High-speed Rolling Research Articles

DETERMINATION OF CHARACTERISTICS OF FATIGUE CRACKS GROWTH IN THE AXLES OF RAILWAY CARRIAGES

Providing damage resistance is the most important requirement presented to railway axles. This paper provides a detailed review of the characteristics of resistance to fatigue crack growth in axles made of EA4T steel (25CrMo4). This steel is typical for axles of high-speed rolling stock. Resistance to fatigue crack growth is defined by the nature of the Paris-Erdogan curve da/dN=CKm, the parameters of which are the coefficient C and the exponent m. Determination of these parameters is based on the results of fatigue tests with the samples or with full-scale axles having cracks. The analysis of numerous scientific papers has shown that for the specified steel there is a significant scatter in the values of these parameters. This scatter is caused by a number of factors, the main of which are: the difference in test objects (from small samples of the SE(B) type to full-scale rolling axles 190 mm in diameter); the difference in loading methods (tension-compression, flat bending, circular bending); the variation of mechanical properties of EA4T steel. In the paper the models of surface fatigue crack geometry are analyzed and semi-elliptical shape of crack front line is selected as the most acceptable. The significant scatter in the values of the parameters m and C prevents to establish reliably the residual life of axles with cracks, which is an important characteristic for practical forecasting of axle survivability. The technique for parameters m and C optimization in view of semi-elliptical shape of the crack front line has been developed. The relationship linking the parameters m and C has been established. The method for determining the residual life of the axle by the criterion of non-destruction is proposed. The dependence between the residual life and the value of the parameters of the Paris-Erdogan equation in the development of fatigue failure is established. The procedure for axles monitoring timeframes setting to prevent their fatigue failure is discussed. Keywords: parameters of Paris-Erdogan equation, fatigue crack, residual life of axle.

INFLUENCE OF ROLLING SPEED ON THE TEMPERATURE FIELD DURING COLD ROLLING OF ALUMINIUM SHEETS

One of the effects of plastic deformation is an increase in the temperature of the formed metal. The rolling pressure, friction stress, and contact state show different characteristics in different zones along the deformation zone, which causes the heat generation and transfer states to be different, so the strip temperature is subject to a complex change process. The paper presents the results of experimental temperature measurements at several points on the width of the rolled strip and on the surface of the working rolls depending on the rolling speed in the range of 0.5-4.0 m/s. The results obtained showed a clear dependence of both the strip temperature and the working roll temperature on the rolling speed, with the increase in strip temperature being more intense. At very high rolling speeds, the temperature of the rolled sheet may even exceed 1000C, which is unfavourable due to the possibility of the formation of deposits on the surface of the rollers.

Fault diagnosis of high-speed rolling bearing in the whole life cycle based on improved grey wolf optimizer-least squares support vector machines

Under the high-speed condition, the fault diagnosis of rolling bearing is difficult due to parameter limitation and local optimization. To solve these problems, a fault diagnosis method of the whole life cycle based on wavelet thresholding denoising, genetic algorithm-variational mode decomposition (GA-VMD) and improved grey wolf optimizer-least squares support vector machines (IGWO-LSSVM) is proposed. The nonlinear convergence factor is adopted to improve the global search ability of GWO, and then LSSVM is optimized by IGWO, which is used to improve the fault identification accuracy. Based on the high-speed rolling bearing test rig, this method is applied to fault diagnosis of high-speed rolling bearing in the whole life cycle. The kurtosis and approximate entropy indexes are adopted as the basis for the stage division in the degradation process. The fault diagnosis of rolling bearing in the whole life cycle is completed from the five aspects of data acquisition, stage division, data preprocessing, fault feature extraction and fault feature identification. The results show that the maximum identification accuracy of this method can reach 97 %.

Recent research advances on high-speed railway noise

Around 42,000 km high-speed railways are in operation in China at speeds up to 350 km/h. 400 km/h trains are also under development. Huge resources have been put into research on high-speed railway noise. This paper outlines advances achieved in several key projects by covering the following aspects: measurement results showing typical characteristics of high-speed railway noise; analyses on source contribution to pass-by noise based microphone array data; modelling of high-speed rolling, aerodynamic and viaduct bridge noise; prediction of the vibro-acoustic behaviour of car-body with poro-elastic media; and finally, analyses of vibration transmission in the suspension/bogie system.

Copper sulfides agglomeration using a novel lab-scale granulator: Integrated evaluation of bonding, leaching and mechanical behavior

The ore agglomerations could ameliorate intra-particle pore network, homogenize flow paths, and improve leaching efficiency of heap leaching. This paper innovatively develops a novel ore granulator with adjustable inclined angle and rolling speed. To comprehensively evaluate granulation procedure, the effects of physical (crushed feeds particle size distribution, rolling speed, inclined angle), chemical (binder type, curing time) and biological factors (bacterial concentration) on bonding performance of crushed feeds are analyzed. The objective of this paper is to obtain the optimal granulation conditions by studying the influence of various factors on the bonding ability, strength, and stability of granulated ores, in order to improve the pore structure of the heap leaching system, and increase the leaching rate of the ore. The results show that well-shaped agglomeration (WAs) does improve minerals leaching efficiency, and the uniaxial compressive strength of WAs is positively related to curing time, binder concentration, inclined angle, and rolling speed. The excessive lower or higher rolling speed is not suitable to get a higher extraction rate due to undesirable disintegration or compaction. The higher concentration (0.5–10 %) sulfuric acid solution could obviously increase WAs strength from 32.6 KPa to 48.3 KPa. The organic binders such as polyacrylamide are benefit for powders bonding and increase the compressive strength, but does not good for the desirable leaching reaction rate. The bacterial pre-adding has no significant positive influence on bonding and leaching efficiency. Relied on the 3D response surface, the preferred preparing condition is: 78.9 rpm rolling speed, 30° inclined angle, 7-days curing time and 9.3 % H2SO4 solution. Future studies should focus on exploring the intrinsic correlation between the various factors and evaluating the granulating and leaching effects from the perspective of chemical detection and leaching bacteria.

A Deep Neural Network-Based Optimal Scheduling Decision-Making Method for Microgrids

With the rapid growth in the proportion of renewable energy access and the structural complexity of distributed energy systems, traditional microgrid (MG) scheduling methods that rely on mathematical optimization models and expert experience are facing significant challenges. Therefore, it is essential to present a novel scheduling technique with high intelligence and fast decision-making capacity to realize MGs’ automatic operation and regulation. This paper proposes an optimal scheduling decision-making method for MGs based on deep neural networks (DNN). Firstly, a typical mathematical scheduling model used for MG operation is introduced, and the limitations of current methods are analyzed. Then, a two-stage optimal scheduling framework comprising day-ahead and intra-day stages is presented. The day-ahead part is solved by mixed integer linear programming (MILP), and the intra-day part uses a convolutional neural network (CNN)—bidirectional long short-term memory (Bi LSTM) for high-speed rolling decision making, with the outputs adjusted by a power correction balance algorithm. Finally, the validity of the model and algorithm of this paper are verified by arithmetic case analysis.

Influence of rolling speed on fatigue crack initiation and growth of wheel steel under dry-wet rolling/sliding contact

In order to examine the effect of rolling speed on rolling contact fatigue (RCF) of wheel steel, dry-wet rolling/sliding tests were carried out at varied rolling speeds. Wear loss, friction coefficient, crack morphology, and crack size distribution of test wheel discs were analyzed. Finite element (FE) analysis was subsequently performed to evaluate the RCF crack growth according to the max ΔKeq criterion. By combining the findings from both experimental and FE analyses, potential influences of rolling speed on RCF crack initiation and growth were postulated. It was discovered that the crack initiation is governed by the ratcheting mechanism under dry condition. As the rolling speed increases, the initiated crack size first increases and then decreases, probably due to the concurrent rising of friction coefficient and yield strength. Furthermore, the predicted crack growth paths using FE model with and without considering the trapped fluid are consistent with test results at lower and higher rolling speeds, respectively. The driving force of crack growth in depth and branching direction decreases with an increase in rolling speed, probably owning to the reducing hydrostatic pressure in the crack cavity induced by the increasing air volume. This ultimately results in smaller crack size and reduced wear loss under wet condition.

Ultrasonic measurement of roller revolution speed for high-speed rolling bearing

The sliding state of the bearing rollers can be identified by measuring the roller revolution speed. At present, the roller revolution speed is mainly approximated by the average speed of the cage, which can be obtained by optical and electric methods. However, there are some bottlenecks in the practical application of these methods. In this study, a non-destructive ultrasonic technique is proposed to measure the high-speed rolling bearings' roller revolution speed. In order to reduce the impact of time-domain noise on the ultrasonic echo pulse signal, autocorrelation analysis and the FFT transform are introduced. The passing frequency of a roller can be more accurately calculated by using the CZT (linear frequency modulation Z transform) spectrum thinning algorithm. This ultrasonic approach's validity is confirmed when compared to the conventional optical method at low speed. Then, in accordance with the theoretical models, the roller slippage at high speed is observed by directly measuring the speed of the roller revolution.

Effect of Al addition and rolling reduction on microstructure and texture evolution of Mg–3Sn alloy during high-speed rolling

Effect of Al addition and rolling reduction on microstructure and texture evolution of Mg–3Sn alloy during high-speed rolling

Анализ современных подшипниковых узлов, применяемых для высокоскоростного состава, и перспективы их развития

Purpose: To identify the main directions for increasing the service life and reliability of bearing assemblies for high-speed rolling stock. Methods: An analysis of modern bearing designs and new materials used in their manufacturing has been conducted. Results: The analysis of the conducted research has shown that all the examined designs of bearing assemblies produced by NSK company mainly meet the current demands of railways operating at speeds up to 320 km/h, and can ensure the safety of train movement under all existing operating conditions. Recommendations for equipping the axle box unit s of rolling stock with bearings that perform most successfully under special operating conditions have been developed. The issues of monitoring the faults of axle box units operating on high-speed trains, such as TGV, ICE, and Talgo, and the systems of their onboard diagnostics, have been addressed. An assessment of the domestic control system is provided, and its advantages over foreign counterparts are demonstrated. A solution for diagnosing trains under the ‘black box’ regime has been proposed. Practical significance: The application of modern bearing designs, new materials, and diagnostic systems allows for an increase in the reliability and performance of railway rolling stock.

High Speed Roll Casting of Al-5%Mg Strip at Semisolid Condition

Semisolid Al–Mg alloy strips were cast using high-speed twin-roll casting under very low roll loads to investigate the effect of low roll loads on surface cracking and center segregation of Mg. In the conventional twin-roll caster for aluminum alloys, the roll speed is usually less than 2 m/min, and the roll load is typically greater than 1 kN/mm to solidify the aluminum alloy and reduce casting defects. In the vertical type high-speed twin-roll caster, the roll speed can range from 10 to 90 m/min, and strips can be cast at roll loads below 500 N/mm, down to loads as low as 2 N/mm. Strips cast at 2 N/mm in this study did not completely solidify when released from the rolls; this means that the strips were semisolid. Al–Mg strips can be continuously cast without breaking when they are semisolid. The surface cracking and center segregation of these strips were compared with those of strips cast at a higher load of 88 N/mm. The effect of the small load on the presence of Mg at cross sections of the strip was investigated using etching with Weck’s reagent.

Optical High-Speed Rolling Mark Detection Using Object Detection and Levenshtein Distance

This paper presents an automated high-speed rolling mark recognition system for railroad rails utilizing image processing techniques. Rolling marks, which consist of numbers, letters, and special characters, were engraved into the rail web as 3D information. These rolling marks provide crucial details regarding the rail manufacturer, steel quality, year of production, and rail profile. As a result, they empower rail infrastructure managers to gain valuable insights into their infrastructure. The rolling marks were captured using a standard color camera under dark field illumination. The recognition of individual numbers, letters, and special characters was achieved through state-of-the-art deep neural network object detection, specifically employing the YOLO architecture. By leveraging reference rolling marks, the detected characters can then be accurately interpreted and corrected. This correction process involves calculating a weighted Levenshtein distance, ensuring that the system can identify and rectify partially misidentified rolling marks. Through the proposed system, the accurate and reliable identification of rolling marks was achieved, even in cases in which there were partial errors in the detection process. This novel system thus has the potential to substantially improve the management and maintenance of railroad infrastructure.

Wheel Speed Effect on Transient Lateral Force and Its Characterization by Ramp-Step Steer Test Method

ABSTRACT The concept “relaxation length” serves as one of several ways to characterize the transient lateral response for a rolling tire. Most test methods developed to identify relaxation length tightly link to Pacejka’s single-contact-point linear transient model. Its underlying assumption is that the traveled distance during the transition interval is always a constant regardless of the wheels’ linear rolling speed. The current research provides physical data against this strong assumption. The data is acquired through a newly-developed test method named the “ramp-step steer method”. The ramp-step steer method features a nonstop, high rolling speed, and fast-changing slip angle procedure that cannot be fulfilled by the conventional “start-stop-resume” step steer method. Thanks to the high dynamic capability of the equipment in GCAPS Corp., the proposed test method becomes feasible. A novel data postprocessing scheme accompanies the test method as well. The ramp-step steer method is independent of any specific models and replicates the scenario of a rolling tire subjected to a sudden slip angle change from on-vehicle to an indoor environment. The wheel speed effect on the tires’ transient lateral response is reflected through a proposed quantity, Ly, which is a more general descriptor and can downscale to relaxation length under specific circumstances. Ly itself does not associate with any model, so the remaining study explains the speed effect through an updated model. The present research aims to provide a better way of characterizing tires’ lateral transient behavior and is not an alternative to identify the key parameter “relaxation length” in Pacejka’s model. Another contribution of the research is categorizing and separating the hierarchy of various transient tire models.

Particularities of the formation of the air masses structure in the tunnel during the train movement

The effect of aerodynamic factors on the rolling stock and railway infrastructure has been analysed. The formation of air mass structure in tunnel structures during the movement of high-speed rolling stock has been investigated. The processes of aeroelastic interaction of rolling stock with tunnel portal structures are analysed by means of numerical simulation. The description of mathematical models and the ways of their three-dimensional realization in the Solid Works Flow Simulation software complex are presented. Methods of finite elements and volumes for the solution of the set tasks are used. The results of the numerical research of velocity fields near the tunnel portal area obtained with the help of the developed mathematical models for the cases of entry and exit of the rolling-stock into the tunnel are given. The complex structure of air masses formation in the gap between the train body and tunnel lining which leads to increased resistance to the train movement in the tunnel is revealed. The patterns in the changes of pressure dynamics on the surface of the head fairing when the train enters the tunnel are found. The fact of negative effect of high and low pressure zones, as well as their abrupt difference, on the locomotive crew and passengers has been established.

Применение машинного обучения для анализа технических характеристик и параметров эксплуатируемого подвижного состава на высокоскоростных железнодорожных магистралях

Purpose: Machine learning is one of the most popular technologies at the present time, which finds application in various industries. One such industry is rail transport, where machine learning can significantly improve the management of locomotives and electric trains. The article is devoted to the study of the possibility of using machine learning to analyze the technical characteristics and parameters of the rolling stock using electric trains operating on high-speed railway lines as an example. The article discusses machine learning mechanisms for data analysis, as well as offers practical recommendations for using machine learning for data analysis on railway transport. Methods: The k-means method is one of the most popular machine learning algorithms for clustering, which allows to split a dataset into k similar groups or clusters. The algorithm is based on finding the centroids (mean values) of each cluster and assigning objects to the cluster that has the closest centroid. Depending on the choice of the initial values of the centroids and the parameters of the algorithm, the partitioning of data into clusters can be different. In addition, k-means is a relatively easy-to-implement and efficient clustering algorithm that can be used as an initial estimate for more complex clustering algorithms; The linear regression method is a statistical algorithm used to determine the relationship between two continuous variables. The algorithm uses a linear function that describes the relationship between the dependent variable and one or more independent variables. Results: Algorithm for processing and primary analysis of the characteristics and parameters of high-speed rolling stock, the results of parameter clustering, a technique for predicting the technical characteristics of prospective high-speed rolling stock. Practical significance: The methods of application of machine learning for the analysis of technical characteristics and parameters of the operated rolling stock on high-speed railway lines are shown. The methods will allow to substantiate and predict the necessary characteristics when developing technical requirements for high-speed transport in Russia. Using machine learning, it is possible to improve the accuracy of calculating the technical and economic models of high-speed highways, and further reduce the cost of operating rolling stock.

The Friction of Radially Loaded Hybrid Spindle Bearings under High Speeds

Friction losses are an important parameter for evaluating the operational behaviour of high-speed rolling bearings. Specifically, in machine tool applications, the bearings are subjected to high radial loads and high speeds, which lead to increased forces in the rolling contact and, as a result, increased bearing friction. In this high-speed application, hybrid spindle bearings, typically made of ceramic balls and steel raceways, show better frictional behaviour compared to full steel-made bearings. Therefore, precise knowledge of the friction characteristics of high-speed hybrid bearings can improve friction models and generalise them to spindle bearings with different types, geometries, and operating conditions. In this article, a new straightforward and cost-efficient method for measuring the frictional torque in spindle bearings is presented. A rigidly arranged 7008 hybrid spindle bearing pair was tested up to rotational speeds of 24,000 rpm and high radial loads of 3 kN. The effects of oil–air and grease lubrication are discussed in characteristic diagrams of the tested bearings. Then, based on the test results, a friction calculation model is presented and validated for the outer race control and minimised power dissipation regarding the influence of radial forces.

Effect of clearance on the dynamic characteristics of high-speed rolling bearings with multiple defects

Clearance is a pivotal factor in determining the fatigue life of high-speed rolling bearings (HSRBs). As HSRBs naturally experience various defects, their clearance levels tend to rise. However, a clear understanding of the vibration caused by clearance is still lacking. To address this gap, a five-degree-of-freedom dynamics model for HSRBs is proposed. This model accounts for centrifugal force, gyroscopic moment, and time-varying contact angle. In addition, the proposed model incorporates asymptotic theory to describe the defect process and the time-varying contact force derived from the Hertzian point contact theory between rolling elements and raceways. Furthermore, the model considers the variations in load zone and rolling element velocity that arise due to clearance. Applying this model, the dynamic response of HSRBs with different level clearances is calculated. The model's correctness is verified by comparing the dynamic response with the finite element model results and data measured using a test rig built for aero-engine spindle bearing. The results demonstrate that the extent of the load zone shrinks as the clearance increases, although the reduction rate gradually slows down. Since the bearing is loaded only in the load zone, aggravated clearance causes rolling elements to slip in the non-load zone. The effect of clearance on contact force is significantly weaker pronounced than that of defects. These research findings provide a theoretical foundation for the analysis and performance prediction of HSRBs and have important reference values for their optimal design.

Microstructure evolution and mechanical properties of Mg-3Al-3Sn-1Zn alloy during multi-pass high-speed rolling

The microstructure evolution and mechanical properties of as-homogenized Mg-3Al-3Sn-1Zn (ATZ331) alloy with an initial grain size of ∼126.7 µm are studied during multi-pass high-speed rolling (HSR) process. The main deformation mechanism governing the microstructure is comprised of twinning and dislocation migration, Firstly, high dislocation density and twinning generated during HSR. Then, the dislocations are rearranged and incorporated as subgrain boundaries (sub-GBs), leading to a reduction of grain size with an increase in rolling pass. Results show that a fine and uniform microstructure (1.1 µm) of HSRed ATZ331 is achieved after the sixth pass, with a yield strength (YS), ultimate tensile strength (UTS), and elongation to failure (FE) of 319 MPa, 360 MPa, and 5.9 %, respectively. After being subject to HSR, low-temperature short-time annealing is carried out in order to improve ductility, which has proven to bring about sufficient static recrystallization (SRX). The SRX mechanism of ATZ331 alloy after HSR processing is found to consist of the classical recovery followed by recrystallization. Subgrains are formed by the realignment and absorption of the accumulated dislocations, which is followed by the migration of low angle grain boundaries (LAGBs) and their transformation into high angle grain boundaries (HAGBs). Finally, the sample with fine average grain size (1.7 µm) is achieved. Furthermore, the YS, the UTS, and the FE of ATZ331 are 253 MPa, 313 MPa, and 9.8 %, respectively.

Recent advances on research into high-speed railway noise

Abstract Around 42,000 km high-speed railways are in operation in China with a maximum speed of 350 km/h. Trains which can run at 400 km/h are also under development. To control both train pass-by and train interior noise, huge resources have been put into research on high-speed railway noise, and the authors of this paper and their teams have been involved in several key projects. This paper is to summarise some of the advances achieved in these projects by covering the following topics: measurement results and characteristics of high-speed railway pass-by noise; analyses on source contribution to pass-by noise based on microphone array measurement; modelling of high-speed rolling, aerodynamic, and viaduct bridge noise; prediction of the vibro-acoustic behaviour of car-body with poro-elastic media; analyses of vibration transmission in the suspension/bogie system; statistical energy analysis-based prediction of train interior noise. Open problems and potential technologies for controlling high-speed railway noise are also discussed.

Multidiscipline Design Optimization for Large-Scale Complex Nonlinear Dynamic System Based on Weak Coupling Interfaces

For high-tech manufacturing industries, developing large-scale complex nonlinear dynamic systems must be taken as one of the basic works, formulating problems to be solved, steering system design in a more preferable direction, and making correct strategic decisions. By using effective tools of big data mining, Dynamic Design Methodology was proposed to establish a technical platform for Multidiscipline Design Optimization such as High-Speed Rolling Stock, including three key technologies: analysis graph of full-vehicle stability properties and variation patterns, improved transaction strategy of flexible body to MBS interface, seamless collaboration with weldline fatigue damage assessments through correct Modal Stress Recovery. By applying the above methodology, a self-adaptive improved solution was formulated with optimal parameter configuration, which is one of the more favorable options for higher-speed bogies. While within a velocity (140–200) km/h at λe < 0.10, car body instability’s influence on ride comfort can be easily improved by using a semi-active vibration reduction technique between inter-vehicles through outer windshields. Comprehensive evaluations show that only under rational conditions of wheel-rail matching, i.e., 0.10 ≥ λeN > λemin and λemin = (0.03–0.06), can this low-cost solution achieve the three goals of low track conicity, optimal route planning, and investment benefit maximization. So, rail vehicle experts are necessary to collaborate and innovate intensively with passenger transportation and steel rail ones. Specifically, by adopting rail grinding treatment, occurrence probability is controlled at 85% and 5% for track conicity of (0.03–0.10) and (0.25–0.35). By optimizing routing planning, operating across dedicated lines of different speed grades can achieve self-cleaning of central hollow tread wear over time. According to the inherent rigid-flex coupling relationship, geometric nonlinearities of worn wheel-rail contact should be avoided as much as possible for HSR practices. Only under weak coupling interfaces in the floor frame can the structural integrity of an aluminum alloy car body be ensured.