Bullet train driver wind power simulation training method and system

Abstract

The invention belongs to the technical field of wind power simulation training, and particularly relates to a bullet train driver wind power simulation training method and system.The method comprises the steps that S1, the current vehicle speed is obtained through a simulation training instrument interface, and the effective lateral wind speed is calculated in combination with the external wind speed and the wind direction angle; s2, calculating and normalizing transverse wind power based on the effective lateral wind speed, and calculating a final somatosensory amplitude in combination with a vehicle speed coupling gain; s3, calculating roll and transverse movement peak values based on the final somatosensory amplitude, and calculating roll angles and transverse displacement in stages according to wind action time; and S4, converting the roll angle and the transverse displacement into a six-degree-of-freedom platform Y-axis displacement and roll angle instruction, generating a compensation instruction, then forming a smooth motion instruction, and driving a driver seat to complete wind power simulation training. The method can assist in improving the operation judgment capability and the emergency disposal capability of a driver under the extreme strong wind working condition, so that the training has repeatability, adjustability and evaluability.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of simulation training, and particularly relates to a high-speed train driver wind force simulation training method and system. BACKGROUND

[0002] With the rapid growth of high-speed railway operation mileage, the influence of wind force mutation in the line environment such as viaduct bridge, wind outlet section and tunnel exit on the lateral stability of the train is increasingly significant. Crosswind, oblique wind and gust can cause the train to produce lateral deviation, short-period oscillation and attitude disturbance, thereby affecting the judgment and safety handling ability of the driver.

[0003] The prior art cannot meet the demand of simulating the lateral stress and oscillation response of the train under the action of wind force, and cannot independently obtain the external vehicle speed and drive the somatosensory platform, and there is no repeatable, adjustable and quantifiable wind force emergency training. SUMMARY

[0004] The application provides a high-speed train driver wind force simulation training method and system based on external wind force disturbance, non-invasive data acquisition and independent somatosensory platform driving.

[0005] A high-speed train driver wind force simulation training method, comprising: S1, based on the speed area image of the simulation training instrument, obtaining the current vehicle speed, the wind speed, the wind direction angle and the gust frequency of the external wind field, and calculating the effective lateral wind speed based on the wind speed and the wind direction angle; S2, based on the air resistance coefficient, the air density and the effective lateral wind speed, calculating the lateral wind force and normalizing the lateral wind force; based on the vehicle speed coupling gain coefficient, the current vehicle speed and the maximum vehicle speed, calculating the vehicle speed coupling gain; based on the somatosensory amplitude scaling coefficient, the normalized lateral wind force and the vehicle speed coupling gain, calculating the final somatosensory amplitude; S3, based on the final somatosensory amplitude and the roll proportion coefficient, calculating the roll peak value; based on the lateral shift proportion coefficient and the final somatosensory amplitude, calculating the lateral shift peak value; based on the yaw proportion coefficient and the final somatosensory amplitude, calculating the yaw peak value; respectively when the expected duration is greater than or equal to the wind force action time and the wind force action time is greater than the expected duration, based on the roll peak value, the system inherent frequency, the damped oscillation frequency and the damping ratio, calculating the roll angle; based on the lateral shift peak value, the system inherent frequency, the damped oscillation frequency and the damping ratio, calculating the lateral displacement; based on the yaw peak value, the system inherent frequency, the damped oscillation frequency and the damping ratio, calculating the yaw angle; S4, according to the roll angle, lateral displacement, yaw angle and gust frequency, the displacement instruction in Y axis direction, the roll angle instruction and the yaw angle instruction of the six-degree-of-freedom platform are respectively converted through the preset mapping coefficient; based on the displacement instruction and the roll angle instruction, the compensation motion instruction of the remaining degrees of freedom is obtained, and finally the continuous motion simulation training instruction of each degree of freedom of the six-degree-of-freedom platform is obtained; the six-degree-of-freedom platform acts on the motor driver seat through the six-degree-of-freedom motion simulation training instruction, and the wind force simulation training is completed.

[0006] When the expected duration in S3 is greater than or equal to the wind force action time, the roll angle is: , Wherein, is the roll peak value, ζ is the damping ratio, t is the wind force action time, is the damping oscillation frequency, is the system natural frequency; The lateral displacement is: , Wherein, is the lateral displacement peak value.

[0007] The yaw angle is: , Wherein, is the yaw peak value.

[0008] When the wind force action time in S3 is greater than the expected duration, the roll angle is: , Wherein, is the roll angle when the expected duration, ζ is the damping ratio, t is the wind force action time, is the expected duration, is the damping oscillation frequency, is the system natural frequency, is the roll angle balance constant; The lateral displacement is: , Wherein, is the lateral displacement when the expected duration, is the displacement balance constant.

[0009] The yaw angle is: , Wherein, is the yaw angle when the expected duration, is the yaw balance constant In S2, the vehicle speed coupling gain is calculated based on the vehicle speed coupling gain coefficient, the current vehicle speed and the maximum vehicle speed, and the specific method is: , wherein, a is a vehicle speed coupling gain coefficient, S is a current vehicle speed, is a maximum vehicle speed.

[0010] In S4, the final simulation training instruction of each degree of freedom of the six-degree-of-freedom platform is obtained, and the specific operation is as follows: For the displacement instruction and the roll angle instruction in the Y-axis direction, a trajectory is obtained by using a cubic spline interpolation method for fitting, and the trajectory is subjected to acceleration planning processing to obtain the simulation training instruction of each degree of freedom of the six-degree-of-freedom platform.

[0011] In S1, the speed area image of the simulation training instrument is used to obtain the current vehicle speed, and the specific operation is as follows: a high-definition camera fixed in front of the dashboard of the simulation training instrument is used to obtain a region image containing a speed number at a fixed frame rate of not less than 30 Hz, and an optical character recognition technology is used to process the image in real time to extract the vehicle speed value in the form of a number.

[0012] According to the wind force simulation training method for a train driver according to claim 1, in S4, based on the displacement instruction and the roll angle instruction, compensation motion instructions of the remaining degrees of freedom are obtained, and the specific operation is as follows: the remaining degrees of freedom include Z-axis compensation motion instructions, X-axis compensation motion instructions and pitch angle compensation motion instructions, wherein, based on the roll angle instruction, the Z-axis compensation motion instructions and the X-axis compensation motion instructions are obtained; and based on the lateral displacement and the speed component, the pitch angle compensation motion instructions are obtained.

[0013] In S2, the final somatosensory amplitude is obtained, and the specific operation is as follows: , wherein, k is a somatosensory amplitude scaling coefficient, λ is a normalized lateral wind force, and GS is a vehicle speed coupling gain.

[0014] A wind force simulation training system for a train driver is used to implement the wind force simulation training method for a train driver, and comprises: An effective lateral wind speed acquisition module is used to obtain the current vehicle speed based on the speed area image of the simulation training instrument, and to obtain the wind speed, the wind direction angle and the gust frequency of the external wind field, and to calculate the effective lateral wind speed based on the wind speed and the wind direction angle. A somatosensory amplitude acquisition module is used to calculate the lateral wind force based on the air resistance coefficient, the air density and the effective lateral wind speed, to normalize the lateral wind force, to calculate the vehicle speed coupling gain based on the vehicle speed coupling gain coefficient, the current vehicle speed and the maximum vehicle speed, and to calculate the final somatosensory amplitude based on the somatosensory amplitude scaling coefficient, the normalized lateral wind force and the vehicle speed coupling gain. The roll angle lateral displacement acquisition module calculates a roll peak value based on the final body sense amplitude, a roll proportion coefficient, calculates a lateral shift peak value based on the lateral shift proportion coefficient, the final body sense amplitude, calculates a yaw peak value based on the yaw proportion coefficient, the final body sense amplitude, calculates the roll angle based on the roll peak value, the system inherent frequency, the damped oscillation frequency, the damping ratio when the expected duration is greater than or equal to the wind force action time and the wind force action time is greater than the expected duration, calculates the lateral displacement based on the lateral shift peak value, the system inherent frequency, the damped oscillation frequency, the damping ratio, and calculates the yaw angle based on the yaw peak value, the system inherent frequency, the damped oscillation frequency, the damping ratio; The simulation module converts the roll angle, the lateral displacement, the yaw angle and the gust frequency into a displacement instruction in the Y-axis direction, a roll angle instruction and a yaw angle instruction of the six-degree-of-freedom platform through preset mapping coefficients according to the roll angle, the lateral displacement, the yaw angle and the gust frequency; compensation motion instructions of the remaining degrees of freedom are obtained based on the displacement instruction and the roll angle instruction, and finally continuous motion simulation training instructions of each degree of freedom of the six-degree-of-freedom platform are obtained, the six-degree-of-freedom platform applies the six-degree-of-freedom motion simulation training instructions to the motor train driver's seat to complete the wind force simulation training.

[0015] The motor train driver wind force simulation training system further comprises a six-degree-of-freedom motion platform in communication connection with the simulation module, used for receiving and executing the motion simulation training instructions of each degree of freedom, driving the motor train driver's seat fixed thereon to generate corresponding motion and completing the wind force simulation training.

[0016] The motor train driver wind force simulation training method and system have the following beneficial effects: The wind speed, the wind direction, the gust frequency and other external forces are input in real time to convert into train attitude disturbance, so that the driver experiences real-time crosswind / gust dynamic working conditions; The body sense amplitude is calculated by non-intrusive collection of vehicle speed, combination of a wind force stress model and a vehicle speed coupling function, and realization of differential body sense response under different wind speed levels and different vehicle speeds; A two-stage damped pendulum simulation of wind force disturbance is adopted to truly restore the typical wind-affected dynamic characteristics of train side deflection, zero-crossing recovery, reverse pendulum and damping attenuation after crosswind action; The six-degree-of-freedom motion platform is externally connected to provide the driver's seat with uninterrupted, amplitude-controllable, curve-continuous and non-jump body sense feedback, so as to ensure that the body sense effect is completely consistent with the dynamic visual scene; The training is repeatable, adjustable and assessable, and the driver's steering judgment ability and emergency disposal ability under extreme wind conditions are improved. DETAILED DESCRIPTION

[0017] EMBODIMENT In order to further understand the content of the present application, the present application is described in detail in combination with the embodiments.

[0018] The application discloses a high-speed train driver wind force simulation training method, which comprises the following steps. S1, based on the speed area image of the simulation training instrument, the current vehicle speed, the wind speed, the wind direction angle and the gust frequency of the external wind field are obtained, and the effective lateral wind speed is calculated based on the wind speed and the wind direction angle.

[0019] Specifically, the high-definition camera fixed in front of the simulation training instrument panel is used to obtain the area image containing the speed number at a fixed frame rate of not less than 30Hz, the optical character recognition technology is used to process the image in real time, and the vehicle speed value in the form of number and the wind speed, the wind direction angle and the gust frequency of the external wind field are extracted.

[0020] The effective lateral wind speed V is calculated based on the wind speed V and the wind direction angle θ. eff .

[0021] The speed acquisition method does not access internal data and does not damage the original data structure.

[0022] S2, based on the air resistance coefficient, the air density and the effective lateral wind speed, the lateral wind force is calculated, and the normalized lateral wind force is calculated. Based on the vehicle speed coupling gain coefficient, the current vehicle speed and the maximum vehicle speed, the vehicle speed coupling gain is calculated. Based on the somatosensory amplitude scaling coefficient, the normalized lateral wind force and the vehicle speed coupling gain, the final somatosensory amplitude is calculated.

[0023] Further, the specific calculation method is as follows: Lateral wind force: , Wherein, is the resistance coefficient; ρ is the air density; A is the wind area.

[0024] Normalized lateral wind force: , Wherein, λ is the normalized lateral wind force, m is the mass of the vehicle body, and g is the acceleration of gravity.

[0025] Vehicle speed coupling gain G S , specifically: , Wherein, α is the vehicle speed coupling gain coefficient, S is the current vehicle speed, is the maximum vehicle speed.

[0026] The final somatosensory amplitude is specifically: , Wherein,​k is a body sense amplitude scaling factor.

[0027] S3, based on the final body sense amplitude, a roll scaling factor, calculate a roll peak value; based on the lateral scaling factor, the final body sense amplitude, calculate a lateral peak value; based on the yaw scaling factor, the final body sense amplitude, calculate a yaw peak value; respectively when the expected duration is greater than or equal to the wind action time and the wind action time is greater than the expected duration, based on the roll peak value, the system natural frequency, the damped oscillation frequency, the damping ratio, calculate the roll angle; based on the lateral peak value, the system natural frequency, the damped oscillation frequency, the damping ratio, calculate the lateral displacement; based on the yaw peak value, the system natural frequency, the damped oscillation frequency, the damping ratio, calculate the yaw angle.

[0028] The specific calculation method is as follows: The roll peak value is specifically: , wherein, is a roll scaling factor.

[0029] The lateral peak value is specifically: , wherein, is a lateral scaling factor.

[0030] The yaw peak value is: , wherein, is a yaw scaling factor, Wind action stage, when the expected duration is greater than or equal to the wind action time, the roll angle is: , wherein, is a roll peak value, ζ is a damping ratio, t is a wind action time, is an expected duration, is a damped oscillation frequency, is a system natural frequency; The lateral displacement is: , wherein, is a lateral peak value.

[0031] The yaw angle is: , wherein, is a yaw peak value.

[0032] Wind disappears stage, when the wind action time is greater than the expected duration, the roll angle is: , wherein, is the roll angle at the expected time length, ζ is the damping ratio, t is the wind action time, is the expected time length, is the damped oscillation frequency, is the system natural frequency, is the roll angle balance constant, and , The two stages are equal when the expected time length is equal to the wind action time; The lateral displacement is: , wherein, is the lateral displacement at the expected time length, is the displacement balance constant, and The same reasoning applies.

[0033] The yaw angle is: , wherein, is the yaw angle at the expected time length, is the yaw balance constant.

[0034] S4, according to the roll angle, the lateral displacement, the yaw angle and the gust frequency, the displacement instruction in the Y-axis direction, the roll angle instruction and the yaw angle instruction of the six-degree-of-freedom platform are respectively converted through the preset mapping coefficient in the six-degree-of-freedom instructions of the six-degree-of-freedom platform; based on the displacement instruction and the roll angle instruction, the compensation motion instructions of the remaining degrees of freedom are obtained, and finally the continuous motion simulation training instructions of each degree of freedom of the six-degree-of-freedom platform are obtained, the six-degree-of-freedom platform acts on the motor driver seat through the six-degree-of-freedom motion simulation training instructions, and the wind force simulation training is completed.

[0035] Specifically, the displacement instruction in the Y-axis direction is: , wherein, is the platform lateral displacement mapping coefficient, y(t) is the lateral displacement, and the calculation mode in S3 is selected according to t.

[0036] The roll angle instruction is: , wherein, is the platform roll mapping coefficient, is the roll angle, and the calculation mode in S3 is selected according to t.

[0037] The yaw angle is: , wherein, is the platform yaw mapping coefficient, is the yaw angle, and the calculation mode in S3 is selected according to t.

[0038] Based on the displacement instruction and the roll angle instruction, compensation motion instructions of the remaining degrees of freedom are obtained, the remaining degrees of freedom including Z-axis compensation motion instruction ΔZ, X-axis compensation motion instruction ΔX and pitch angle compensation motion instruction Δpitch, wherein the Z-axis compensation motion instruction and the X-axis compensation motion instruction are obtained based on the roll angle instruction; the pitch angle compensation motion instruction is obtained based on the lateral displacement and the velocity component.

[0039] In order to avoid the attitude imbalance, displacement deviation or instantaneous impact of the six-degree-of-freedom platform when performing the main actions such as lateral movement, roll, yaw and the like, an automatic compensation mechanism is introduced to the compensation motion instructions (ΔX, ΔZ, Δpitch) of the remaining degrees of freedom, the real-time change of the main attitude quantity is derived or a nonlinear mapping is constructed to keep the overall attitude stable, and the core compensation relationship is as follows: ; ; ; Wherein, , , are the Z-axis compensation coefficient, the X-axis compensation coefficient and the pitch angle compensation coefficient respectively.

[0040] When the roll angle instruction acts, the center of gravity of the seat will deviate, so the Z-axis compensation motion instruction is introduced, and the relationship makes the seat moderately lift when the roll increases, so as to maintain the subjective horizontal feeling of the driver and avoid the lateral falling feeling. In addition, when the roll angle instruction acts, the upper surface of the seat will be inclined relative to the horizontal plane, so the X-axis compensation motion instruction needs to be generated for the small X-axis compensation. This compensation is used to keep the body center point of the driver from suddenly moving forward and backward with the roll, and the displacement instruction in the Y-axis direction will make the human body feel lateral acceleration. In order to weaken the sudden lateral inertia, the pitch angle compensation motion instruction is used, which adjusts the pitch angle according to the lateral movement speed, so that the action is comfortable and ergonomic.

[0041] At this point, the complete seat position instruction P = [ΔX, ΔY, ΔZ, Δpitch, , Δyaw] is formed, which is a complete six-degree-of-freedom instruction.

[0042] Finally, the continuous six-degree-of-freedom motion simulation training instruction is obtained, and the specific operation is as follows: The displacement instruction in the Y-axis direction and the roll angle instruction are fitted by using the cubic spline interpolation method to obtain the trajectory, and the trajectory is processed by acceleration planning to obtain the motion simulation training instruction of each degree of freedom.

[0043] Further, this six-DOF command is input to the inverse kinematics model, which is a geometric / analytical calculation process for determining the elongation of the seat for completing the wind simulation according to the six-DOF command.

[0044] The length command of the six electric cylinders of the six-DOF platform is obtained through the inverse kinematics model, and thus the compensation process is completed and directly reflected in the final command, and there is no need to explicitly output the compensated ΔX(t), ΔZ(t), and Δpitch(t), but directly obtain the command.

[0045] The length command of the six electric cylinders of the six-DOF platform is smoothed to ensure that the platform motion is free of impact, free of jitter, and continuous in speed and acceleration.

[0046] This is a two-step process: three-spline interpolation path planning and S-curve acceleration planning are jointly completed.

[0047] It should be noted that the six-DOF command is discrete-time point data. Directly connecting these points with straight lines will form a broken line between the points, resulting in a jump in discontinuous speed and thus impact.

[0048] Therefore, the command of each electric cylinder is subjected to three-spline interpolation, with time as the independent variable and the length of the electric cylinder as the dependent variable.

[0049] A set of three polynomial functions is constructed , i.e., the motion path of the electric cylinder, each polynomial is defined on a time : , wherein , , , are interpolation coefficients.

[0050] The following constraints are imposed to ensure the smoothness of the entire path: 1. Passability constraint, must pass through the given point; 2. Continuity constraint, at the internal point t, the first and second derivatives are continuous.

[0051] 3. Boundary condition: the first derivative of the start and end points is usually set to 0, i.e., the speed is 0.

[0052] At this time, a smooth, second-derivable, continuous curve that passes through all discrete target points is obtained, and now both the position and the speed are continuous.

[0053] The problem to be solved by the S-curve acceleration planning is that although the path is smoothed, if the seat tracks the path with constant acceleration or complex variable acceleration, it may still cause acceleration to jump, causing platform vibration and discomfort of the train driver.

[0054] By using S-curve for acceleration planning, the position curve is not directly tracked, but is used as the total distance to obtain a more optimal actual motion trajectory with controlled acceleration change by S-curve planning. The second derivative of the continuous obtained in the last step is processed instead of being re-planned around the spline.

[0055] Specific operation: From the spline curve , identify the sections where the acceleration needs to change significantly, such as the starting point of acceleration from rest, or the turning point from constant speed to deceleration. In these key sections, replace the original possibly steep acceleration process with a preset S-shaped acceleration change template: , where, is the expected acceleration of a certain degree of freedom at time t, is the maximum acceleration planned for the degree of freedom, is the duration of the acceleration rise phase, is the end time of the constant acceleration phase, T f is the end time of the entire acceleration and deceleration process.

[0056] Generate the final trajectory, integrate this new acceleration curve with S-shaped acceleration modification, which is continuous in acceleration, twice. The first integration obtains a smooth velocity curve, and the second integration obtains instructions for controlling the trajectory of the electric cylinder.

[0057] The S-curve acceleration planning optimizes the motion dynamics and softens the acceleration change process, ensuring that the acceleration does not jump, thereby eliminating platform vibration and discomfort caused by excessive jerk.

[0058] Finally, according to the instructions for controlling the trajectory of the electric cylinder, obtain the motion simulation training instructions of each degree of freedom. Take the gust frequency obtained by S1 as the instruction action frequency, apply continuous six-degree-of-freedom motion simulation training instructions to the train driver's seat, and complete the wind force simulation training.

[0059] A train driver wind force simulation training system for implementing the train driver wind force simulation training method described above, comprising: An effective lateral wind speed acquisition module acquires the current vehicle speed, the wind speed, the wind direction angle and the gust frequency of the external wind field based on the speed area image of the simulation trainer, and calculates the effective lateral wind speed based on the wind speed and the wind direction angle; A body sensation amplitude acquisition module calculates the lateral wind force based on the air resistance coefficient, the air density and the effective lateral wind speed, normalizes the lateral wind force, calculates the vehicle speed coupling gain based on the vehicle speed coupling gain coefficient, the current vehicle speed and the maximum vehicle speed, and calculates the final body sensation amplitude based on the body sensation amplitude scaling coefficient, the normalized lateral wind force and the vehicle speed coupling gain. A roll angle and lateral displacement acquisition module calculates the roll peak value based on the final body sensation amplitude and the roll proportion coefficient, calculates the lateral shift peak value based on the lateral shift proportion coefficient and the final body sensation amplitude, calculates the yaw peak value based on the yaw proportion coefficient and the final body sensation amplitude, calculates the roll angle based on the roll peak value, the system inherent frequency, the damped oscillation frequency and the damping ratio when the expected duration is greater than or equal to the wind force action time and when the wind force action time is greater than the expected duration, calculates the lateral displacement based on the lateral shift peak value, the system inherent frequency, the damped oscillation frequency and the damping ratio, and calculates the yaw angle based on the yaw peak value, the system inherent frequency, the damped oscillation frequency and the damping ratio. A simulation module converts the roll angle, the lateral displacement and the yaw angle into the displacement instruction in the Y-axis direction, the roll angle instruction and the yaw angle instruction of the six-degree-of-freedom platform through the preset mapping coefficient based on the displacement instruction and the roll angle instruction, obtains the compensation motion instructions of the remaining degrees of freedom, and finally obtains the continuous motion simulation training instructions of each degree of freedom of the six-degree-of-freedom platform, so that the six-degree-of-freedom platform applies the six-degree-of-freedom motion simulation training instructions to the EMU driver's seat to complete the wind force simulation training.

[0060] An EMU driver wind force simulation training system also includes a six-degree-of-freedom motion platform in communication connection with the simulation module, for receiving and executing the motion simulation training instructions of each degree of freedom, driving the EMU driver's seat fixed thereon to generate corresponding motion, and completing the wind force simulation training.

Claims

1. A wind power simulation training method for high-speed train drivers, characterized in that, include: S1. Based on the speed area image of the simulation training instrument, obtain the current vehicle speed, wind speed, wind direction angle, and gust frequency of the external wind field, and calculate the effective lateral wind speed based on the wind speed and wind direction angle. S2. Calculate the lateral wind force based on the air drag coefficient, air density, and effective lateral wind speed, and normalize the lateral wind force. Calculate the vehicle speed coupling gain based on the vehicle speed coupling gain coefficient, the current vehicle speed, and the maximum vehicle speed; The final perceived amplitude is calculated based on the perceived amplitude scaling factor, the normalized lateral wind force, and the vehicle speed coupling gain. S3. Calculate the peak roll based on the final perceived amplitude and roll ratio coefficient; Calculate the peak value of the lateral shift based on the lateral shift ratio coefficient and the final perceived amplitude; The peak yaw rate is calculated based on the yaw ratio coefficient and the final perceived amplitude. When the expected duration is greater than or equal to the wind's duration and when the wind's duration is greater than the expected duration, Calculate the roll angle based on the roll peak, system natural frequency, damped oscillation frequency, and damping ratio; The lateral displacement is calculated based on the peak lateral displacement, the system's natural frequency, the damped oscillation frequency, and the damping ratio. The yaw angle is calculated based on the peak yaw value, the system's natural frequency, the damped oscillation frequency, and the damping ratio. S4. Based on the roll angle, lateral displacement, yaw angle, and gust frequency, these are converted into displacement, roll angle, and yaw angle commands in the Y-axis direction of the six-degree-of-freedom platform through preset mapping coefficients. Based on the displacement and roll angle commands, compensation motion commands for the remaining degrees of freedom are obtained, ultimately resulting in continuous motion simulation training commands for each degree of freedom of the six-degree-of-freedom platform. The six-degree-of-freedom platform applies these motion simulation training commands to the train driver's seat to complete the wind simulation training.

2. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, When the expected duration of wind action in S3 is greater than or equal to the wind action time and greater than or equal to 0, the roll angle is: ， in, ζ represents the roll peak value, ζ represents the damping ratio, and t represents the duration of wind action. The frequency of the damped oscillation. This is the system's inherent frequency; The lateral displacement is: ， in, This represents the peak value during horizontal shift. The yaw angle is: , in, This represents the peak yaw value.

3. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, When the duration of wind action in S3 is greater than the expected duration, the roll angle is: ， in, Let ζ be the roll angle for the expected duration, ζ be the damping ratio, and t be the duration of wind action. For the expected duration, The frequency of the damped oscillation. The system's inherent frequency, This is the roll angle balance constant; The lateral displacement is: ， in, The lateral displacement during the expected duration. It is the displacement equilibrium constant; The yaw angle is: ， in, The yaw angle for the expected duration. This is the yaw balance constant.

4. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, In S2, the vehicle speed coupling gain is calculated based on the vehicle speed coupling gain coefficient, the current vehicle speed, and the maximum vehicle speed, specifically as follows: ， Where α is the vehicle speed coupling gain coefficient, and S is the current vehicle speed. This is the maximum speed.

5. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, In S4, the final simulation training instructions for the continuous motion of each degree of freedom of the six-degree-of-freedom platform are obtained. The specific operation is as follows: For displacement and roll commands in the Y-axis direction, the trajectory is obtained by fitting using cubic spline interpolation. The trajectory is then processed by acceleration planning to obtain continuous motion simulation training commands for each degree of freedom of the six-degree-of-freedom platform.

6. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, S1 obtains the current vehicle speed based on the speed area image of the simulation training instrument. Specifically, a high-definition camera fixed in front of the simulation training instrument panel acquires an area image containing speed numbers at a fixed frame rate of no less than 30Hz. Optical character recognition technology is used to process the image in real time to extract the vehicle speed value in digital form.

7. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, In S4, based on the displacement command and the roll angle command, the compensation motion commands for the remaining degrees of freedom are obtained. Specifically, the remaining degrees of freedom include the Z-axis compensation motion command, the X-axis compensation motion command, and the pitch angle compensation motion command. Among them, the Z-axis compensation motion command and the X-axis compensation motion command are obtained based on the roll angle command; and the pitch angle compensation motion command is obtained based on the lateral displacement and velocity components.

8. The wind power simulation training method for high-speed train drivers according to claim 1, characterized in that, The final perceived amplitude in S2 is as follows: ， Where k is the motion amplitude scaling factor, λ For normalized lateral wind force, G S This is the vehicle speed coupling gain.

9. A wind simulation training system for high-speed train drivers, used to implement the wind simulation training method for high-speed train drivers as described in any one of claims 1-8, characterized in that, include: The effective lateral wind speed acquisition module acquires the current vehicle speed, as well as the wind speed, wind direction angle, and gust frequency of the external wind field, based on the speed area image of the simulation training instrument, and calculates the effective lateral wind speed based on the wind speed and wind direction angle. The motion amplitude acquisition module calculates the lateral wind force based on the air drag coefficient, air density, and effective lateral wind speed, and normalizes the lateral wind force. The vehicle speed coupling gain is calculated based on the vehicle speed coupling gain coefficient, the current vehicle speed, and the maximum vehicle speed; the final perceived amplitude is calculated based on the body amplitude scaling coefficient, the normalized lateral wind force, and the vehicle speed coupling gain. The roll angle lateral displacement acquisition module calculates the roll peak value based on the final perceived amplitude and roll ratio coefficient. Calculate the peak value of the lateral shift based on the lateral shift ratio coefficient and the final perceived amplitude; Based on the yaw ratio coefficient and the final perceived amplitude, the yaw peak value is calculated; when the expected duration ≥ wind action time ≥ 0 and when the wind action time > expected duration, the roll angle is calculated based on the roll peak value, the system natural frequency, the damping oscillation frequency, and the damping ratio; the lateral displacement is calculated based on the lateral displacement peak value, the system natural frequency, the damping oscillation frequency, and the damping ratio; and the yaw angle is calculated based on the yaw peak value, the system natural frequency, the damping oscillation frequency, and the damping ratio. The simulation module, based on roll angle, lateral displacement, yaw angle, and gust frequency, converts them into displacement, roll angle, and yaw angle commands in the Y-axis direction of the six-degree-of-freedom platform through preset mapping coefficients. Based on the displacement and roll angle commands, the compensation motion commands for the remaining degrees of freedom are obtained, ultimately resulting in continuous motion simulation training commands for each degree of freedom of the six-degree-of-freedom platform. The six-degree-of-freedom platform applies these six-degree-of-freedom motion simulation training commands to the train driver's seat to complete the wind simulation training.

10. A wind power simulation training system for high-speed train drivers according to claim 9, characterized in that, It also includes a six-degree-of-freedom motion platform, which is connected to the simulation module to receive and execute motion simulation training instructions for each degree of freedom, drive the train driver's seat fixed on it to produce corresponding movements, and complete wind power simulation training.

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