Strength and life estimation for assigning the useful life of wheelpairs of high-speed flat wagons

Aim. The most vital unit of railway rolling stock is a wheelpair, as a broken wheel or axle may have catastrophic consequences. Therefore, before the production of a highspeed flat wagon designed for operation at speeds of up to 140 km/h, which is unique for the 1520 mm gauge space, could commence, it was required to research the applicability of the standard wheelpair for high-speed movement. Ensuring the safe operation of a wheelpair involves compliance with the requirements that are to be confirmed by means of assessment of strength and durability parameters [1]. Product conformity assessment may be based on the requirements of standards, whose voluntary fulfilment ensures compliance with [1], or other documents. Methods. The paper describes the computational and experimental methods used for confirming the strength and estimating the life (durability) of wheelpair elements in the probabilistic setting. As experimental data, the authors used the results of full-scale bench testing of wheelpairs for fatigue using the method of rotational bending as it best approximates the loading conditions in operation. The results confirmed the endurance limits of the axle and wheel as parts of an assembled wheelpair. Using design analysis, the authors examined the stress-strain state of the wheelpair caused by installation and operational loads in various running modes. Results. The conducted studies confirmed the wheelpair’s compliance with the requirements of [1–3] in terms of safety factors of fatigue strength and endurance, which eliminates the possibility of hazardous situations in the course of high-speed flat wagon operation. The time to fatigue crack nucleation in wheelpair components was evaluated using the fatigue resistance figures of the parts and equivalent amplitudes of dynamic stress caused by operational loads. It appears that this assessment allows establishing – with the assumed probability of destruction – the assigned useful life of a wheelpair axle at 32 years, which corresponds to the assigned useful life of the flat wagon according to the combined criterion. Corresponding standards and regulations required for developing the container-carrying flat wagon are being updated and a new State Standard is being developed. Conclusion. The conducted conformity assessment established that the flat wagon wheelpair meets the safety requirements of [1] and ensures the absence of unacceptable risks associated with harm to life and health of people, animals and plants, the environment and property of individuals and companies in the course of flat wagon operation.

Use of exponential distribution in mathematical models of dependability

The exponential distribution of time to event or end of state is popular in the dependability theory. This distribution is characterized by the strength that is a convenient parameter used in mathematical models and calculations. The exponential distribution is used as part of dependability-related process simulation. Examples are given to illustrate the applicability of the exponential distribution. Aim. The aim of the paper is to improve the dependability-related simulation methods when using the exponential distribution of periods of states or times to events. Methods. The assumption of the exponential distribution of time between events can be justified or discarded using methods of the probability theory and/or mathematical statistics or on the basis of personal or engineering experience. It has been experimentally established that the failure flow in an established mode of operation is stationary, ordinary and produces no consequences. Such flow is Poisson and is distinct in the fact that the time between two consecutive failures is distributed exponentially with a constant rate. This exponential distribution is reasonably extended to the distribution of an item’s failure-free time. However, in other cases, the use of exponential distribution is often not duly substantiated. The methodological approach and the respective conclusions are case-based. A number of experience-based cases are given to show the non-applicability of exponential distribution. Discussion. Cases are examined, in which the judgement on the applicability or non-applicability of exponential distribution can be made on the basis of personal experience or the probability theory. However, in case of such events as completion of recovery, duration of scheduled inspection, duration of maintenance, etc., a judgement regarding the applicability of exponential distribution cannot be made in the absence of personal experience associated with such events. The distribution of such durations is to be established using statistical methods. The paper refers to the author’s publications that compare the frequency of equipment inspections with regular and exponentially distributed periods. The calculated values of some indicators are retained, while for some others they are different. There is a two-fold difference between the unavailability values for the above ways of defining the inspection frequency. Findings and conclusions. The proposed improvements to the application of exponential distribution as part of dependability simulation come down to the requirement of clear substantiation of the application of exponential distribution of time between events using methods of the probability theory and mathematical statistics. An unknown random distribution cannot be replaced with an exponential distribution without a valid substantiation. Replacing a random time in a subset of states with a random exponentially distributed time with a constant rate should be done with an error calculation.

Decision support for preventing safety violations

Aim. The aim of the paper is to examine the experience of reducing the effect of the human factor on business processes, to develop the structure and software of the decisionsupport system for preventing safety violations by train drivers using machine learning and to analyse the findings. Methods. The study presented in the paper uses machine learning, statistical analysis and expert analysis. In terms of machine learning, the following methods were used: logistical regression, random forests, gradient boosting over decision trees with frequency-domain representation of categorical features, neural networks. Results. A set of indicators characterizing a train driver’s operation were identified and are to be used as part of the system under development. The term “train driver’s reliability” was defined as the ability not to violate train traffic safety over a certain number of trips. Algorithms were designed and examined for predicting violations in a train driver’s operation that are used in defining reliability groups and lists of preventive measures recommended for the reduction of the number of safety violations in a train driver’s operation. Major violations with proven guilt of the driver that may be committed within the following 3, 7, 10, 20, 30, 60 days were chosen as attributes for the purpose of safety violation prediction. Analysis of the results on the test sample revealed that the model based on gradient boosting over decision trees with frequency-domain representation of categorical features shows the best results for binary classification on the prediction horizon of 30 and 60 days. The developed algorithm made a correct prediction in 76% of cases with the threshold value of 0.7 and horizon of 30 days and in 82% of cases with the threshold value of 0.9 and horizon of 60 days. The solution of the problem can be found in the integration of different approaches to predicting safety violations in a train driver’s operation. Additionally, 10 of the most significant indicators of a train driver’s operation were identified with the best of the considered models, i.e., gradient boosting over decision trees with frequency-domain representation of categorical features. Conclusion. The paper presents an overview of methods and systems of assessing human reliability and the effect of the human factor on the safety of transportation systems. It allowed choosing the most promising directions and methods of predictive analysis of a train driver’s operation, including methods of machine learning. The resulting set of indicators of a train driver’s operation that take into consideration the changes in the quality of such operation allowed obtaining initial data for training the models implemented as part of the system under development. The implemented models enabled the aggregation of information on train drivers and adoption of targeted and temporary preventive measures recommended for improving driver reliability. The resulting approach to the definition of preventive measures has been implemented in three depots of JSC RZD in trial operation mode.

A method of testing relay protection and automation involving exposure to cascading effects for improved power supply reliability and electric power system stability

The Aim of the paper is to show that improved power supply reliability and electric power system stability are achieved by applying new methods of testing relay protection and automation (RPaA). Major cascading failures in electric power systems are caused by cascading effects, i.e., effects involving several successive effects of various nature. Cascading effects allow extending the functionality while testing RP&A and taking into account the time factor in the context of effects of various nature. Method. A method is proposed for testing relay protection and automation taking into account the cascading effect that is used in the process of development, calibration and installation of protection devices for operation in predefined modes for the purpose of improved power supply reliability and unfailing stability of electric power systems. Result. Intermittent cascading effects do not allow the relay protection and automation recover the electric power system from the post-emergency mode, thus reducing the dynamic stability to the critical level. The diagram of relay protection and automation exposure allows taking into consideration the environmental effects in the process of testing the relay protection and automation. Conclusion. The proposed method of cascading exposure as part of testing relay protection and automation can be used in the process of development, calibration and installation of electric power systems protection and will enable improved stability of electric power systems and reliability of power supply.

On the safety assessment of an automatic train operation system

The paper examines the automatic train operation system as part of the locomotive control and protection system, the remote supervision centre’s means for control of onboard and trackside machine vision facilities. The focus is on the dependence of the system’s safety and dependability on the dependability characteristics of its components and adverse weather effects. The criteria of a system’s wrong-side and right-side failures were defined, the graph models were constructed of the safety and dependability states of an automatic train operation system. The Markovian graph method of calculating the safety and dependability of complex systems was substantiated. That allowed defining such key safety indicators of an automatic train operation system as the mean time to wrong-side failure, probability of wrong-side failure, wrong-side failure rate. The study established that the safety of an automatic train operation system primarily depends on the dependability of machine vision facilities. The growth of the system’s wrong-side failure rate is limited to half the failure rate of machine vision facilities. It was also established that the dependability of an automatic train operation system is defined by the failure rate of a locomotive control and protection system and the failure rate of machine vision facilities. The conducted analysis allows concluding that in order to achieve an acceptable level of safety of an automatic train operation system, efforts should focus on machine vision redundancy, ensuring the SIL4 functional safety of on-board and trackside machine vision facilities, as well as regular comparison of the outputs of on-board and trackside machine vision facilities, redundant output comparison, integration of the outputs in motion. Additionally, adverse weather effects are to be countered by improving the efficiency of machine learning of the machine vision software.

Evaluation of the effect of JSC RZD transportation infrastructure availability on the risks of losses in the process of transportation

Aim. The availability of transportation infrastructure facilities affects the quality of the transportation services provided by JSC RZD. At the same time, this effect may significantly differ depending on the operating conditions of the transportation infrastructure or a specific railway line and can cause various degrees of risk of damage to the transportation process. Such risks are defined as risks of train-hour losses due to transportation infrastructure failures. Planning dependability management activities under conditions of scarce resources requires targeted identification of the transportation infrastructure facilities whose availability most significantly affects the magnitude of the risks of damage to the transportation process. The aim of the paper is to develop a method for evaluating daily availability and identifying its correlation with the risk of train-hour losses. Methods. The authors used the methods of risk management, probability theory and mathematical statistics, correlation and regression analysis. Results. The paper suggests representing the daily availability indicator of JSC RZD’s transportation infrastructure facilities as a two-parameter gamma distribution and describing its effect on the risks of the transportation process with a regression model. Conclusions. The paper’s findings can be used as part of transportation infrastructure dependability planning and targeted allocation of resources, as well as for substantiating the dependability indicator when evaluating the practical capacity of railway lines and utilization ratio and in a number of other operational tasks.

Improving the dependability of light vented foundations exposed to vibration load on frost soils

Aim. Today, dynamically-loaded foundations of process equipment often prove to be oversized with significantly overestimated values of stiffness, mass and material consumption. Therefore, reducing the costs and time of construction of gas pipeline facilities, especially on permafrost, is of relevance to PJSC Gazprom. One of the primary ways of solving this problem is installing gas pumping equipment on light vented support structures. The disadvantage of such structures is the low vibration rigidity. A method [1] is proposed for improving the vibration rigidity of a foundation subjected to vibration load. The simulation aims to improve the dependability of light vented foundations by studying vibration displacements of foundations with attached reinforced concrete panels depending on the thermal state of frost soils, parameters of the attached panels and connectors. Methods. Vibration displacements of a foundation with an attached device were identified using the finite element method and the improved computational model of the foundation – GCU – soil system. Results. Computational experiments identified the vibration displacements of the foundation in the cold and warm seasons for the following cases of reinforced concrete plates attached to the foundation: symmetrical and non-symmetrical; at different distances; through connectors with different stiffness parameters; with additional weights; frozen to the ground. Conclusions were made based on the results of simulation of vibration displacements of foundations with an attached device in cold and warm seasons. Conclusion. The presented results of computational experiments aimed at improving the vibration rigidity of light foundations by using method [1] show sufficiently good indicators of reduced vibration displacements of the foundation. Thus, in the case of symmetrical connection of four reinforced concrete panels in summer, the reduction of vibration displacements is 42.4%, while increased stiffness of the connectors, attachment of additional weights and freezing of reinforced concrete panels into the ground will allow reducing the vibration displacements of the foundation up to 2.5 times. However, it should be noted, that applying the findings in the process of development of project documentation and construction of foundations requires R&D activities involving verification and comparison of the obtained results of numerical simulation with a natural experiment.

On the classification of motive power failures

The Aim of the article is to develop a motive power failure classification to enable substantiated definition of dependability requirements for motive power as a part of a railway transportation system, as well as for organizing systematic measures to ensure a required level of its dependability over the life cycle. Methods. The terminology of interstate dependability-related standards was analysed and the two classifications used by OJSC “RZD” for estimating the dependability of technical systems and motive power were compared. The dependability of railway transportation systems is studied using structural and logical and logical and probabilistic methods of dependability analysis, while railway lines are examined using the graph theory and the Markov chains. Results. An analysis of the existing failure classifications identified shortcomings that prevent the use of such classifications for studying the structural dependability of such railway transportation systems as motive power. A classification was developed that combines two failure classifications (“category-based” for the transportation process and technical systems and “type-based” for the motive power), but this time with new definitions. The proposed classification of the types of failures involves stricter definitions of the conditions and assumptions required for evaluating the dependability and technical condition of an item, which ensures correlation between the characteristics of motive power and its dependability throughout the life cycle in the context of the above tasks. The two classifications could be used simultaneously while researching structural problems of dependability using logical and probabilistic methods and Markov chains. The developed classification is included in the provisions of the draft interstate standard “Dependability of motive power. Procedure for the definition, calculation methods and supervision of dependability indicators throughout the life cycle” that is being prepared by JSC “VNIKTI” in accordance with the OJSC “RZD” research and development plan. Conclusion. The article’s findings will be useful to experts involved in the evaluation of motive power dependability.

In memory of A.M. Zamyshliaev

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Intelligent methods for improving the accuracy of prediction of rare hazardous events in railway transportation

The paper Aims to examine various approaches to the ways of improving the quality of predictions and classification of unbalanced data that allow improving the accuracy of rare event classification. When predicting the onset of rare events using machine learning techniques, researchers face the problem of inconsistency between the quality of trained models and their actual ability to correctly predict the occurrence of a rare event. The paper examines model training under unbalanced initial data. The subject of research is the information on incidents and hazardous events at railway power supply facilities. The problem of unbalanced data is expressed in the noticeable imbalance between the types of observed events, i.e., the numbers of instances. Methods. While handling unbalanced data, depending on the nature of the problem at hand, the quality and size of the initial data, various Data Science-based techniques of improving the quality of classification models and prediction are used. Some of those methods are focused on attributes and parameters of classification models. Those include FAST, CFS, fuzzy classifiers, GridSearchCV, etc. Another group of methods is oriented towards generating representative subsets out of initial datasets, i.e., samples. Data sampling techniques allow examining the effect of class proportions on the quality of machine learning. In particular, in this paper, the NearMiss method is considered in detail. Results. The problem of class imbalance in respect to the analysis of the number of incidents at railway facilities has existed since 2015. Despite the decreasing share of hazardous events at railway power supply facilities in the three years since 2018, an increase in the number of such events cannot be ruled out. Monthly statistics of hazardous event distribution exhibit no trend for declines and peaks. In this context, the optimal period of observation of the number of incidents and hazardous events is a month. A visualization of the class ratio has shown the absence of a clear boundary between the members of the majority class (incidents) and those of the minority class (hazardous events). The class ratio was studied in two and three dimensions, in actual values and using the method of main components. Such “proximity” of classes is one of the causes of wrong predictions. In this paper, the authors analysed past research of the ways of improving the quality of machine learning based on unbalanced data. The terms that describe the degree of class imbalances have been defined and clarified. The strengths and weaknesses of 50 various methods of handling such data were studied and set forth. Out of the set of methods of handling the numbers of class members as part of the classification (prediction of the occurrence) of rare hazardous events in railway transportation, the NearMiss method was chosen. It allows experimenting with the ratios and methods of selecting class members. As the results of a series of experiments, the accuracy of rare hazardous event classification was improved from 0 to 70-90%.