System and method for monitoring the state of a wheel of a railway vehicle
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- KNORR BREMSE SYST FUR SCHIENENFAHRZEUGE GMBH
- Filing Date
- 2021-10-04
- Publication Date
- 2026-06-19
Smart Images
Figure CN116507546B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a system and method for monitoring the condition of the wheels of a rail vehicle, particularly during the operation of a rail vehicle. Background Technology
[0002] During braking, the wheels of a rail vehicle bear intense loads. Damage to the wheels, such as from intense friction or sudden and excessive heating of the material, must be avoided. This is particularly challenging when braking very forcefully, especially in areas with poor ground adhesion. This situation is more common, for example, in regions exposed to maritime climates, especially with high humidity and the accompanying poor adhesion between the wheels and the rail.
[0003] Systems for preventing wheel lock-up or slippage during braking are known. Therefore, for example, flat areas are avoided on the otherwise circular periphery of the wheel. However, under adverse conditions, damage to the wheel or adverse changes in the material, such as those associated with the formation of martensite in the wheel material, can occur. Some areas of metal wheels, particularly on the rolling surfaces where the material has become martensitic, are harder and more brittle than the surrounding material and are therefore often the starting point for surface cracks and material loss.
[0004] It is known that non-destructive testing can be used to inspect the working wheels at regular intervals and remove damaged material if necessary, for example, with the aid of a lathe.
[0005] For example, a method for detecting cracks in wheel assemblies of rail vehicles is known from EP 3 517 927 A1.
[0006] In addition, DE 198 33 027 C1 describes a method for testing railway wheels.
[0007] In addition, an apparatus for performing electromagnetic and ultrasonic diagnostics in wheels is known from EP 1 485 704 A1.
[0008] In addition, EP 3 206 933 A1 describes a method for condition diagnosis of wheels for rail vehicles. Summary of the Invention
[0009] The object of the present invention is to further improve a system and method of the type described at the beginning in an advantageous manner, in particular, to enable the identification of critical structures and / or initial formation of cracks in the material of the wheel.
[0010] According to the present invention, the task is accomplished by a system for monitoring the condition of the wheels of a rail vehicle.
[0011] According to this regulation, a system for monitoring the state of wheels of a rail vehicle includes: a detection unit configured to detect at least one operating parameter of the wheel during a braking event; an evaluation unit configured to determine a temperature value of the wheel based on the detected operating parameter; and a control unit configured to generate and output an output based on the determined temperature value; wherein the temperature value determined for the wheel includes the average temperature of the rolling surface of the wheel and the temperature distribution along the rolling surface of the wheel and the temperature at the contact surface of the wheel, and the detection unit is further configured to detect braking parameters, wherein the operating parameters detected for the wheel include wheel speed and / or the speed of the rail vehicle, and / or the operating parameters detected for the wheel include the time derivative of the wheel speed and / or the time derivative of the speed of the rail vehicle.
[0012] This invention is based on the fundamental concept of identifying tissue changes in a wheel while it is still in operation, through temperature monitoring or thermal monitoring. Essentially, the tissue diagram is known and can be stored in the system. If, through thermal monitoring, and perhaps also through the time history of temperature (i.e., monitoring temperature curves) and corresponding comparisons, or through monitoring temperature curves alone without comparison, it is identified that a problematic tissue change has occurred, is likely to occur, or is concerning, then a corresponding warning message is output.
[0013] This provides advantageous parameters for the condition and safety of the wheel, as well as for its maintenance. Furthermore, costs can be optimized during maintenance by using particularly costly methods in a targeted manner. Additionally, maintenance work can be advantageously planned and implemented as needed rather than at fixed intervals; this avoids unnecessary maintenance work. Moreover, the wheel can still be processed on a lathe before cracks can form and propagate in the material.
[0014] In particular, the condition of the wheels can be monitored during the continuous operation of the rail vehicle. This is a significant difference from known methods, in which monitoring is performed at predetermined time intervals and the rail vehicle must be transported to, for example, a workshop. In this invention, data detected during braking events is directly evaluated, and conclusions about the wheel condition can be directly output.
[0015] Thus, monitoring or diagnostics can be performed in this invention to identify the formation of martensite and / or other indications regarding the formation of cracks or fracture sites. Furthermore, the presence of a risk of material weakening can be identified. Additionally, the diagnostics can be used to detect the occurrence of hazards after braking under adverse adhesion properties.
[0016] The basic concept of this invention is to determine the probability of martensite formation in the wheels of rail vehicles. This information is then used to identify whether to notify the wheel to be inspected, for example, using non-destructive testing methods; and / or whether the wheel needs to be treated, for example, using a lathe.
[0017] The following is utilized here: In modern rail vehicles, a large number of parameters are frequently detected, which can be used to determine the energy present at the contact point between the wheel and the rail. In particular, the system utilizes the following: the speed of the wheel and the speed of the rail vehicle, i.e., the reference speed, can be detected. These values have been used, for example, to identify or prevent wheel slippage. For example, a wheel slide protection (WSP) system or a similar system can be used. Furthermore, values detected by the brake control unit (BCU), such as the braking pressure applied by the brake cylinder, can also be used.
[0018] The speed of the wheels and the vehicle, as well as the cylinder pressure of the braking system, can be used in a simplified thermal model of the material of the wheel's rolling surface, particularly to determine the temperature distribution within the material. Such a model can be performed by an evaluation unit.
[0019] To simulate temperature rises and / or falls in materials as realistically as possible—for example, to calculate the peak temperature at a location on the wheel per revolution—a more detailed thermal model of the wheel's rolling surface material is needed, perhaps for simulation using the finite element method. Calculations based on such a model can require significant computational power and can be very time-consuming. This typically precludes the use of such a detailed model in evaluation units directly within the vehicle. Instead, it can be specified that tables and / or characteristic curves with temperature values are determined based on a more detailed thermal model outside the rail vehicle, and the system then accesses these tables and / or characteristic curves; for example, the tables and / or characteristic curves can be stored in the system's storage units.
[0020] Therefore, the average temperature of the wheel can be calculated in the system using a simplified thermal model, and locally occurring peaks can be identified by looking up values in a table, where the values have been determined with greater computational cost and using a more expensive model. Specifically, the peaks determined according to the table are added to the average temperature. The time-temperature curve obtained in this way can be compared with material-specific curves describing conditions for certain changes in the metal microstructure.
[0021] It is possible to examine multiple conditions used to produce a defined critical point or material change, especially conditions that are progressively built upon each other.
[0022] For example, it can be first determined whether sufficient conditions exist for the formation of austenite, such as a temperature rise within a defined time. Furthermore, it can be determined whether subsequent cooling is sufficiently rapid for the formation of martensite.
[0023] In particular, the probability of martensite formation can be determined. Specifically, the probability can be determined for a specific wheel, a pair of wheels, or a wheel set with different definitions.
[0024] For example, error codes can be generated, output, and / or stored, the error codes including a determined probability of martensite forming in the wheel.
[0025] In one configuration of the system, the detection unit is further configured to detect braking parameters, particularly the braking pressure and / or braking force of the brake cylinder.
[0026] This allows for the advantageous, particularly simple, and direct determination of the energy that must be dissipated during braking through contact between the wheels and the rails. Furthermore, these operating parameters are typically readily accessible via the rail vehicle's brake controller.
[0027] In another configuration, the operating parameters detected for the wheels include wheel speed, particularly wheel rotation speed and / or the speed of the rail vehicle.
[0028] Therefore, the kinetic energy to be absorbed during braking can be determined easily and advantageously based on the fundamental parameters of rail vehicle operation. Furthermore, it can be checked whether the wheels lock up or continue to rotate during braking. In particular, these values can be easily detected using commonly available control devices, such as those used to prevent wheel slippage during braking.
[0029] In a further improvement, the operating parameters for wheel detection include the time derivative of wheel speed, particularly the time derivative of wheel rotation speed, and / or the time derivative of rail vehicle speed. Specifically, primary and / or multiple time derivatives of wheel speed, particularly primary and / or multiple time derivatives of wheel rotation speed, and / or primary and / or multiple time derivatives of rail vehicle speed can be detected.
[0030] Thus, the dynamics of braking events can be detected in a particularly simple and advantageous manner, and the energy present can be easily determined.
[0031] In one configuration, at least one operating parameter of the wheel can be detected using an anti-skid system. For example, the anti-skid system includes a detection unit, or the anti-skid system can function as a detection unit.
[0032] Therefore, the feasibility of existing and known anti-skid systems can be advantageously used to detect operating parameters, for example, by integrating them into the braking control system of rail vehicles. This allows the system to operate with particularly high efficiency. Furthermore, the system can be integrated particularly easily into existing rail vehicles, as in the best-case scenario, no new sensor devices need to be installed.
[0033] This means that the rail vehicle has a wheel slide protection system (WSP) that detects the wheel's operating parameters. Furthermore, it can be specified that at least one of the multiple operating parameters detected for the wheel is detected by the wheel slide protection system.
[0034] Typically, WSP systems are designed to detect wheel speed, vehicle speed, and / or braking pressure. Therefore, this existing data can be acquired particularly easily.
[0035] In a further configuration, the temperature values determined for the wheel include the average temperature of the wheel rolling surface and / or the temperature distribution along the wheel rolling surface and / or the temperature at the wheel contact surface. Specifically, it is determined whether the wheel continues to rotate during a braking event, or whether the wheel locks up and slides on the track.
[0036] Therefore, it is advantageous to directly determine whether specific temperature-related damage on the wheel can be identified. In particular, phase changes or structural changes may occur when materials are heated and / or cooled, which, for example, promote the formation of expanded damaged areas, such as cracks.
[0037] In a further improved embodiment, the evaluation unit is configured to determine the average temperature of the wheel rolling surface when determining the temperature value of the wheel based on a simplified thermal model, and to determine the temperature peak value based on a lookup table.
[0038] Thus, analytical methods that can be performed with investigable computational costs are combined with more computationally expensive simulation methods in an advantageous manner.
[0039] The simplified thermal model enables the determination of the average temperature of the rolling surface in real time with sufficient accuracy based on detected operating parameters. For example, this analysis can be performed using the computing unit within the rail vehicle itself.
[0040] Determining potential temperature peaks during braking typically involves computationally intensive methods and is therefore generally not feasible in real-time, at least not with the typical onboard resources of rail vehicles. Therefore, simulations can be used to determine values under different conditions and store them in a lookup table. The evaluation unit is then configured to determine and apply one or more values from the lookup table that match the currently detected operating parameters. In this case, the lookup replaces entirely new calculations and allows for sufficiently accurate results.
[0041] In particular, the temperature at the contact surface between the wheel and the track can be determined using a simplified thermal model.
[0042] In one configuration, the control unit is configured to generate an output based on reaching at least one temperature threshold. Alternatively, the output can be generated based on changes in detected operating parameters over time. Optionally, the control unit is also configured to determine the probability of a damaged area appearing, particularly the probability of martensite formation, and generate the output based on at least one probability threshold.
[0043] Thus, the potential problems with the wheels are pointed out in a favorable manner.
[0044] For example, it is possible to analyze the probability of certain damage caused by specific conditions defined based on detected operating parameters. The output could then include information about the expected probabilities of which problems will occur, and targeted countermeasures, such as specific maintenance measures, can be taken.
[0045] In a further configuration, the output includes warning messages and / or diagnostic messages and / or error codes. Here, the control unit may optionally be configured to store the output in a diagnostic memory.
[0046] This allows the output to be read out later, for example, by an authorized user.
[0047] Furthermore, the output can be directly output. For example, an optically or acoustically perceptible signal can be generated based on the output. For instance, if the output includes a defined error code, a first signal can be output, while if the output includes another error code, a second signal can be output.
[0048] For example, this signal can be used to output requirements for specific maintenance measures.
[0049] In a method for monitoring the state of wheels of a rail vehicle, at least one operating parameter of the wheel is detected during a braking event, a temperature value of the wheel is determined based on the detected operating parameter, and an output is generated and output based on the determined temperature value. The temperature value determined for the wheel includes the average temperature of the rolling surface of the wheel, the temperature distribution along the rolling surface of the wheel, and the temperature at the contact surface of the wheel. Braking parameters are also detected, and the operating parameters detected for the wheel include wheel speed and / or the speed of the rail vehicle, and / or the operating parameters detected for the wheel include the time derivative of the wheel speed and / or the time derivative of the rail vehicle speed.
[0050] The method is specifically configured as an operating system. Therefore, the method has the same advantages as the system. Attached Figure Description
[0051] Figure 1A An embodiment of the system is shown.
[0052] Figure 1B An embodiment of the method is shown.
[0053] Figure 2A and Figure 2B A schematic diagram of the wheel under different braking conditions is shown.
[0054] Figure 3 The time-temperature graph is shown.
[0055] Figure 4 A cross-sectional view of the wheel and track is shown.
[0056] Figure 5 The characteristic curves related to the formation of austenite are shown.
[0057] Figure 6 The characteristic curves related to the formation of martensite are shown. Detailed Implementation
[0058] Figure 1A An embodiment of the system 100 according to the present invention is shown.
[0059] In the illustrated embodiment, system 100 is integrated into rail vehicle 10 or a subsystem of rail vehicle 10.
[0060] Therefore, the rail vehicle 10 has a system 100.
[0061] The system has a detection unit 20.
[0062] The detection unit 20 is a component of the anti-slip device 30, which is configured as a WSP (wheel slide protection system) system in a manner known per se.
[0063] System 100 also has an evaluation unit 40.
[0064] System 100 also has a control unit 50.
[0065] The detection unit 20 is configured to detect at least one operating parameter of the wheel during a braking event.
[0066] In addition, the detection unit 20 can be configured to detect the existence of the braking event itself, for example by detecting the activity of the brake cylinder.
[0067] The evaluation unit 40 is configured to determine the temperature value of the wheels of the rail vehicle 10 based on the detected operating parameters.
[0068] The control unit 50 is configured to generate and output an output based on a determined temperature value.
[0069] The functions of System 100 can be basically described as follows:
[0070] Using data detected by detection unit 20, evaluation unit 40 performs temperature monitoring based on said data. Specifically, it determines the temperature present in the wheel during a braking event or the temperature development over time. This thermal monitoring identifies the presence of conditions for specific tissue changes in the wheel during the continuous operation of the rail vehicle 10. For this purpose, tissue diagrams, which are known per se, are used in particular.
[0071] If it is determined that there are conditions for constructing the problematic transformation, then the corresponding output can be generated.
[0072] System 100 can achieve the following advantages:
[0073] The critical state of the wheels can be identified during the continuous operation of the rail vehicle 10, and the safety of operation can be improved.
[0074] Such critical states can be indicated, particularly those directly related in time to the occurrence of the critical state and / or at a later point in time.
[0075] In addition, maintenance or repair measures can be arranged, for example, to eliminate damage to the wheels that has occurred or is of concern during braking events.
[0076] In addition, maintenance or preventative measures can be arranged to prevent damage before it occurs.
[0077] In addition, maintenance work can be performed as needed to avoid unnecessary measures.
[0078] Figure 1B An embodiment of the method explained below is shown. Here, the starting point is particularly referenced above. Figure 1A The embodiments of the system explained are described in more detail below.
[0079] In particular, a diagnostic method that can be executed by a computer device is shown here.
[0080] In step S10, at least one operating parameter of the wheel is detected during a braking event.
[0081] Here, in this example, the force at the contact surface between the wheel and the track is determined.
[0082] Detect data about wheel speed.
[0083] In addition, the braking force of the braking equipment of the rail vehicle is tested here.
[0084] In particular, this embodiment specifies that the control unit of the anti-slip device (WSP) processes the detected operating parameters and data.
[0085] Determine the energy absorbed by the wheel through the contact surface.
[0086] For example, braking force and wheel speed These can be parameters that appear here, which are respectively related to time t and are detected in particular based on time t.
[0087] In step S20, a simplified thermal model of the wheel is used. The check examines whether the wheel rotates during braking or locks up and slips on the track (wheel lock-up). Specifically, the values detected or determined in step S10 are used in the model.
[0088] Based on a simplified model, if the wheel rotates during braking, the average temperature of the wheel's rolling surface is determined according to time t. .
[0089] Based on a simplified model, if the wheels lock up during braking, the temperature of the contact area between the wheel's rolling surface and the rail is determined according to time t. .
[0090] In step S30, the temperature determined using a simplified model is modified. .
[0091] Here, we use the parameters previously determined through simulation using the FEM method. These parameters are provided, for example, by the storage cells.
[0092] Here, the modified time is determined based on time t. .
[0093] In step S40, the temperature thus determined is... A comparison is made with a predetermined graph that includes characteristic curves that characterize the prerequisites for austenitization of the material used for the wheel or its rolling surface.
[0094] exist Figure 5 Figure 500 shows an example that can be used in step S40.
[0095] In particular, this step checks whether austenitization has been performed. If the result is "no," then in step S70 it is determined that there is no risk of martensite formation.
[0096] However, if it is determined in step S40 that a prerequisite for austenitization exists, then the determined temperature is then applied in step S50. The comparison is made with another predetermined chart, which includes characteristic curves that characterize the prerequisites for the formation of martensite in the material of the wheel or its rolling surface.
[0097] exist Figure 6 Figure 600 shows an example that can be used in step S50.
[0098] In particular, this check examines whether there are any prerequisites for martensite formation, especially if the material cools sufficiently quickly. If the answer is "no," then in step S70 it is determined that there is no risk of martensite formation.
[0099] However, if it is determined in step S50 that there are prerequisites for martensite formation, such as sufficiently rapid cooling, then it is then determined in step S60 that there is a risk of martensite formation.
[0100] In the method, an output is then generated and output. The output may include, for example, an error code indicating whether a risk of martensite formation exists.
[0101] In another embodiment of the method, the probability that martensite has formed is also determined in step S60. The generated output may include this probability.
[0102] Similarly, in another embodiment of the method, alternatively or additionally, the probability that martensite has formed can be determined in step S70. The generated output may include this probability.
[0103] In particular, a threshold can be predetermined, and a determined value representing the probability of martensite formation can be compared to the threshold. An output can then be generated based on this comparison. For example, a warning message can be generated and output when the threshold has been exceeded.
[0104] In particular, an integrated sensor is provided in the anti-slip device 30, which is used to prevent the wheels from slipping on the track.
[0105] The detection unit 20 may include, for example, a sensor of the MGS3 type.
[0106] The values and parameters detected by the detection unit 20 allow for the determination of instantaneous heat on the wheel surface in real-time or near real-time. Even with current anti-skid devices (WSP, "wheel slide protection"), wheel overload cannot be prevented in all situations, especially due to the input of energy or heat during braking. However, based on the data detected by the anti-skid device, slippage can be detected and / or the duration of the slippage process of the wheel or wheelset can be determined. Based on a suitable thermal model of the wheel and the known material properties of the wheel, it can be determined whether and how transitions occur between different material states, such as between different microstructures or phases in metallic materials.
[0107] Typically, large areas of particularly hardened material are prone to cracking or spalling. To prevent this, diagnostic memory can be read at regular intervals, such as monthly, or on specific occasions, such as during regular wheel or wheelset maintenance. Based on the data stored in the diagnostic memory, it can be determined whether the wheel should be machined. Furthermore, it can be determined that machining is unnecessary. Additionally, based on the data stored in the diagnostic memory, it can be determined that non-destructive diagnostics, such as using ultrasound, should be performed on the wheel or wheelset to detect cracks and / or localized changes in material hardness.
[0108] Figure 2 to Figure 6 Further exemplary details of the system and method are shown below.
[0109] The following describes an exemplary model that can determine the formation of textured microstructures in potentially hardened materials. In particular, it can determine the formation of martensite and / or the probability that martensite has already formed during a braking event.
[0110] The wheel speed, vehicle speed, and braking pressure applied through the brake cylinder are detected by sensors included in the detection unit.
[0111] A simplified thermal model is employed, which is provided, for example, by means of an evaluation unit.
[0112] A simplified thermal model can be provided, for example, on the computing unit and / or insert card of the central control unit.
[0113] For example, first determine the energy absorbed by the wheel, for instance, based on the following model, referencing Figure 2A and Figure 2B as well as Figure 4 Explanation of the model:
[0114] To calculate the energy absorbed by the wheelset, for example for a wheelset with four wheels i=1, 2, 3, 4, the sliding speed is multiplied by the actual braking force at the contact point between wheels 210, 420 and track 440.
[0115] The contact force is determined based on the pressure of the brake cylinder. Furthermore, the angular acceleration of the wheel assembly is also considered, where J represents the moment of inertia of the wheel.
[0116]
[0117] Here, This indicates the braking force, which is applied to individual wheels 210 and 420 at the contact surface between the wheels 210 and 420 and the track 440. This is the actual braking pressure. A direct function. This function It can be determined, for example, based on general calculations of the braking process, as described in, for example, UIC544-1.
[0118] There is a WSP system that directly determines the force by detecting the actual acceleration of the wheel assembly, so that the acceleration can be used directly.
[0119] The surface temperature can then be determined, where, in particular, it can be considered that approximately 50% of the heat can be rapidly distributed in this situation, i.e., approximately 50% of the generated heat is absorbed by the wheel. This is described, for example, in P.T. Zwierczyk's "Thermal stress analysis of a railway wheel-rail rolling-sliding contact" (Budapest, 2015). In other models, different distributions can be started from, for example, based on determined environmental parameters.
[0120] A simplified thermal model of wheels 210 and 420 can be determined.
[0121] In the simplified thermal model, two states are particularly distinguished:
[0122] a) If wheels 210 and 420 do not rotate, i.e., if the wheels lock up, it is assumed that energy is absorbed through the contact point or contact area 230 between the wheel surface and the track. This situation is particularly relevant. Figure 2A As shown in the image.
[0123] b) If wheels 210 and 420 rotate, it is assumed that energy is uniformly absorbed at the contact point between the surfaces of wheels 210 and 420 and the track 440 through the rolling surface 230 of wheels 210 and 420. This is particularly true in... Figure 2B As shown in the image.
[0124] In a modification of the case explained in b), it is also considered that heat is absorbed at a point on the contact surface between wheels 210, 420 and track 440, and then released during further rotation of wheels 210, 420 until the point comes into contact with track 440 again.
[0125] Figure 3 An example of a temperature history curve determined according to the modified model is shown: at the peak of the temperature, the observed point on the rolling surface of wheels 210, 420 contacts track 440 and absorbs heat, then the contact disengages and the point cools down. The average temperature of the wheels is shown as a dashed line, and the temperature with additional peaks is shown as a solid line.
[0126] exist Figure 2A The model shown in the image depicts the situation where the wheels are rotating; while... Figure 2B The image shows wheels 210 and 420 locked up, with wheels 210 and 420 sliding on track 440.
[0127] In use Figure 2A In the model shown, This indicates the temperature of the rolling surface, especially the average temperature.
[0128] In the example described, the mass of the rolling surface 220 is pre-calculated. Here, for example, the Kalker method can be used, where the radius of the wheel 210 and the width of the surface 220 are specifically determined for the vehicle. Furthermore, the depth of the rolling surface can be calculated based on simulation.
[0129] For example, the following expression can be derived:
[0130]
[0131]
[0132] In addition, it can be used for Figure 2B The temperature at contact point 230 is determined in the model shown. For example, the area of contact point 230 can be considered to be approximately 1. The area and the depth are 2mm.
[0133] This area can be calculated specifically for vehicles. For example, the Kalker method can be used. Furthermore, the depth of the rolling surface can be calculated based on simulations.
[0134] For example, the following expression can be derived:
[0135]
[0136]
[0137] Or simplified to:
[0138]
[0139] Figure 3 This illustrates an example of how the temperature changes at a point in the rolling surface region of wheels 210 and 420 during braking as they rotate during the braking process. The increase in average temperature in the rolling surface region is shown as dashed line 310. Furthermore, the temperature peak shown as solid line 320 is also considered, which occurs when the point contacts the track and absorbs energy, and subsequently the energy is released and the temperature decreases accordingly (Source: P.T. Zwierczyk, Thermal stress analysis of a railway wheel-rail rolling-sliding contact (Budapest, 2015)).
[0140] Compared to the peak temperature, the average temperature along the 230° circumference of the rolling surface changes slowly. (Based on the above reference...) Figure 2A The simplified model is used to determine the average temperature. In the example, at least one parameter is determined by fitting based on the finite element method (FEM), specifically... Figure 3 The dashed line 310 in the middle.
[0141] The example values of the model used are given in tabular form below. Physical constants, vehicle-specific constants, and values determined by fitting are shown, particularly when validating and simulating temperature distribution using the FEM method. Specifically, the following are listed: wheel diameter (D_wheel), diameter of the contact area between the wheel and the track (d_point), thickness of the contact area into the wheel material depth (h), area of the wheel contact area (point A) or area of the annular rolling surface (A_ring), volume of the wheel contact area (point V) or volume of the annular rolling surface (V_ring), material density (ro), mass of the wheel contact area (point m) or mass of the annular rolling surface (m_ring), thermal conductivity of the material (steel heat transfer, lam), thermal conductivity of the rolling surface (lambda_ring) or thermal conductivity of the contact area (lambda_point), and specific heat of the material (c).
[0142]
[0143] The parameters shown are still there Figure 4 An exemplary cross-section of a wheel on a track is illustrated.
[0144] Now we can use a temperature-time curve, for example, based on... Figure 3 The data shown.
[0145] Here, we particularly consider the temperature changes during braking events, i.e., temperature rises and falls.
[0146] Here, for example, we check whether a specific temperature value has been reached or exceeded. At a specific temperature, for example, the pearlitic texture of a wheel material can change to an austenitic structure. Such a point is, for example, at... Figure 5 The point is marked "AC3", where the austenitization characteristic curve of the steel material for the wheel is shown as an example in Figure 500.
[0147] For example, it is also checked whether the temperature drops rapidly after reaching a value sufficient for austenitization, thus preventing the formation of martensite. For example, in... Figure 6 The corresponding characteristic curves are shown. In particular, the graph represents a time-temperature-transformation diagram (continuous cooling transformation, CCT).
[0148] Starting with the following material composition under the conditions shown: 0.33% C, 1.12% Mn, 0.30% Si, 0.027% S, 0.018% P, 0.24% Ni, 0.11% Cr, 0.04% Mo, 0.19% Cu, 0.010% Al, grain size: 8-9, austenitized at 850℃ (1562°F) for 1 hour.
[0149] Figure 6 A CCT chart 600 is shown for an exemplary steel used as a wheel material. This chart relates the material's microstructure and texture in relation to the cooling rate.
[0150] Figure Labels
[0151] 10 rail vehicles
[0152] 20 detection units
[0153] 30 Anti-slip Equipment; WP System
[0154] 40 assessment units
[0155] 50 control units
[0156] 100 system
[0157] 210 wheels
[0158] 220 rolling surface
[0159] 230 contact area
[0160] 310 dashed line
[0161] 320 solid line
[0162] 420 wheel (cross-section)
[0163] 440 track (cross section)
[0164] 500 charts
[0165] 600 charts
[0166] Step S10
[0167] S20 Step
[0168] S30 Steps
[0169] S40 Steps
[0170] S50 Steps
[0171] S60 Steps
[0172] S70 Steps
Claims
1. A system for monitoring the condition of wheels (210, 420) of a rail vehicle (10), the system comprising: A detection unit (20) configured to detect at least one operating parameter of wheels (210, 420) during a braking event; an evaluation unit (40) configured to determine the temperature value of wheels (210, 420) based on the detected operating parameters; and a control unit (50) configured to generate and output an output based on the determined temperature value, characterized in that... The temperature values determined for the wheels (210, 420) include the average temperature of the rolling surfaces of the wheels (210, 420), the temperature distribution along the rolling surfaces of the wheels (210, 420), and the temperature at the contact surfaces of the wheels (210, 420). The detection unit (20) is also configured to detect braking parameters. The operating parameters detected for the wheels (210, 420) include wheel speed and / or the speed of the rail vehicle (10). And / or the operating parameters detected for the wheels (210, 420) include the time derivative of the wheel speed and / or the time derivative of the speed of the rail vehicle (10).
2. The system according to claim 1, characterized in that, The braking parameters are the braking pressure and / or braking force of the brake cylinder.
3. The system according to claim 1, characterized in that, The wheel speed is the rotational speed of the wheel (210, 420).
4. The system according to claim 1, characterized in that, The time derivative of the wheel speed is the time derivative of the rotational speed of the wheel (210, 420).
5. The system according to any one of claims 1 to 4, characterized in that, The at least one operating parameter of the wheels (210, 420) can be detected by means of the anti-skid system (30).
6. The system according to any one of claims 1 to 4, characterized in that, The evaluation unit (40) is configured to: determine the average temperature of the rolling surface (220) of the wheels (210, 420) when determining the temperature value of the wheels (210, 420) based on a simplified thermal model; and determine the temperature peak based on a lookup table.
7. The system according to any one of claims 1 to 4, characterized in that, The control unit (50) is configured to generate an output based on the achievement of at least one temperature threshold.
8. The system according to claim 7, characterized in that, The control unit (50) is configured to determine the probability of a damaged part and generate an output based on at least one probability threshold.
9. The system according to claim 8, characterized in that, The control unit (50) is configured to determine the probability of martensite formation.
10. The system according to any one of claims 1 to 4, characterized in that, The output includes warning messages and / or diagnostic messages and / or error codes.
11. The system according to claim 10, characterized in that, The control unit (50) is configured to store the output in a diagnostic memory.
12. A method for monitoring the state of wheels (210, 420) of a rail vehicle (10), wherein, in a braking event, at least one operating parameter of the wheels (210, 420) is detected; a temperature value of the wheels (210, 420) is determined based on the detected operating parameter; and an output is generated and output based on the determined temperature value, characterized in that, The temperature values determined for the wheels (210, 420) include the average temperature of the rolling surfaces of the wheels (210, 420), the temperature distribution along the rolling surfaces of the wheels (210, 420), and the temperature at the contact surfaces of the wheels (210, 420). It also checks braking parameters. The operating parameters detected for the wheels (210, 420) include wheel speed and / or the speed of the rail vehicle (10). And / or the operating parameters detected for the wheels (210, 420) include the time derivative of the wheel speed and / or the time derivative of the speed of the rail vehicle (10).