A real-time sensing method and system for wheel-rail adhesion of railway train

Abstract

The present application relates to the field of railroad train wheel-rail technology, and provides a railroad train wheel-rail adhesion real-time perception method and system, the method comprising: step S1: calculating the evaluation value of the utilization adhesion coefficient of the train wheel-rail; step S2: obtaining the observation value of the utilization adhesion; step S3: when the wheelset of the train is initially sliding, the utilization adhesion coefficient of the wheelset can be used as the estimated value μ of the wheel-rail adhesion coefficient of this wheelset; step S4: accumulating the estimated values ​​of the wheel-rail adhesion coefficient of all sliding wheelsets, and then taking the average value to obtain the initial adhesion evaluation value of the train; step S5: obtaining the curve of the wheel-rail adhesion coefficient of m axles during the train braking process with speed, where m is a positive integer greater than or equal to 1. The present application realizes dynamic, real-time, and high-precision monitoring of the wheel-rail adhesion state of railroad trains, and significantly improves the safety and operational efficiency of train operation.

Description

Technical Field

[0001] The present application relates to the field of railway train wheel-rail technology, and in particular to a railway train wheel-rail adhesion real-time sensing method and system. Background Art

[0002] According to UIC541-05-2016 standard, there are two methods for calculating train adhesion:

[0003] Method 1:

[0004] ,

[0005] Among them, x is the average deceleration value of the vehicle within 0.2s before and after the initial coasting;

[0006] Method 2:

[0007] ,

[0008] .

[0009] Neither of the above two methods takes angular acceleration into account The existence of has an impact on the calculation results, so the accuracy is low.

[0010] Currently, the rotation speed of the wheelset is measured on rail trains by an axle speed pulse sensor installed at the axle end, and there is no direct means to directly measure the angular acceleration (deceleration) of the wheelset. Summary of the invention

[0011] In order to help solve the above-mentioned technical problems, the present application provides a method and system for real-time perception of wheel-rail adhesion of a railway train.

[0012] In a first aspect, the present application provides a method for real-time perception of wheel-rail adhesion of a railway train, which adopts the following technical solution:

[0013] A method for real-time perception of wheel-rail adhesion of a railway train, wherein the method comprises:

[0014] Step S1: Calculate the estimated value of the train wheel-rail adhesion coefficient by the following method: :

[0015] Formula 1:

[0016] ;

[0017] Step S2: Using the adhesive force in the following way Make an estimate:

[0018] Formula 2:

[0019] ,

[0020] Performing Laplace transform on equation 2 yields:

[0021] Formula 3:

[0022] ,

[0023] p is the Laplace operator, and the right side of Equation 3 is subjected to a first-order low-pass filter. is the cutoff frequency in the first-order low-pass filter, and then transformed into:

[0024] Formula 4:

[0025] ,

[0026] in Defined as:

[0027] Formula 5:

[0028] ,

[0029] Taking the Laplace inverse transform of equation 5, we get:

[0030] Formula 6:

[0031] ,

[0032] in,

[0033] ;

[0034] Solving the differential equation shown in formula 6 yields , and then the observed value of adhesion is:

[0035] Formula 7:

[0036] ,

[0037] Further we can get formula 8:

[0038] ;

[0039] Step S3: When the wheelset of the train starts to slide, the wheelset’s utilization adhesion coefficient is It can be regarded as the estimated value μ of the wheel-rail adhesion coefficient of this wheelset;

[0040] Step S4: Estimated values ​​of wheel-rail adhesion coefficients of all sliding wheelsets Accumulate, i is the wheel number of the train, and then take the average value to get the initial adhesion evaluation value of the train , specifically, Formula 9:

[0041] ;

[0042] Step S5: obtaining a curve of wheel-rail adhesion coefficient versus speed of m axles during train braking, where m is a positive integer greater than or equal to 1;

[0043] in, is the moment of inertia of the wheels, Vt is the train speed, is the wheel angular velocity, is the wheel radius, K is the clamping force, To utilize the adhesion, F b The friction force exerted by the brake pad or brake shoe on the brake disc or wheel. is the friction coefficient of the brake shoe, r is the friction radius of the brake pad or brake shoe;

[0044] is the brake cylinder pressure, A is the piston area, is the brake cylinder spring back pressure, is the nominal friction coefficient of the brake friction pair, is the leverage ratio, is the mechanical efficiency, For the axle weight.

[0045] Preferably, in step S1, the formula 1 is obtained in the following manner:

[0046] Formula 10:

[0047] ;

[0048] Further we get formula 11:

[0049] ;

[0050] Further obtain the formula 2:

[0051] ,

[0052] in,

[0053] ;

[0054] And because of formula 12:

[0055] ;

[0056] Therefore, formula 13:

[0057] ;

[0058] Substituting equation 13 into equation 2, we get equation 14:

[0059] ,

[0060] Finally, we get formula 1: .

[0061] Preferably, in step S5, for one axle, there will be n sliding cycles from the train speed v0 to the speed 0, where n is a positive integer greater than or equal to 1, and the adhesion coefficient will have a maximum value in each sliding cycle. , the maximum value of the adhesion coefficient used in n sliding cycles Plotted as a curve showing the change in wheel-rail adhesion coefficient at this axle position as a function of speed during train braking.

[0062] Preferably, in step S5, if m axles slip during braking, a curve of wheel-rail adhesion coefficient variation with speed at the positions of the m axles is obtained based on the curve of wheel-rail adhesion coefficient variation with speed at the positions of the axles.

[0063] In the second aspect, the present application provides a rail train wheel-rail adhesion real-time sensing system, which adopts the following technical solution:

[0064] A rail train wheel-rail adhesion real-time sensing system, wherein the real-time sensing system uses the real-time sensing method as described in any one of the first aspects above, the real-time sensing system includes an online real-time sensing chassis for wheel-rail adhesion, the online real-time sensing chassis for wheel-rail adhesion includes a power supply board, a fault diagnosis board, a signal input and output board, a central processing unit board and a communication board connected in sequence, and the online real-time sensing chassis for wheel-rail adhesion receives input signals and sends output signals.

[0065] Preferably, the input signal includes train speed, axle speeds, brake cylinder pressure, moment of inertia, wheel radius and axle weight, and the output signal includes adhesion coefficient, slip rate and adhesion force.

[0066] Preferably, the input signal input method includes MVB signal input, Ethernet transmission and sensor acquisition, and the input signal also includes piston area, brake cylinder spring back pressure, brake cylinder diameter, friction coefficient, leverage ratio and mechanical efficiency.

[0067] In summary, the method of the present application realizes dynamic, real-time, and high-precision monitoring of the wheel-rail adhesion state of rail trains through precise processing of angular acceleration, thereby significantly improving the safety and operational efficiency of train operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for real-time perception of wheel-rail adhesion of a railway train of the present application;

[0069] Figure 2 This is a schematic diagram of the principle of train wheel force analysis;

[0070] Figure 3 It is a schematic diagram of the curves of track wheel speed and wheel speed changing with time;

[0071] Figure 4 It is a schematic diagram of the curve of the change of adhesion force over time;

[0072] Figure 5 A schematic block diagram of an embodiment of a real-time perception system for wheel-rail adhesion of a railway train according to the present application. DETAILED DESCRIPTION

[0073] The present application is further described below in conjunction with the accompanying drawings, and the structure and principle of the present application are very clear to people in the field. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0074] Figure 1 This is a flow chart of an embodiment of a method for real-time perception of wheel-rail adhesion of a railway train of the present application. Figure 2 The schematic diagram of the train wheel force analysis principle is shown in Figure 1. Figure 3 It is a schematic diagram of the curves of track wheel speed and wheel speed changing with time. Figure 4 The figure is a schematic diagram of the curve showing the change of adhesion force over time.

[0075] Combination Figure 1 and Figure 4 It is understood that the method of the present application may include:

[0076] Step S1: Calculate the estimated value of the train wheel-rail adhesion coefficient by the following method: :

[0077] Formula 1:

[0078] .

[0079] The specific derivation of formula 1 is as follows:

[0080] The equation of motion for wheelset rotation is:

[0081] Formula 10:

[0082] .

[0083] That is: Formula 11:

[0084] .

[0085] but:

[0086] Formula 2:

[0087] .

[0088] in:

[0089] .

[0090] And because:

[0091] Formula 12:

[0092] .

[0093] Therefore, formula 13:

[0094] .

[0095] Substitute equation 13 into equation 2,

[0096] Formula 14:

[0097] .

[0098] Therefore: The utilization adhesion coefficient of the wheelset is:

[0099] Formula 1:

[0100] .

[0101] Step S2: The adhesive force is applied to the Make an estimate:

[0102] Due to the angular acceleration It is difficult to measure directly, so the disturbance observer method is used to estimate the adhesion. First, perform Laplace transformation on equation 2 to obtain

[0103] Formula 3:

[0104] .

[0105] Where p is the Laplace operator.

[0106] In order to suppress the measurement noise, a first-order low-pass filter (cutoff frequency is )have to

[0107] .

[0108] Transform and rearrange this formula to get:

[0109] Formula 4:

[0110] .

[0111] in Defined as:

[0112] Formula 5:

[0113] .

[0114] Taking the Laplace inverse transform of equation 5, we get

[0115] Formula 6:

[0116] .

[0117] in:

[0118] ;

[0119] Solving the differential equation shown in formula 6 yields , and then the observed value of adhesion is:

[0120] Formula 7:

[0121] .

[0122] According to formula 1, the wheelset utilization adhesion coefficient can be obtained: The observed value is

[0123] Formula 8:

[0124] .

[0125] Step S3: When the wheelset of the train starts to slide, the wheelset’s utilization adhesion coefficient is It can be regarded as the estimated value μ of the wheel-rail adhesion coefficient of this wheelset.

[0126] Step S4: Estimated values ​​of wheel-rail adhesion coefficients of all sliding wheelsets Accumulate, i is the wheel number of the train, and then take the average value to get the initial adhesion evaluation value of the train , specifically, Formula 9: .

[0127] Step S5: Obtain the curve of wheel-rail adhesion coefficient of m axles during the train braking process, where m is a positive integer greater than or equal to 1. In step S5, according to the method described above, the train starts braking from speed v0 until the speed reaches 0. During the entire braking process, each axle will have multiple sliding cycles. For an axle, there will be n sliding cycles during the process from speed v0 to speed 0. The adhesion coefficient will have a maximum value in each sliding cycle. , the maximum value of the adhesion coefficient used in n sliding cycles It is drawn into a curve, which is the curve of the wheel-rail adhesion coefficient at the position of this axle during the train braking process. If m axles slip during the braking process, this method can be used to obtain the curve of the wheel-rail adhesion coefficient at the position of m axles as a function of speed, that is, the wheel-rail adhesion coefficient curve representing the m axles as a function of speed can be obtained.

[0128] in, is the moment of inertia of the wheels, Vt is the train speed, is the wheel angular velocity, is the wheel radius, K is the clamping force, To utilize the adhesion, F b The friction force exerted by the brake pad or brake shoe on the brake disc or wheel. is the friction coefficient of the brake shoe, r is the friction radius of the brake pad or brake shoe;

[0129] is the brake cylinder pressure, A is the piston area, is the brake cylinder spring back pressure, is the nominal friction coefficient of the brake friction pair, is the leverage ratio, is the mechanical efficiency, For the axle weight.

[0130] The present application also proposes a rail train wheel-rail adhesion real-time sensing system, which uses the aforementioned real-time sensing method. Figure 5 A schematic block diagram of an embodiment of a real-time perception system for wheel-rail adhesion of a railway train according to the present application.

[0131] The real-time sensing system may include an online real-time sensing chassis for wheel-rail adhesion, which includes a power supply board, a fault diagnosis board, a signal input and output board, a central processing unit board and a communication board connected in sequence, and the online real-time sensing chassis for wheel-rail adhesion receives input signals and sends output signals. The input signals include but are not limited to the train speed, the shaft speed of each axle, the brake cylinder pressure, the moment of inertia, the wheel radius and the axle weight, and the output signals include the adhesion coefficient, the slip rate and the adhesion force. The input signal input method includes at least MVB signal input, Ethernet transmission and sensor acquisition, and the input signal also includes the piston area S, the brake cylinder spring back pressure, the brake cylinder diameter, the friction coefficient, the leverage ratio and the mechanical efficiency, as shown in the following table.

[0132]

Claims

1. A real-time perception method for wheel-rail adhesion of a railway train, characterized in that: The method comprises: Step S1: Calculate the estimated value of the train wheel-rail adhesion coefficient by the following method: : Formula 1: ； Step S2: Using the adhesive force in the following way Make an estimate: Formula 2: ， Performing Laplace transform on equation 2 yields: Formula 3: ， p is the Laplace operator, and the right side of Equation 3 is subjected to a first-order low-pass filter. is the cutoff frequency in the first-order low-pass filter, and then transformed into: Formula 4: ， in Defined as: Formula 5: ， Taking the Laplace inverse transform of equation 5, we get: Formula 6: ， in, ； Solving the differential equation shown in formula 6 yields , and then the observed value of adhesion is: Formula 7: ， Further we can get formula 8: ； Step S3: When the wheelset of the train starts to slide, the wheelset’s utilization adhesion coefficient is It can be regarded as the estimated value μ of the wheel-rail adhesion coefficient of this wheelset; Step S4: Estimated values ​​of wheel-rail adhesion coefficients of all sliding wheelsets Accumulate, i is the wheel number of the train, and then take the average value to get the initial adhesion evaluation value of the train , specifically, Formula 9: ； Step S5: obtaining a curve of wheel-rail adhesion coefficient versus speed of m axles during train braking, where m is a positive integer greater than or equal to 1; in, is the moment of inertia of the wheels, Vt is the train speed, is the wheel angular velocity, is the wheel radius, K is the clamping force, To utilize the adhesion, F b The friction force exerted by the brake pad or brake shoe on the brake disc or wheel. is the friction coefficient of the brake shoe, r is the friction radius of the brake pad or brake shoe; is the brake cylinder pressure, A is the piston area, is the brake cylinder spring back pressure, is the nominal friction coefficient of the brake friction pair, is the leverage ratio, is the mechanical efficiency, is the axle weight, is the wheel angular acceleration.

2. The method for real-time perception of wheel-rail adhesion of a railway train according to claim 1, characterized in that: In the step S1, the formula 1 is obtained in the following manner: Formula 10: ； Further we get formula 11: ； Further obtain the formula 2: ， in, ； And because of formula 12: ； Therefore, formula 13: ； Substituting equation 13 into equation 2, we get equation 14: ， Finally, we get formula 1: .

3. The method for real-time perception of wheel-rail adhesion of a railway train according to claim 1, characterized in that: In step S5, for one axle, there will be n sliding cycles from the train speed v0 to the speed 0, where n is a positive integer greater than or equal to 1. The adhesion coefficient will have a maximum value in each sliding cycle. , the maximum value of the adhesion coefficient used in n sliding cycles Plotted as a curve showing the wheel-rail adhesion coefficient at the position of this axle during train braking as a function of speed.

4. The method for real-time perception of wheel-rail adhesion of a railway train according to claim 3, characterized in that: In step S5, if there are m axles sliding during braking, a curve of wheel-rail adhesion coefficient variation with speed at the positions of the m axles is obtained based on the curve of wheel-rail adhesion coefficient variation with speed at the positions of the axles.

5. A real-time sensing system for wheel-rail adhesion of a railway train, characterized in that: The real-time perception system uses the real-time perception method as described in any one of claims 1 to 4, and the real-time perception system includes a wheel-rail adhesion online real-time perception chassis, and the wheel-rail adhesion online real-time perception chassis includes a power supply board, a fault diagnosis board, a signal input and output board, a central processing unit board and a communication board connected in sequence, and the wheel-rail adhesion online real-time perception chassis receives input signals and sends output signals.

6. The real-time sensing system according to claim 5, characterized in that: The input signals include train speed, axle speeds, brake cylinder pressure, moment of inertia, wheel radius and axle weight, and the output signals include adhesion coefficient, slip rate and adhesion force.

7. The real-time sensing system according to claim 6, characterized in that: The input signal input methods include MVB signal input, Ethernet transmission and sensor acquisition, and the input signal also includes piston area, brake cylinder spring back pressure, brake cylinder diameter, friction coefficient, leverage ratio and mechanical efficiency.

Images