the dependences of changes in the technical condition index of a hydraulic transmission during the tests have been determined. Analysis of the technical condition index makes it possible to assess the transmission's response to changes in test modes, the dynamics of changes in losses

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising a procedure for calculating the technical condition index of locomotive nodes based on monitoring results

Bodnar

Очкасов

Ochkasov

2021

EEJET

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“…It allows expecting the use of automation and robotization facilities in repair works in the immediate future. Railway locomotive and wagon manufacturing works possess the positive experience of production lines' use [4,5]. The widest extension got production lines for repair of bogies, railway motors, mounted wheels and axle boxes, shells and reducers of traction gears, diesel engines, connecting rod and piston group and radiator sections [6].…”

Section: Introductionmentioning

confidence: 99%

Design of Algorithm for Identification of Locomotive Electrical Machine Unit During Repair

Puzyr¹,

Datsun²,

Obozny³

2018

IJET

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The purpose of this article is the design of an algorithm for identification of locomotive electrical machine unit by robotic cleaning facility during repair. The recognition and identification of objects is affected by several random factors and is the probabilistic process. the Johnson criterion was used as the criterion that allows making decision on fulfilment of the identification task with the specified degree of reliability. The diameter of locomotive fuel and oil pump motor fittings was adopted as the critical minimal dimension of the object to be identified. It was calculated that for identification of locomotive electrical machine unit the digital image should have dimensions of 80х80 pixels. The identification of 80х80 two-dimensional vector requires larger memory space and longer system learning time. The decrease of input data amount is possible by image additional processing. In order to decrease the unit identification system input data amount the algorithm foreseeing input vector of values generation using summarization of pixel binary codes over lines was developed. The unit identification system was built on the basis of the multilayer perceptron and was modeled in Neural Network Toolbox MATLAB package. The best learning error magnitude result was shown by the network with 40 hidden layers.

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Implementing Intelligent Monitoring of the Technical Condition of Locomotive Hydraulic Transmissions

Bondar

Petrenko

2023

Lecture Notes in Intelligent Transportation and Infrastructure

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Systems Approach to the Organization of Locomotive Maintenance on Ukraine Railways

Cited by 10 publications

References 7 publications

Devising a procedure for calculating the technical condition index of locomotive nodes based on monitoring results

Devising a procedure for calculating the technical condition index of locomotive nodes based on monitoring results

Design of Algorithm for Identification of Locomotive Electrical Machine Unit During Repair

Implementing Intelligent Monitoring of the Technical Condition of Locomotive Hydraulic Transmissions

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