CN114659812A - Wheel rail sanding and viscosity increasing simulation experiment method and sander structure - Google Patents
Wheel rail sanding and viscosity increasing simulation experiment method and sander structure Download PDFInfo
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Abstract
The invention discloses a wheel rail sanding and viscosity increasing simulation experiment method and a sander structure, wherein the experiment method comprises the following steps: calculating the rail surface sand grain distribution density and the characteristic contact length in the field sanding process; calculating the characteristic contact length in a simulation experiment according to the diameter of the simulated wheel rail sample, and equivalently calculating the sand grain distribution density of the rail surface of the simulation experiment based on the scaling of the characteristic contact length of the field and the simulation experiment; further calculating to obtain the sanding flow required in the experiment; finally, performing a wheel rail sanding and tackifying experiment under a low-adhesion working condition on a double-disc wheel rail rolling contact simulation experiment machine; the sand spreader comprises a sand box, a primary sand discharging valve, a sand collecting box-left bin, a sand collecting box-right bin, a displacement sliding table, a secondary sand discharging valve-left and secondary sand discharging valves-right and a Venturi nozzle. The equivalent simulation of the sand scattering amount in the wheel-rail sand scattering and viscosity increasing simulation experiment is realized; and the precise regulation and control and real-time monitoring of the sanding amount in the wheel-rail sanding simulation experiment are realized.
Description
Technical Field
The invention belongs to the technical field of wheel-rail tribology, and particularly relates to a wheel-rail sanding and viscosity-increasing simulation experiment method and a sander structure.
Background
The sanding is the most effective and economic technical means for improving the adhesion coefficient of the wheel-rail interface under the low adhesion working condition, and the application on the railway is very wide; however, unreasonable sanding, such as too large or too small amount of sanding, cannot fully exert sanding and tackifying effects, and can bring about adverse effects such as aggravation of abrasion and damage of wheel rails and insulation of track circuits. Therefore, in order to give full play to the sanding and viscosity increasing effect and reduce the adverse effect in the sanding and viscosity increasing process, the research and the like by means of experiments and the like reveal that key influencing factors and rules in the sanding and viscosity increasing process are necessary for optimizing sanding parameters and reasonably sanding.
Compared with field experiments, the double-disc type wheel-rail rolling contact simulation experiment machine has the remarkable advantages of high controllability, short period, low cost and the like when used for carrying out simulation experiments in a laboratory, and is the current mainstream technical means in the field of wheel-rail tribology research. However, unlike conventional simulation subjects, there is a very significant size effect in simulating the track sanding tackifying process because the track specimens used in the simulation experiments were scaled so that the amount of tackifying sand particles entering the contact zone changed significantly from the in-situ track contact conditions. Under the influence of the size effect, the direct use of the sanding amount parameter on site (usually in the range of 0.3-2.0 kg/min) will undoubtedly result in serious excessive sanding effect in the simulation experiment and thus in erroneous conclusion. Therefore, it is necessary to establish a sanding equivalent simulation method that can take into account the scaling of the simulated sample size, which is a key technical problem that is not solved in the field at present.
In addition, the accuracy of the experimental result also significantly depends on the precise control and real-time monitoring of the sanding amount in the simulation experiment process, however, no matter the locomotive/motor train unit sander is used on site, or the common simulation sanding device in the existing public data and research literature, the flow regulation of the device usually only depends on a single sanding valve for independent control, the flow regulation range and the control precision of the device are limited, the simulation experiment requirements in a smaller sanding amount range are difficult to realize (for example, the sanding flow is less than 10g/min, and the control precision is 1g/min), and the device does not have the function of monitoring the sanding amount in real time in the sanding process.
Disclosure of Invention
The method aims at the equivalent simulation problem of the sanding amount in the wheel-rail sanding and viscosity increasing simulation experiment and the requirement of carrying out accurate regulation and control and real-time monitoring on the sanding amount in the wheel-rail sanding simulation experiment. The invention provides a wheel rail sanding and viscosity increasing simulation experiment method and a sander structure.
The invention relates to a wheel rail sanding and viscosity increasing simulation experiment method, which is used for carrying out a wheel rail sanding and viscosity increasing simulation experiment under a low-adhesion working condition on a double-disc wheel rail rolling contact simulation experiment machine and comprises the following steps:
step 1: calculating the rail surface sand grain distribution density q in the field sanding process according to the actual field operation conditions0Calculating the on-site characteristic contact length l according to the diameter of the wheel and the particle diameter of the tackifying particles0。
Step 2: calculating the characteristic contact length l in the simulation experiment according to the diameter of the simulated wheel rail and the grain diameter of the tackifying particles, and equivalently calculating the sand grain distribution density q of the rail surface of the simulation experiment according to the calculation result in the step 1:
and step 3: and (3) calculating the normal force, the rotating speed and the creep rate in the simulation experiment according to the principle that the maximum Hertz contact stress, the rotating speed and the creep rate are consistent with the on-site wheel-rail contact conditions, and calculating the sanding flow Q in the simulation experiment according to the calculation result in the step (2) and the rotating speed of the simulation sample.
And 4, step 4: and (3) performing a wheel rail sanding and tackifying experiment according to the simulation experiment parameters obtained in the step (3), applying a medium to the surface of a wheel rail sample in the experiment process to simulate the low adhesion working condition of the wheel rail, recording the wheel rail adhesion coefficient in the experiment as an evaluation index of sanding and tackifying effect, and analyzing and representing wheel rail abrasion and damage in the sanding and tackifying process through weighing and sample surface/sub-surface damage.
Further, in step 1, the distribution density q of the rail surface sand grains0The calculation formula is as follows:
wherein N is the rotation speed of the wheel on site, R is the radius of the wheel on site, B is the effective shakeout width of the steel rail surface during the sand spraying on site, and Q0Is the on-site sanding flow.
Characteristic contact length l in situ0The calculation formula is as follows:
in the formula, d is the median particle size of the tackifying sand particles.
Further, the characteristic contact length l in step 2 is calculated as:
in the formula, r1、r2Respectively, the radius of a simulated wheel rail sample, and d is the median particle size of the tackifying sand particles.
Further, the calculation formula of the sanding flow Q in the step 3 is as follows: q2 n pi r1bq；
Wherein n is the rotating speed of the simulated wheel rail sample, r1In order to simulate the radius of the wheel rail sample, b is the effective shakeout width of the steel rail surface in the simulation experiment.
Further, the medium applied in step 4 is, but not limited to, water, oil or leaves.
The invention relates to a sand spreader structure for a wheel rail sand spreading and viscosity increasing simulation experiment, which comprises a sand box, a primary sand discharging valve, a sand collecting box, a displacement sliding table, a secondary sand discharging valve and a Venturi nozzle, wherein the sand spreading valve is arranged on the sand box; wherein, the sand collecting box is arranged on the displacement sliding table and is divided into a sand collecting box-a left bin and a sand collecting box-a right bin; the secondary sand discharging valve is divided into a secondary sand discharging valve-left and a secondary sand discharging valve-right, the secondary sand discharging valve-left is arranged at the bottom of the sand collecting box-left bin, and the secondary sand discharging valve-right is arranged at the bottom of the sand collecting box-right bin.
Furthermore, the sand box, the sand collecting box-left bin and the sand collecting box-right bin are all of measuring cup type structures.
Further, the method for monitoring and controlling the sanding flow of the wheel-rail sanding and viscosity-increasing simulation experiment sander structure comprises the following steps: in the process of sanding, the second-level sanding valve-left is kept at the maximum opening degree, so that no sand is accumulated in the sand collecting box-left bin, and the real-time sanding flow in the experimental process is determined by the reduction delta V of sand particles stored in the sand box in unit monitoring time t1Sand particle increment delta V of sand collecting box-right bin2Calculating to obtain the sand flow, and realizing the real-time monitoring of the sand spreading flow in the simulation experiment, wherein the calculation formula is as follows:
Q＝ρ(ΔV1－ΔV2)/t
wherein ρ is the particle packing density; if Q is larger than the set simulated sanding flow, reducing the sanding flow by reducing the opening of the primary sand discharge valve or adjusting the displacement sliding table to reduce the proportion of sand particles falling into the left cabin of the sand collection box or combining the two modes; and if Q is smaller than the set simulated sanding flow, performing reverse adjustment.
The beneficial technical effects of the invention are as follows:
the invention provides a simulation experiment method for equivalent conversion of sanding amount by taking the characteristic contact length of an on-site wheel rail and a simulation sample as a scaling ratio. Simultaneously, the sand spreader structure capable of accurately regulating and controlling the sand spreading amount and monitoring the sand spreading amount in real time in a wheel-rail sand spreading simulation experiment is provided.
Drawings
Fig. 1 is a flow chart of a wheel rail sanding and viscosity increasing simulation experiment method of the invention.
FIG. 2 is a schematic diagram of a field wheel rail characteristic contact length calculation.
FIG. 3 is a schematic diagram of the calculation of the characteristic contact length of a simulated sample.
Fig. 4 is a schematic view of the structure of the sander of the present invention.
FIG. 5 shows the results of the example simulation experiment.
Detailed Description
The invention is described in further detail below with reference to the figures and the detailed description.
The invention discloses a wheel rail sanding and viscosity increasing simulation experiment method, which is shown in figure 1, and the wheel rail sanding and viscosity increasing simulation experiment is carried out on a double-disc wheel rail rolling contact simulation experiment machine under a low-adhesion working condition, and specifically comprises the following steps:
step 1: calculating the rail surface sand grain distribution density q in the field sanding process according to the actual field operating conditions (train operating speed and sanding flow)0Calculating the on-site characteristic contact length l according to the diameter of the wheel and the particle diameter of the tackifying particles0。
Step 2: calculating characteristic contact length l in a simulation experiment according to the diameter of the simulated wheel rail and the grain diameter of the tackifying particles, and equivalently calculating sand grain distribution density q of the rail surface of the simulation experiment according to the calculation result in the step 1:
and step 3: and (3) calculating the normal force, the rotating speed and the creep rate in the simulation experiment according to the principle that the maximum Hertz contact stress, the rotating speed and the creep rate are consistent with the on-site wheel-rail contact conditions, and calculating the sanding flow Q in the simulation experiment according to the calculation result in the step (2) and the rotating speed of the simulation sample.
And 4, step 4: and (3) performing a wheel rail sanding and tackifying experiment according to the simulation experiment parameters obtained in the step (3), applying a medium to the surface of a wheel rail sample in the experiment process to simulate the low adhesion working condition of the wheel rail, recording the wheel rail adhesion coefficient in the experiment as an evaluation index of sanding and tackifying effect, and analyzing and representing wheel rail abrasion and damage in the sanding and tackifying process through weighing and sample surface/sub-surface damage.
It should be noted that the concept of characteristic contact length in the present invention is used to measure the distance between individual bonded sand particles and the rail interface where contact and interaction occurs. During the process of sanding and tackifying, from an initial contact position A of a single sand particle (the particle size is millimeter scale) with the surface of the wheel track to a final entering into the center B of a wheel track contact patch, the sand particle is gradually pressed and crushed into particle powder (the particle size is micrometer scale) along with the reduction of the contact gap between the surfaces of the wheel track, and finally, the tackifying effect is exerted by the furrow effect of the broken sand particles between the contact interfaces of the wheel track, so that the tackifying effect is obviously dependent on the number of the particles distributed on the contact interfaces, namely the distribution density of the broken particles. The distance between AB is taken as the characteristic contact length, and the broken particles can be assumed to be distributed on the surface of a wheel track on the AB length in the process of continuously crushing and breaking the single sand particles from A to B, and obviously, under the condition of certain mass of the single sand particles, the distribution density of the particles is inversely related to the characteristic contact length. However, in the simulation experiment, the particle size of the sand particles remains unchanged after the size of the simulated wheel rail sample is scaled, so that the characteristic contact length is reduced and the total amount of particles formed by crushing is unchanged; under the condition that the experimental sanding amount is not corrected, the actual particle distribution density in the simulation experiment is necessarily far beyond the actual conditions on site, so that in order to ensure the accuracy of the simulation, equivalent calculation is required to be carried out on the rail surface sand particle distribution density in the experiment based on the scaling of the characteristic contact length in the site and simulation experiments.
Further, in step 1, the distribution density q of the rail surface sand grains0The calculation formula is as follows:
wherein N is the rotation speed of the wheel on site, R is the radius of the wheel on site, B is the effective shakeout width of the steel rail surface during the sand spraying on site, and Q0Is the on-site sanding flow.
Characteristic contact length l in situ0The calculation formula is as follows:
in the formula, d is the median particle size of the tackifying sand particles.
Further, the characteristic contact length l in step 2 is calculated as:
in the formula, r1、r2Respectively, the radius of a simulated wheel rail sample, and d is the median particle size of the tackifying sand particles.
Further, the calculation formula of the sanding flow Q in the step 3 is as follows:
Q＝2nπr1bq (5)
wherein n is the rotating speed of the simulated wheel rail sample, r1In order to simulate the radius of the wheel rail sample, b is the effective shakeout width of the steel rail surface in the simulation experiment.
Further, the medium applied in step 4 is, but not limited to, water, oil or leaves.
The invention relates to a sand spreader structure for a wheel rail sand spreading and viscosity increasing simulation experiment, which comprises a sand box 1, a primary sand discharging valve 2, a sand collecting box, a displacement sliding table 5, a secondary sand discharging valve and a Venturi nozzle 8; wherein, the sand collecting box is arranged on the displacement sliding table 5 and is divided into a sand collecting box-left bin 3 and a sand collecting box-right bin 4; the secondary sand discharging valve is divided into a secondary sand discharging valve-left 6 and a secondary sand discharging valve-right 7, the secondary sand discharging valve-left 6 is arranged at the bottom of the sand collecting box-left bin 3, and the secondary sand discharging valve-right 7 is arranged at the bottom of the sand collecting box-right bin 4.
The proportional distribution of sand particles entering the sand collecting box-left bin 3 and the sand collecting box-right bin 4 is realized by adjusting the position of the separating surface of the sand collecting box-left bin 3 and the sand collecting box-right bin 4 relative to the primary sand discharging valve 2. In the using process, sticky sand particles are stored in the sand box 1, fall into a lower sand collecting box through the primary sand discharging valve 2 under the action of gravity, wherein the sand particles falling into the sand collecting box-left bin 3 are sucked into the Venturi nozzle 8 through the secondary sand discharging valve-left 6, are blown into the simulated wheel rail sample rolling contact interface through compressed air, are retained in the sand collecting box-right bin, and are taken out through the secondary sand discharging valve-right 7 after the experiment is finished or the sand collecting box is filled.
Preferably, the pressure of the used air source should be kept constant, and the adjustment of the pressure of the air source is not suitable for controlling the flow of sanding flow, so that the chaos of the system is avoided.
Further, the air source pressure is reasonably adjusted to meet the requirement that the sand blasting flow of the Venturi nozzle 8 is larger than the sand blasting flow of the second-level sand blasting valve-left 6 with the maximum opening degree, and no particle accumulation is ensured in pipelines from the second-level sand blasting valve-left 6 to the nozzle and the nozzle; but also should not be too big simultaneously, avoid the grit granule to get into the granule of simulation wheel rail sample contact interface and spout and launch the loss.
The sand spreading flow control in the simulation experiment is realized by jointly adjusting the primary sand discharging valve 2 and the displacement sliding table 5.
The sand box 1 and the sand collecting box are of measuring cup type structures and are used for measuring the volume change of sand particles in the box in real time; in the process of sanding, the second-level sanding valve-left 6 is kept to be the maximum opening, so that no sand is accumulated in the sand collecting box-left bin 3, and the real-time sanding flow in the experimental process can be obtained by the reduction quantity delta V of the sand particles stored in the sand box 1 in unit monitoring time t1Sand particle increment delta V of sand collecting box-right bin 42And calculating to obtain the flow rate of the sanding in the simulation experiment, and realizing real-time monitoring of the sanding flow rate.
Further, the sanding flow rate monitored in real time in the experimental process is Q ═ rho (delta V)1－ΔV2) And/t, wherein ρ is the particle bulk density. If Q is larger than the set simulated sanding flow, the sanding flow is reduced by reducing the opening of the first-stage lower sand valve 2 or adjusting the displacement sliding table 5 to reduce the proportion of sand particles falling into the left chamber 3 of the sand collection box or combining the two modes; and if Q is smaller than the set simulated sanding flow, performing reverse adjustment according to the method.
Example (b):
the method is characterized in that a harmonious type freight locomotive is taken as a simulation object, the radius of wheels of the harmonious type freight locomotive is 0.625m, the axle weight is 25T, and the maximum running speed is 120km/h, the sand scattering amount of a pressure difference type sand spreader arranged in a locomotive is in the range of 0.45-1.05 kg/min according to the technical requirements of TB/T3254 and 2019 locomotive vehicle sand scattering devices, and the particle size of used sand particles is concentrated in the range of 0.63-2.0 mm (the median particle size is 1.2 mm).
The simulation experiment is carried out on an MJP-30A double-disc type wheel rail rolling contact simulation experiment machine, two disc samples with the diameter of 60mm (line contact simulation, contact width of 10mm) are used for simulating wheel rail contact, and the used tackifying sand particles are consistent with the field.
Then the sanding amount of the locomotive at the running speed of 60km/h is respectively 0.45kg/min, 0.65kg/min, 0.85kg/min and 1.05kg/min, and the simulation experiment is carried out according to the following steps:
step 1: calculating the rail surface sand grain distribution density of different sanding flow rates under the running speed of the train of 60km/h by the formula (2), wherein the effective shakeout distribution width is B60 mm, and calculating q0Are respectively 7.5g/m2、10.8g/m2、14.2g/m2And 17.5g/m2(ii) a Calculating the characteristic contact length l of the on-site wheel rail by the formula (3)038.73mm, as shown in fig. 2.
Step 2: the characteristic contact length l of the simulated wheel rail sample calculated by the formula (4) is 8.49mm, as shown in fig. 3; calculating according to the formula (1) to obtain the equivalent orbital surface particle distribution density q of 0.22q in the simulation experiment01.65g/m respectively2、2.38g/m2、3.12g/m2And 3.85g/m2。
And step 3: calculating the normal force of 6000N (the maximum contact stress of 1200MPa), the rotating speed of 510r/min and the creep rate of 2% in a simulation experiment according to the principle that the maximum Hertz contact stress, the rotating speed and the creep rate are consistent with the on-site wheel-rail contact conditions; and calculating the sanding flow in the simulation experiment according to the calculation result in the step 2 and a formula (5), wherein the effective sanding distribution width in the simulation experiment is 20mm, and the calculated sanding flow Q is respectively 3.2g/min, 4.6g/min, 6.0g/min and 7.4 g/min.
And 4, step 4: and (3) performing a wheel-rail sanding and tackifying experiment according to the simulation experiment parameters obtained in the step (3), simulating a wheel-rail low-adhesion working condition in a rainy environment by continuously dripping water (with the flow rate of 20ml/min) onto the surface of a wheel-rail sample in the experiment process, recording the wheel-rail adhesion coefficient in the experiment, and representing the wheel-rail abrasion and damage in the sanding and tackifying process by means of weighing, sample surface/sub-surface damage analysis and the like.
Fig. 4 shows a structure of a sand spreader used in a simulation experiment, the sand spreader is composed of a sand box 1, a primary sand discharging valve 2, a sand collecting box-left bin 3, a sand collecting box-right bin 4, a displacement sliding table 5, a secondary sand discharging valve-left 6, a secondary sand discharging valve-right 7 and a venturi nozzle 8; the sand spreader sand collecting box is arranged on the displacement sliding table 5, and the proportional distribution of sand entering the left sand collecting box and the right sand collecting box is realized by adjusting the position of the left cabin interface and the right cabin interface of the sand collecting box relative to the center line of the primary sand discharging valve 2. In the using process, sticky sand particles are stored in the sand box 1, fall into a lower sand collecting box through the primary sand discharging valve 2 under the action of gravity, wherein the sand particles falling into the sand collecting box-left bin 3 are sucked into the Venturi nozzle 8 through the secondary sand discharging valve-left 6, are blown into the simulated wheel rail sample rolling contact interface through compressed air, are retained in the sand collecting box-right bin, and are taken out through the secondary sand discharging valve-right 7 after the experiment is finished or the sand collecting box is filled.
The primary sand discharging valve 2 in the sand spreader structure is a flow control valve with the diameter of 12mm, sand discharging amount regulation and control within the range of 0-100 g/min can be realized through opening control, and the control precision is about 5 g/min; the sand collecting boxes below the first-level lower sand valve 2 are arranged on the displacement sliding table 5, the sand spreading flow rate is controlled in a shunting manner by adjusting the sand flow dividing proportion of the left sand collecting box and the right sand collecting box, the displacement control precision of the displacement sliding table is 0.1mm, and the antipodal sand spreading flow control precision is about 1% of the sand spreading flow rate of the first-level lower sand valve 2 when the cutting line is positioned near the center line position of the first-level lower sand valve 2. Before the experiment, the sanding flow selected by the simulation experiment is obtained by calibrating the sanding flow and adjusting the sanding flow according to the control parameters shown in the table 1.
TABLE 1 Regulation and control parameters of sanding flow in simulation experiment
The air source pressure used by the sand spreader is constant at 0.2MPa, so that no particles are accumulated in pipelines from the second-stage sand discharging valve-left 6 to the spray head and the spray nozzle in the sand spreading process, and the particle injection and ejection loss of the sand particles entering a simulated wheel rail sample contact interface is relatively small.
The sand box 1 and the sand collecting box in the sand spreader structure are of a measuring cup structure made of acrylic materials, the measuring cup structure is provided with volume scale lines and the minimum scale is 1ml, the calibrated sand particle stacking density is 1.5g/ml, when the unit observation time is 1min, the minimum sand spreading flow can be measured at 1.5g/min, and the real-time observation requirement of the sand spreading flow in the experiment is met.
Figure 5 shows the wheel track adhesion coefficient and wear rate results from a sanding adhesion promotion simulation conducted according to the above experimental procedure and described sander structure. It can be seen from the figure that, when sanding is performed under the water state working condition, the wheel-rail adhesion coefficient is within the range of 0.2-0.3 (about 0.15 when no sanding is performed), and with the increase of the sanding amount, the wheel-rail adhesion coefficient and the wear rate both show the trend of increasing first and then decreasing; it was shown that the sanding viscosifying effect had approached saturation at sanding amounts close to 6.0g/min (0.85 kg/min at the simulated site), further increasing the sanding amount impaired the viscosifying effect due to the solid lubrication effect produced by the excess sand.
Claims (7)
1. A wheel rail sanding and viscosity increasing simulation experiment method is characterized in that a double-disc wheel rail rolling contact simulation experiment machine is used for carrying out wheel rail sanding and viscosity increasing simulation experiments under a low adhesion working condition, and the method comprises the following steps:
step 1: calculating the rail surface sand grain distribution density q in the field sanding process according to the actual field operation conditions0Calculating the on-site characteristic contact length l according to the diameter of the wheel and the particle diameter of the tackifying particles0；
Step 2: calculating characteristic contact length l in a simulation experiment according to the diameter of the simulated wheel rail and the grain diameter of the tackifying particles, and equivalently calculating sand grain distribution density q of the rail surface of the simulation experiment according to the calculation result in the step 1:
and step 3: calculating normal force, rotating speed and creep rate in the simulation experiment according to the principle that the maximum Hertz contact stress, rotating speed and creep rate are consistent with the on-site wheel-rail contact conditions, and calculating the sanding flow Q in the simulation experiment according to the calculation result in the step 2 and the rotating speed of the simulation sample;
and 4, step 4: and (3) performing a wheel rail sanding and tackifying experiment according to the simulation experiment parameters obtained in the step (3), applying a medium to the surface of a wheel rail sample in the experiment process to simulate the low adhesion working condition of the wheel rail, recording the wheel rail adhesion coefficient in the experiment as an evaluation index of sanding and tackifying effect, and analyzing and representing wheel rail abrasion and damage in the sanding and tackifying process through weighing and sample surface/sub-surface damage.
2. The method for simulating sanding and viscosity increasing of wheel rails according to claim 1, wherein the distribution density q of sand grains on the rail surface in the step 1 is0The calculation formula is as follows:
wherein N is the rotation speed of the wheel on site, R is the radius of the wheel on site, B is the effective shakeout width of the steel rail surface during the sand spraying on site, and Q0The flow rate of the sand spraying on site;
characteristic contact length in situ0The calculation formula is as follows:
in the formula, d is the median particle size of the tackifying sand particles.
3. The method for simulating wheel rail sanding and viscosity increasing as claimed in claim 1, wherein the characteristic contact length l in step 2 is calculated by the following formula:
in the formula, r1、r2Respectively simulating the radius of a wheel rail sample, and d is the median particle size of the tackifying sand particles。
4. The method for simulating wheel-rail sanding and viscosity increasing according to claim 1, wherein the calculation formula of the sanding flow Q in the step 3 is: q2 n pi r1bq；
Wherein n is the rotating speed of the simulated wheel rail sample, r1In order to simulate the radius of the wheel rail sample, b is the effective shakeout width of the steel rail surface in the simulation experiment.
5. A wheel track sanding and viscosity increasing simulation experiment sander structure is characterized in that the sander is composed of a sand box (1), a primary sand discharging valve (2), a sand collecting box, a displacement sliding table (5), a secondary sand discharging valve and a Venturi nozzle (8); wherein the sand collecting box is arranged on the displacement sliding table (5) and is divided into a sand collecting box-left bin (3) and a sand collecting box-right bin (4); the secondary sand discharging valve is divided into a secondary sand discharging valve-left (6) and a secondary sand discharging valve-right (7), the secondary sand discharging valve-left (6) is arranged at the bottom of the sand collecting box-left bin (3), and the secondary sand discharging valve-right (7) is arranged at the bottom of the sand collecting box-right bin (4).
6. The structure of the sand spreader for the wheel track sanding and viscosity increasing simulation experiment according to claim 5, wherein the sand box (1), the sand collecting box-left bin (3) and the sand collecting box-right bin (4) are all of measuring cup type structures.
7. The method for monitoring and controlling the sanding flow of the structure of the sand spreader for the wheel-track sanding and viscosity increasing simulation experiment according to claim 6, wherein during sanding, the secondary sand valve-left (6) is kept at the maximum opening degree, so that no sand is accumulated in the sand collection box-left bin (3), and then the real-time sanding flow during the experiment is obtained by the sand particle reduction amount delta V stored in the sand box (1) in the unit monitoring time t1Sand particle increment delta V of sand collecting box-right bin (4)2Calculating to obtain the sand flow, and realizing the real-time monitoring of the sand spreading flow in the simulation experiment, wherein the calculation formula is as follows:
Q＝ρ(ΔV1－ΔV2)/t
wherein ρ is the particle packing density; if Q is larger than the set simulated sanding flow, the sanding flow is reduced by reducing the opening of the primary sand discharging valve (2) or adjusting the displacement sliding table (5) to reduce the proportion of sand particles falling into the sand collecting box-left cabin (3) or combining the two modes; and if Q is smaller than the set simulated sanding flow, performing reverse adjustment.
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| CN117272685B (en) * | 2023-11-17 | 2024-01-26 | 西南交通大学 | Optimal sanding decision simulation method based on train operation parameters |
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