Marine rail type vehicle operation safety analysis method

Abstract

The invention relates to the technical field of marine rail-mounted vehicles, and discloses a marine rail-mounted vehicle operation safety analysis method, which comprises the following steps of: 1, establishing a deck-rail coupled finite element model in finite element software; 2, extracting power spectral density functions of motion in different directions under different sea conditions, and carrying out inverse derivation to form shipborne random excitation; step 3, constructing a deck-track-vehicle coupling system dynamic model; 4, inputting shipborne random excitation and track irregularity excitation into the deck-track-vehicle coupling system dynamic model to realize marine environment-oriented track vehicle dynamic behavior analysis; and 5, proposing an evaluation index of the traffic safety of the marine railway vehicle, and obtaining an operation safety evaluation index limit value suitable for the marine railway vehicle. According to the invention, ship motion excitation can be generated by adopting ship motion simulation data, model data and actually measured data, and the ship motion excitation simulation method can be suitable for any ship type.

Description

Technical Field

[0001] The present invention relates to the technical field of marine rail vehicles, and particularly to a method for analyzing the running safety of marine rail vehicles. Background Art

[0002] The operating environment of marine rail transfer vehicles is more complex and changeable than that of traditional railway track vehicles. It not only has to face the inherent risks of standard track operation but also needs to cope with various external influencing factors brought by the marine environment. The waves, wind force, and sea current changes in the marine environment will cause the rolling, pitching, and irregular acceleration of the hull, which in turn leads to the instability of the rail vehicle during operation and the stress concentration problem of its own structure. This greatly limits the driving speed of marine rail vehicles. In addition, when the hull tilts or makes a sharp turn due to the change of the sea wave environment, the offset of the vehicle's center of gravity and the action of centrifugal force exacerbate the risk of derailment and damage to the vehicle and the track. The above factors will greatly affect the running safety of marine rail vehicles. Therefore, realizing the driving safety assessment of rail vehicles on board under complex sea conditions is of great significance for the design of rail vehicles and the improvement of the passing efficiency and safety in actual use.

[0003] However, the existing vehicle dynamics models are for traditional track vehicles, and there is no dynamics model for marine rail vehicles, so it is impossible to simulate the dynamic characteristics of marine rail vehicles during operation. In particular, there is currently no safety evaluation index applicable to marine rail transfer vehicles. Due to their on-board operating conditions and vehicle structures being different, the existing safety indexes are difficult to directly apply to the running safety analysis of marine rail vehicles. Summary of the Invention

[0004] The technical problem to be solved by the present invention is that the existing vehicle dynamics models are for traditional track vehicles, there is no dynamics model for marine rail vehicles, and the existing formed safety indexes are difficult to directly apply to the running safety analysis of marine rail vehicles.

[0005] To solve the above technical problem, the technical solution of the present invention is to provide a method for analyzing the running safety of marine rail vehicles, including the following steps:

[0006] Step 1: Obtain the structural parameters of the marine rail vehicle system and establish a finite element model of deck-rail coupling in finite element software;

[0007] Step 2: Based on the test data of the hull under different sea conditions, extract the power spectral density functions of different directions of motion under different sea conditions, and then generate the on-board random excitation by inverse derivation through the power spectral density functions;

[0008] Step 3: Construct a dynamics model of the deck-rail-vehicle coupling system according to the structural characteristics and dynamic parameters of the marine rail vehicle;

[0009] Step 4: Input the shipborne random excitation and track irregularity excitation into the deck-track-vehicle coupled system dynamics model to realize the dynamic behavior analysis of the railway vehicle for marine environment;

[0010] Step 5: Based on the dynamic response of the marine railway vehicle, propose the evaluation indexes for the running safety of the marine railway vehicle, and combine with the test results of the actual operation conditions. Through mathematical statistics methods, obtain the limit values of the running safety evaluation indexes applicable to the marine railway vehicle, and determine whether the vehicle operation is safe.

[0011] Optionally, in Step 1, adopt the substructure analysis method to reduce the degrees of freedom of the large-size structure finite element model, so as to improve the calculation efficiency of the deck-track coupling model.

[0012] Optionally, Step 1 includes the following steps:

[0013] Step 1.1: Conduct the geometric modeling of the deck and the rail;

[0014] Step 1.2: Conduct the finite element modeling according to the geometric modeling;

[0015] Step 1.3: After the finite element modeling is completed, use the modal method to identify the natural modes and natural frequencies of the track components, and reveal the vibration characteristics and main vibration modes of the track at different frequencies;

[0016] Step 1.4: Conduct the substructure analysis on the finite element model through the modal reduction theory, realize the simplification of the degrees of freedom of the finite element model, and retain the key dynamic characteristics to complete the final finite element model of the deck-track coupling.

[0017] Optionally, in Step 1.4, after the final finite element model of the deck-track coupling is completed, it is necessary to conduct the dynamic characteristic evaluation on the original model and the reduced model of the track components, evaluate the response characteristics of the track under various excitations, and further verify the accuracy of the model.

[0018] Optionally, in Step 2, the power spectral density functions of different motions under different sea conditions are extracted by the probability estimation method.

[0019] Optionally, Step 2 includes the following steps:

[0020] Step 2.1: Use the Fourier transform to obtain the power spectral density, and then fit the power spectral density function through the AR spectrum estimation method;

[0021] Step 2.2: Obtain the time-domain signal of the shipborne random excitation through the inverse Fourier transform, and generate the time-domain signal of the shipborne random excitation;

[0022] Step 2.3: Combine the excitation factors under various sea conditions to simulate the actual dynamic boundary of the hull, and achieve the equivalent simulation of the external excitation of the vehicle system.

[0023] Optionally, in Step 3, a dynamic model of the vehicle-rail-hull coupling system is established through multi-body dynamics theory, which considers the deck, wheel sets, drive chains, drive gears, vehicle frames, and flexible track structures. The flexible track and drive chain are installed on the deck through fasteners, and the fasteners are simulated by spring-damping units. The suspension between the wheels and the bogie is simulated by three-dimensional spring-damping units, and the wheel-rail interaction is solved using Hertz's non-linear elastic contact theory and Kalker's creep theory.

[0024] Optionally, Step 4 specifically includes:

[0025] Apply the shipborne random excitation generated in Step 2 in the form of a function to the center point of the simulation area, apply the unevenness index of the marine rail vehicle as a function of the running distance to the wheel-rail interface, apply the driving torque to the center of the drive gear, and solve the displacement, velocity, acceleration, and dynamic load response of the entire system through numerical integration to achieve the dynamic behavior analysis of the rail vehicle for marine environments.

[0026] Optionally, Step 5 includes the following steps:

[0027] Step 5.1: Construct an operation safety evaluation index system applicable to marine rail vehicles according to the characteristics of the ship and the derailment risk during transportation;

[0028] Step 5.2: Through the dynamic behavior analysis of marine rail vehicles, use the Monte Carlo method to systematically calculate multiple safety indexes of the vehicle under different operating conditions;

[0029] Step 5.3: Using a single index or a cross-combined evaluation method for vehicle stability, operation safety, and wheel-rail dynamic interaction as a support, combined with the test results of actual operating conditions, through mathematical statistics methods such as kernel density estimation, obtain the operation safety evaluation index limits applicable to marine rail transfer vehicles according to the probability density interval;

[0030] Step 5.4: Comprehensively evaluate the dynamic performance and stability of the vehicle under different operating states and conditions, and determine whether the vehicle operation is safe.

[0031] Optionally, the operation safety evaluation index system of the marine rail vehicle in Step 5.1 includes derailment coefficient, wheel load reduction rate, wheel set lift, wheel axle lateral force, and wheel axle vertical force.

[0032] In summary, the present invention has at least one of the following beneficial effects:

[0033] 1. The marine rail vehicle operation safety analysis method proposed by the present invention can generate hull motion excitations using simulated data, model data, and measured data of hull motion. This hull motion excitation simulation method can be applied to any ship type.

[0034] 2. The present invention establishes a rigid-flexible coupling dynamics model of deck-rail-vehicle for marine rail trains. Through modal reduction theory, substructure analysis of the model is carried out to simplify the degrees of freedom of the model while retaining key dynamic characteristics, reducing the computational amount without significantly affecting the model accuracy.

[0035] 3. The present invention inputs the hull motion excitation, characteristics of marine rail transfer vehicles, and track characteristics into the constructed vehicle-rail-deck coupling dynamics system model to calculate the dynamic responses of marine rail vehicles under hull motion, which has important guiding significance for the selection of transfer vehicles, tracks, deck, and reinforcement structure design.

[0036] 4. Based on the operating environment, special vehicle structure, and related dynamic responses of marine rail vehicles, the present invention uses single indicators or cross-combined evaluation methods such as vehicle stability, operation safety, and wheel-rail dynamic interaction as support, and combines mathematical statistics theories such as kernel density estimation to propose a dynamic safety evaluation index system suitable for the driving safety of marine rail transfer vehicles and limits different from railway standards. The present invention can accurately evaluate the driving safety and stability of rail vehicles under complex hull motion states, which has important significance for improving the passing efficiency and transportation safety of marine rail transfer vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic flow chart of a marine rail vehicle operation safety analysis method of the present invention;

[0038] Figure 2 It is a schematic diagram of the dynamics model of the rail vehicle-rail-deck system of the present invention;

[0039] Figure 3 It is the simulation result of the hull motion excitation of the present invention;

[0040] Figure 4 It is the derailment coefficient curve of the marine rail vehicle under the empty car condition in Embodiment 1;

[0041] Figure 5 It is the wheel load reduction rate curve of the marine rail vehicle under the empty car condition in Embodiment 1;

[0042] Figure 6 It is the wheel set lift curve of the marine rail vehicle under the empty car condition in Embodiment 1;

[0043] Figure 7It is the wheel-rail vertical force curve of the marine rail vehicle under the empty vehicle condition in Embodiment 1;

[0044] Figure 8 It is the wheel-rail lateral force curve of the marine rail vehicle under the empty vehicle condition in Embodiment 1;

[0045] Figure 9 It is the derailment coefficient curve of the marine rail vehicle under the condition of carrying 160 tons in Embodiment 2;

[0046] Figure 10 It is the wheel load reduction rate curve of the marine rail vehicle under the condition of carrying 160 tons in Embodiment 2;

[0047] Figure 11 It is the wheel set lift curve of the marine rail vehicle under the condition of carrying 160 tons in Embodiment 2;

[0048] Figure 12 It is the wheel-rail vertical force curve of the marine rail vehicle under the condition of carrying 160 tons in Embodiment 2;

[0049] Figure 13 It is the wheel-rail lateral force curve of the marine rail vehicle under the condition of carrying 160 tons in Embodiment 2. Detailed implementation mode

[0050] The following is combined with Figures 1-13 to further elaborate on the present invention in detail.

[0051] The present invention discloses a method for analyzing the running safety of a marine rail vehicle. The marine rail vehicle refers to a vehicle device specifically used for transporting goods on rails inside a ship. Referring to Figure 1 , it includes the following steps:

[0052] Step 1: Obtain the structural parameters of the marine rail vehicle system, establish a finite element model of deck-rail coupling in finite element software, and adopt the substructure analysis method to reduce the degrees of freedom of the large-size structural finite element model to improve the calculation efficiency of the deck-rail coupling model. Specifically:

[0053] Step 1.1: Conduct geometric modeling of the deck and the steel rail. This process involves accurately modeling flexible components such as the deck and its stiffening structures, and the steel rail, including the shape, size, connecting parts, etc., and then defining the material properties, including elastic modulus, Poisson's ratio, and density, etc., to ensure that the finite element model can accurately reflect the mechanical properties of the actual components;

[0054] Step 1.2: Conduct finite element modeling according to the geometric modeling;

[0055] Step 1.3: After the finite element modeling is completed, use the modal method to identify the natural modes and natural frequencies of the track components, and reveal the vibration characteristics and main vibration modes of the track at different frequencies;

[0056] Step 1.4: Conduct substructure analysis of the finite element model, such as the steel rail and fasteners, through modal reduction theory, simplify the degrees of freedom of the finite element model, retain the key dynamic characteristics, reduce the computational amount, and do not significantly affect the model accuracy to complete the final finite element model of the deck-track coupling;

[0057] After completing the final finite element model of the deck-track coupling, it is necessary to evaluate the dynamic characteristics of the original model and the reduced model of the track components, including natural frequencies and main vibration modes, evaluate the response characteristics of the track under various excitations, and then verify the accuracy of the model; The verification process usually also includes comparing the simulation results of the finite element model with the actual test data to ensure that the model can truly reflect the behavior of the actual track;

[0058] Step 2: Based on the longitudinal, vertical, lateral and other test data of the hull under different sea conditions, extract the power spectral density functions of the motions in different directions under different sea conditions through probability estimation methods, and then generate the shipborne random excitation by inverse derivation of the power spectral density function. The probability estimation method is a method for estimating the overall probability through sample data, which is a statistical inference technique used to estimate one or more probability values from sample data. These methods are based on the principles of probability theory and statistics and aim to infer the characteristics of the population using limited sample information. Specifically, they include:

[0059] Step 2.1: Obtain the power spectral density using Fourier transform, and then fit to obtain the power spectral density function through methods such as AR spectrum estimation;

[0060] Step 2.2: Obtain the time-domain signal of the shipborne random excitation through inverse Fourier transform. The generated time-domain signal of the shipborne random excitation includes the motion signals of the hull's translational and rotational motions in the X, Y, and Z directions;

[0061] Step 2.3: Combine the excitation factors under various sea conditions, including waves, wind, etc., simulate the actual dynamic boundary of the hull, and achieve the equivalent simulation of the external excitation of the vehicle system. Among them, the sea conditions mainly refer to the following two situations. One is under the action of wind, which is divided into 10 levels according to the sea surface conditions within the field of vision, the shape of the wave crest and its degree of breaking, and the appearance of spray foam; The other is the physical, chemical, biological and other properties and their changes in the sea area, including the distribution of temperature, salinity and density, and the distribution of water masses and ocean circulations;

[0062] Step 3: According to the structural characteristics and dynamic parameters of the marine rail vehicle, a dynamic model of the deck-rail-vehicle coupling system is constructed based on the multi-body dynamics theory, which also includes key components such as independent wheels, gear racks, and hydraulic drive. It considers the structures of multiple components including the deck, wheel sets, drive chains, drive gears, vehicle frames, and flexible tracks. Among them, the flexible tracks and drive chains are installed on the deck through fasteners, and the fasteners are simulated by spring-damping units. The suspension between the wheels and the bogie is simulated by three-dimensional spring-damping units, and the wheel-rail interaction is solved using the Hertz non-linear elastic contact theory and the Kalker creep theory;

[0063] Step 4: Input the shipborne random excitation and track irregularity excitation into the dynamic model of the deck-rail-vehicle coupling system to realize the dynamic behavior analysis of the rail vehicle for the marine environment. Specifically:

[0064] The shipborne random excitation generated in Step 2 is applied in the form of a function at the center point of the simulation area. The irregularity indexes such as gauge, level, alignment, and cross level of the track of the marine rail vehicle are applied at the wheel-rail interface as functions of the running distance. The driving torque is applied at the center of the drive gear to realize the motion control of the deck, the simulation of the track irregularity of the marine rail and the vehicle operation, and the coupling of the motion of the marine rail vehicle and the hull motion. The responses of the displacement, velocity, acceleration, and dynamic load of the entire system are solved through numerical integration to realize the dynamic behavior analysis of the rail vehicle for the marine environment, and the dynamic behavior of the vehicle system under different working conditions can be deeply analyzed. These analyses cover the stability, vibration characteristics, and other key performance indexes of the vehicle system;

[0065] Step 5: Based on the dynamic response of the marine rail vehicle, the Monte Carlo method is used to propose evaluation indexes for the running safety of the marine rail vehicle. By calculating relevant indexes such as derailment coefficient, wheel load reduction rate, and wheel lift, and combining with the test results of the actual operation conditions, the limit values of the running safety evaluation indexes applicable to the marine rail vehicle are obtained through mathematical statistics methods to judge whether the vehicle operation is safe. Specifically:

[0066] Step 5.1: According to the characteristics of the ship and the derailment risk during transportation, a running safety evaluation index system applicable to the marine rail vehicle as shown in Table 1 is constructed. The system mainly includes derailment coefficient, wheel load reduction rate, wheel set lift, lateral wheel-axle force, and vertical wheel-axle force;

[0067] Table 1 Running safety evaluation index system for marine rail vehicle

[0068]

[0069] The rolling and pitching motions in the table refer to the six motion states that a ship generally has when sailing in heavy seas and strong winds. They are ROLL (rolling), SWAY (swaying), PITCH (pitching), SURGE (surging), YAW (yawing), and HEAVE (heaving). Generally, we can take a rectangular coordinate system with the center of gravity of the ship as the origin, the X-axis parallel to the hull baseline and pointing forward, the Z-axis perpendicular to the hull baseline and upward, and the Y-axis pointing to the left side of the ship. Then, rolling, pitching, and yawing are the reciprocating rotations around the X, Y, and Z axes respectively, and surging, swaying, and heaving are the reciprocating motions along the X, Y, and Z axes respectively. Among them, pitching, surging, and heaving are called longitudinal motions, and rolling, swaying, and yawing are called lateral motions.

[0070] Step 5.2: By performing a dynamic behavior analysis on the marine rail vehicle, use the Monte Carlo method to systematically calculate multiple safety indicators of the vehicle under different operating conditions;

[0071] Step 5.3: Using a single indicator or a cross-combined evaluation method for vehicle stability, operating safety, and wheel-rail dynamic interaction as a support, combined with the test results of actual operating conditions, through mathematical statistics methods such as kernel density estimation, obtain the operating safety evaluation index limits applicable to marine rail transfer vehicles according to the probability density interval;

[0072] Step 5.4: Comprehensively evaluate the dynamic performance and stability of the vehicle under different operating states and conditions, and determine whether the vehicle is operating safely. Currently, it is divided into three levels: level 3, level 4, and level 5 according to the sea conditions of the transfer operation.

[0073] Embodiment 1

[0074] Taking a certain marine rail transfer vehicle as an example, this transfer vehicle uses a rack and pinion for walking to adapt to the operating conditions. The steel wheels are mainly used for load bearing, and the driving speed is 5 m / min. Figure 2 It is a schematic diagram of the vehicle-rail-deck coupling model. Figure 3 It is the simulated data of the motion of a certain ship input. Use the above method steps to construct the coupling model of the deck-rail-vehicle and simulate and calculate each key index. Figures 4-8 The curves shown are the variation curves of the key index parameters of the transfer vehicle during operation in the unloaded state with the motion time. The curves in the figure are the data of the left and right wheels of the vehicle. It can be seen from the figure that the hull motion under the operating sea conditions shows a relatively random motion, and the hull motion excitation will cause the key indicators of the vehicle to fluctuate violently, and even mutate to produce peaks at some moments. These peak data are the key to evaluating marine rail transfer vehicles, which is completely different from the evaluation of railway rail vehicles. For example, the derailment coefficient and the wheel load reduction rate can reach 3.67 and 1 respectively at low speed in the unloaded state, which are higher than the railway standard limits of 1.2 and 0.65. However, it is found in the dynamic simulation process that the vehicle has no derailment risk. Therefore, marine rail transfer vehicles need to propose index limits different from railway standards according to the maximum operating sea conditions.

[0075] In addition, from Figure 7 it can be seen that the wheel lift is 2 mm, which is less than the flange height, indicating that the vehicle has no derailment risk. However, it should be noted that the wheel lateral force curve shows that there will always be back-and-forth collisions between the wheel and the track, with risks such as component damage.

[0076] Embodiment 2

[0077] Figures 9-13 The figure shows the change curves of various key index parameters of the transporter during operation under a load of 160 tons with the movement time. The curves in the figure are the data of the left and right wheels of the vehicle. It can be seen from the figure that it is completely different from the evaluation of railway track vehicles. For example, the derailment coefficient and wheel load reduction rate can reach 2.03 and 0.15 respectively at a low speed under a load of 160 tons. The derailment coefficient is higher than the railway standard limit of 1.2, but the wheel load reduction rate is less than the railway standard limit. During the dynamic simulation, it is found that the vehicle has no derailment risk;

[0078] In addition, from Figure 7 it can be seen that the wheel lift is 1.5 mm, which is less than the flange height, indicating that the vehicle has no derailment risk. The wheel lateral force curve shows that there will always be back-and-forth collisions between the wheel and the track, with risks such as component damage. The wheel-rail lateral force and vertical force are relatively large, and the track strength needs to be checked.

[0079] The marine rail vehicle operation safety analysis method proposed by the present invention can generate a hull motion excitation by using simulation data, model data and measured data of the hull motion. This hull motion excitation simulation method is applicable to any ship type.

[0080] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A method for analyzing the running safety of marine rail vehicles, characterized in that, It includes the following steps: Step 1: Obtain the structural parameters of the marine rail vehicle system and establish a finite element model of deck-rail coupling in finite element software; Step 2: Based on the test data of the hull under different sea conditions, extract the power spectral density functions of different-direction motions under different sea conditions, and then generate shipborne random excitations through inverse derivation of the power spectral density functions; Step 3: Construct a dynamic model of the deck-rail-vehicle coupling system according to the structural characteristics and dynamic parameters of the marine rail vehicle; Step 4: Input the shipborne random excitation and track irregularity excitation into the dynamic model of the deck-rail-vehicle coupling system to realize the dynamic behavior analysis of the rail vehicle for marine environment; Step 5: Based on the dynamic response of the marine rail vehicle, propose evaluation indexes for the running safety of the marine rail vehicle, and combine with the test results of the actual operation conditions. Through mathematical statistics methods, obtain the limit values of the running safety evaluation indexes applicable to the marine rail vehicle, and judge whether the vehicle operation is safe.

2. The marine orbital vehicle operation safety analysis method according to claim 1, characterized in that, In Step 1, the substructure analysis method is adopted to reduce the degrees of freedom of the large-size structural finite element model to improve the calculation efficiency of the deck-rail coupling model.

3. The marine rail vehicle operation safety analysis method according to claim 2, wherein Step 1 includes the following steps: Step 1.1: Conduct geometric modeling of the deck and the rail; Step 1.2: Carry out finite element modeling according to the geometric modeling; Step 1.3: After the finite element modeling is completed, use the modal method to identify the natural modes and natural frequencies of the track components, and reveal the vibration characteristics and main vibration modes of the track at different frequencies; Step 1.4: Conduct substructure analysis on the finite element model through modal reduction theory, realize the simplification of the degrees of freedom of the finite element model, and retain the key dynamic characteristics to complete the final finite element model of deck-rail coupling.

4. The marine rail vehicle operation safety analysis method according to claim 3, characterized in that, In Step 1.4, after the final finite element model of deck-rail coupling is completed, it is necessary to evaluate the dynamic characteristics of the original model and the reduced model of the track components, evaluate the response characteristics of the track under various excitations, and then verify the accuracy of the model.

5. The method for analyzing the running safety of a marine rail vehicle according to claim 1, wherein, In Step 2, the power spectral density functions of different motions under different sea conditions are extracted by probability estimation methods.

6. The method for analyzing the running safety of a marine rail vehicle according to claim 5, characterized in that, Step 2 includes the following steps: Step 2.1: Use Fourier transform to obtain the power spectral density, and then fit to obtain the power spectral density function through the AR spectrum estimation method; Step 2.2: Obtain the time-domain signal of the shipborne random excitation through inverse Fourier transform, and generate the time-domain signal of the shipborne random excitation; Step 2.3: Combine the excitation factors under various sea conditions to simulate the actual dynamic boundary of the hull and realize the equivalent simulation of the external excitation of the vehicle system.

7. The method for analyzing the running safety of a marine rail vehicle according to claim 1, characterized in that, In Step 3, a dynamic model of the vehicle-rail-hull coupling system is established through multi-body dynamics theory, which considers the deck, wheel sets, drive chains, drive gears, vehicle frames and flexible track structures. The flexible track and drive chain are installed on the deck through fasteners, and the fasteners are simulated by spring-damping units. The suspension between the wheels and the bogies is simulated by three-dimensional spring-damping units. The wheel-rail interaction is solved by using the Hertz nonlinear elastic contact theory and the Kalker creep theory.

8. The method for analyzing the running safety of a marine rail vehicle according to claim 1, characterized in that, The specific content of Step 4 includes: Apply the onboard random excitation generated in Step 2 at the center point of the simulation area in the form of a function, apply the roughness index of the marine rail vehicle as a function of the running distance at the wheel-rail interface, apply the driving torque at the center of the driving gear, and solve the displacement, velocity, acceleration, and dynamic load response of the entire system through numerical integration to achieve the dynamic behavior analysis of the rail vehicle for marine environments.

9. The method for analyzing the running safety of a marine rail vehicle according to claim 1, wherein, Step 5 includes the following steps: Step 5.1: Construct an operation safety evaluation index system applicable to marine rail vehicles according to the characteristics of the ship and the derailment risk during transportation; Step 5.2: Through the dynamic behavior analysis of marine rail vehicles, use the Monte Carlo method to systematically calculate multiple safety indexes of the vehicle under different operating conditions; Step 5.3: With the single index or cross-combined evaluation method of vehicle stability, operation safety, and wheel-rail dynamic interaction as the support, combined with the test results of actual operating conditions, through mathematical statistics methods such as kernel density estimation, obtain the operation safety evaluation index limits applicable to marine rail transfer vehicles according to the probability density interval; Step 5.4: Comprehensively evaluate the dynamic performance and stability of the vehicle under different operating states and conditions, and determine whether the vehicle operation is safe.

10. The method for analyzing the running safety of a marine rail vehicle according to claim 9, characterized in that, The operation safety evaluation index system of the marine rail vehicle in Step 5.1 includes derailment coefficient, wheel load reduction rate, wheel set lift, lateral wheel-axle force, and vertical wheel-axle force.

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