Methods for analyzing the probability of derailment of vehicles following a ship-bridge collision; electronic equipment and storage media

Abstract

The present application provides a method for analyzing the probability of train derailment under a ship-bridge collision, an electronic device and a storage medium, and the analysis method includes: obtaining the probability of each level of ship colliding with a bridge after processing in a preset grading manner; based on the ship-bridge collision finite element model, obtaining the ship-bridge collision time-history force under the cross-combination of different graded ship speeds and each level of ship tonnage formed; based on the train-track-bridge coupling model, combining the obtained ship-bridge collision time-history force and the train crossing bridge speed, obtaining the derailment coefficient, wheel weight reduction rate and axle lateral force; based on the respective extreme values ​​of the obtained derailment coefficient, wheel weight reduction rate and axle lateral force, determining the probability of train derailment under each level of ship colliding with the bridge; calling the probability of train driving on the bridge when the ship-bridge collision occurs, determining the sub-probability of train derailment under each level of ship collision; determining the total probability of train derailment under the ship-bridge collision. Using the analysis method of the present application, the obtained train derailment probability is more in line with the actual situation.

Description

Technical Field

[0001] The present application relates to the technical field of bridge safety, and in particular to a method for analyzing the probability of train derailment following a ship-bridge collision, an electronic device and a storage medium. Background Art

[0002] In recent years, accidents involving ships colliding with railway bridges across waterways have occurred frequently. Once a railway bridge is hit by a ship, it may cause deformation and vibration of the bridge deck, affecting the normal service safety of the railway, or even cause train derailment, seriously endangering the safety of life and property. Therefore, accurately obtaining the derailment probability of railway bridges under the action of ship collision is crucial to the safe operation of high-speed railway bridge trains.

[0003] In the process of implementing this application, the inventors found that there are at least the following problems in the prior art:

[0004] At present, there are two main methods for studying the probability of train derailment on cross-waterway railway bridges:

[0005] 1. Monte Carlo simulation method: The basic idea of ​​this simulation method is the law of large numbers, that is, when a certain experiment is repeated a large number of times, the final frequency will be infinitely close to the probability of the event. In actual simulation, as long as the number of samples is large enough, the frequency of the event can be considered to be the probability of the event. When using the Monte Carlo simulation method to estimate the probability of small failures such as train derailment events, a very large number of samples is required, the time cost is high, and the calculation efficiency is low, which is difficult for engineers to accept.

[0006] 2. Extreme value probability density evolution method: This method is based on the basic idea of ​​probability density evolution. By constructing a virtual random process, the extreme value of the random structural dynamic response is the cut-off random variable of the virtual random process. Then, the probability density evolution method is used to establish the probability density evolution equation and solve the extreme value distribution of the random structural dynamic response. The extreme value probability density evolution method is generally based on the condition that the external excitation has occurred to discuss the derailment probability, without considering the probability of the external excitation occurring.

[0007] The existing train derailment probability calculation method lacks in-depth research on the train derailment probability under ship-bridge collision, so that the train operation safety analysis results under ship-bridge collision are inconsistent with the actual situation, which leads to a large difference between the predicted results and the actual results of the train derailment probability, which seriously threatens the safety of railway bridge train operation.

[0008] Therefore, a method for analyzing the probability of train derailment due to ship-bridge collision, an electronic device and a storage medium are needed to at least partially solve the above technical problems. Summary of the invention

[0009] In view of this, the present application provides a method, electronic device and storage medium for analyzing the probability of train derailment in the event of a ship-bridge collision, and the obtained train derailment probability is more in line with the actual situation.

[0010] A first aspect of the present application provides a method for analyzing the probability of train derailment due to a ship-bridge collision, the method comprising the following steps:

[0011] Obtain the probability of each level of ship hitting the bridge after processing in a preset classification method;

[0012] Based on the finite element model of ship-bridge collision, the time-history force of ship-bridge collision under different graded ship speeds and the cross-combination of ship tonnage of each grade formed is obtained;

[0013] Based on the train-track-bridge coupling model, the derailment coefficient, wheel load reduction rate and wheel axle lateral force are obtained;

[0014] Based on the obtained extreme values ​​of derailment coefficient, wheel load reduction rate and wheel axle lateral force, the probability of train derailment under each level of ship hitting the bridge is determined;

[0015] The probability of a train running on a bridge when a ship-bridge collision occurs is called, and the sub-probability of train derailment when a ship-bridge collision occurs at each level is determined;

[0016] Determine the total probability of train derailment following a ship-bridge collision.

[0017] In some embodiments of the present application, the processing according to a preset classification method specifically refers to:

[0018] Ships are classified according to their tonnage based on actual waterway information.

[0019] In some embodiments of the present application, the obtaining of the probability of each level of ship colliding with the bridge formed after processing in a preset grading manner includes:

[0020] Based on the probability calculation model of ship collision with bridge, the probability P of the i-th level ship colliding with the bridge is obtained. O，i ;P O，i =(N i )(PA i )(PG i )

[0021] Where i = 1, 2, ... J, J represents the number of ship tonnage classifications, N i represents the traffic volume of the i-th type of ship, PA i represents the deviation probability of the i-th type of ship, PG i It represents the geometric probability of the possibility that the i-th type ship will hit the bridge after deviation.

[0022] In some embodiments of the present application, determining the probability of train derailment when each level of ship hits a bridge based on the obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and wheel axle lateral force comprises:

[0023] The obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force are compared with the corresponding set standard values ​​to determine the number of events in which one or more of the extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force exceed the limit and take a guarantee rate of 90% to 95%;

[0024] Call the number of events of each level of ship hitting the bridge to determine the probability of train derailment when the i-th level ship hits the bridge

[0025] Among them, D i Indicates the event corresponding to the extreme value of derailment coefficient, wheel load reduction rate and axle lateral force exceeding the limit and taking the guarantee rate of 90% to 95%, B i Indicates the i-th level ship collision bridge event.

[0026] In some embodiments of the present application, the determination of the sub-probability of derailment of the vehicle underway by collision of each level of ship specifically refers to:

[0027] The probability of derailment of the train when the i-th level ship hits it

[0028] Among them, P T It represents the probability of the train running on the bridge when the ship and bridge collide.

[0029] In some embodiments of the present application, the derailment coefficient, wheel load reduction rate and wheel axle lateral force are obtained based on the train-track-bridge coupling model, including:

[0030] According to the statistical analysis results of the actual running speed of the cross-waterway railway bridge train when crossing the bridge, the selected set train crossing speed is input into the train-track-bridge coupling model respectively;

[0031] The obtained ship-bridge collision time history force is input into the train-track-bridge coupling model as external excitation;

[0032] After simulation calculation, the train-track-bridge coupling model outputs the derailment coefficient, wheel load reduction rate and wheel axle lateral force.

[0033] In some embodiments of the present application, the set train speed across the bridge includes the minimum speed of the train across the bridge, the maximum speed of the train across the bridge, and the most frequent speed of the train across the bridge.

[0034] In some embodiments of the present application, the ship-bridge collision finite element model includes a bridge subsystem and a ship subsystem. The bridge subsystem is modeled in full scale according to the actual bridge site information, and the collision ship selection and ship collision speed of the ship subsystem are modeled according to the actual navigation information; wherein, the collision ship selection includes barges and ships, and the ship collision speed includes the general speed of the largest tonnage ship in the actual waterway and the general speed of the ship with the largest navigation flow. And / or

[0035] The obtaining of the bridge collision time history force under the cross combination of different graded ship speeds and the formed ship tonnage of each grade of ships includes:

[0036] The data formed by cross-combining each level of ship speed and each level of ship tonnage are respectively input into the ship-bridge collision finite element model;

[0037] The finite element model of ship-bridge collision obtains the corresponding ship-bridge collision time-history force through finite element numerical simulation calculation.

[0038] A second aspect of the present application provides an electronic device, the electronic device comprising:

[0039] A memory for storing computer executable instructions;

[0040] The processor is used to implement the analysis method described in the above embodiment when executing the computer executable instructions stored in the memory.

[0041] A third aspect of the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the analysis method described in the above embodiment is implemented.

[0042] According to the analysis method of the embodiment of the present application, the probability of train derailment under the impact of each level of ship is calculated separately by ship classification, which is more accurate and computationally efficient than only using the standard recommended data based on deterministic thinking and subjective. Based on the full probability calculation method, the probability of ship-bridge collision and the probability of the train running on the bridge when the ship-bridge collision occurs are taken into account, and the probability of train derailment in the whole process is calculated, so that the probability of occurrence of external excitation can be reflected, the fitting accuracy is higher, and the calculated probability of train derailment is more consistent with the actual engineering conditions.

[0043] Additional advantages, purposes, and features of the present application will be partially described in the following description, and will become partially apparent to those skilled in the art after studying the following, or may be learned from the practice of the present application. The purposes and other advantages of the present application can be achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0044] Those skilled in the art will understand that the purposes and advantages that can be achieved by the present application are not limited to the above specific description, and the above and other purposes that can be achieved by the present application will be more clearly understood based on the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The drawings described herein are used to provide a further understanding of the present application, constitute a part of the present application, and do not constitute a limitation of the present application. The components in the drawings are not drawn to scale, but are only for the purpose of illustrating the principles of the present application. In order to facilitate the illustration and description of some parts of the present application, the corresponding parts in the drawings may be enlarged, that is, they may become larger relative to other components in the exemplary device actually manufactured according to the present application. In the drawings:

[0046] Figure 1 is an overall flow chart of an analysis method according to an embodiment of the present application;

[0047] Figure 2 is a schematic diagram of a train-track-bridge coupling model in an analysis method according to an embodiment of the present application;

[0048] Figure 3 A schematic diagram of a finite element model of a ship-bridge collision and a time-history force curve of a ship-bridge collision in an analysis method according to an embodiment of the present application;

[0049] Figure 4 is a curve diagram of a safe speed threshold value for a train crossing a bridge according to an embodiment of the present application;

[0050] Figure 5 is a schematic block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the implementation modes and the accompanying drawings. Here, the illustrative implementation modes and descriptions of the present application are used to explain the present application, but are not intended to limit the present application.

[0052] It should also be noted here that in order to avoid obscuring the present application due to unnecessary details, only the structures and / or processing steps closely related to the scheme according to the present application are shown in the accompanying drawings, while other details that are not very relevant to the present application are omitted.

[0053] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0054] It should also be noted that, unless otherwise specified, the term “connection” herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0055] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0056] First, refer to Figure 1 The following describes a method 100 for analyzing the probability of train derailment due to a ship-bridge collision according to an embodiment of the present application. Figure 1 As shown, Figure 1 The overall flow chart of the analysis method according to one embodiment of the present application. The method 100 for analyzing the probability of train derailment due to ship-bridge collision may include the following steps:

[0057] In step S110, the probability of each level of ship colliding with the bridge formed after processing in a preset grading manner is obtained.

[0058] In step S120, based on the ship-bridge collision finite element model, the ship-bridge collision time-history forces under cross-combinations of different graded ship speeds and the formed ship tonnages of each grade of ships are obtained.

[0059] In step S130, based on the train-track-bridge coupling model, the derailment coefficient, wheel load reduction rate and wheel axle lateral force are obtained.

[0060] In step S140, the probability of train derailment after each level of ship hits the bridge is determined based on the obtained extreme values ​​of the derailment coefficient, wheel load reduction rate and wheel axle lateral force.

[0061] In step S150, the probability of a train running on a bridge when a ship-bridge collision occurs is called to determine the sub-probability of train derailment when a ship collision occurs at each level.

[0062] In step S160, the total probability of train derailment due to ship-bridge collision is determined.

[0063] According to the analysis method of the present application, firstly, the probability of each level of ship colliding with the bridge formed after the (all) ships to be analyzed are processed in a preset classification method, and then based on the finite element model of ship-bridge collision, the ship-bridge collision time-history force under the cross-combination of each level of ship speed after the ship speed classification and the ship tonnage of each level of ships formed is obtained, and the ship-bridge collision time-history force and the train bridge speed are respectively input into the train-track-bridge coupling model to obtain three important indicators: derailment coefficient, wheel weight reduction rate and wheel axle lateral force, and then the extreme values ​​of the above three indicators are compared with the corresponding standard values ​​to determine the probability of train derailment under each level of ship colliding with the bridge, and then the probability of train driving on the bridge when the ship-bridge collision is called to determine the sub-probability of train derailment under each level of ship collision, and finally the total probability of train derailment under the ship-bridge collision is determined.

[0064] Through the description of the above process, this analysis method uses the ship classification method to calculate the train derailment probability under the impact of each level of ship. Compared with only using the standard recommended data based on deterministic thinking and subjective, it is more accurate; based on the full probability calculation method, the probability of ship-bridge collision and the probability of train driving on the bridge when the ship-bridge collision occurs are taken into account, and the train derailment probability under the whole process is calculated, so that the probability of occurrence of external excitation can be reflected. The calculated train derailment probability is more consistent with the actual engineering conditions, and the calculation efficiency of the entire analysis method is higher.

[0065] The contents of the above steps of the analysis method 100 according to the embodiment of the present application will be described in detail below.

[0066] In an embodiment of the present application, in step S110, the probability of each level of ship colliding with the bridge formed after processing in a preset grading manner is obtained.

[0067] Specifically, in order to obtain the probability of each level of ship hitting the bridge, the probability P of the i-th level ship hitting the bridge can be obtained based on the ship hitting the bridge probability calculation model: O，i ;

[0068] P O，i =(N i )(PA i )(PG i )

[0069] Where i = 1, 2, ... J, J represents the number of ship tonnage classifications. i Represents the traffic volume of the i-th type of ships. i PG represents the deviation probability of the i-th type of ship. i It represents the geometric probability of the possibility that the i-th type ship will hit the bridge after deviation.

[0070] The probability of ship-bridge collision can be calculated by observation statistics and empirical mathematical model. The embodiment of the present application adopts the ship-bridge collision probability calculation model with strong operability in the empirical mathematical model method to obtain the probability of each level of ship collision. The ship-bridge collision probability calculation model can adopt an existing calculation model, such as the AASHTO standard model.

[0071] Before performing step S110, the ship to be analyzed needs to be processed according to a preset classification method. Specifically, the ships are classified according to the ship tonnage according to the actual channel information, and the ship tonnage is divided into J levels according to size.

[0072] Taking a high-speed cross-channel railway bridge (four-span continuous beam bridge) as an example, due to the complex composition of ship types in the actual navigation channel, the tonnage of ships ranges from less than 1000DWT to more than 8000DWT. In order to facilitate the risk analysis of ship collision, for small and medium-sized tonnage ships, a large number of 1000DWT and 3000DWT cargo ships can be selected as representative ship types for analysis. For large tonnage ships, typical 5000DWT and 8000DWT ships are selected as representative ship types for analysis. Therefore, reasonable classification can be carried out with the tonnage of the above representative ship types as the classification node.

[0073] Of course, the ships to be analyzed in this application refer to all ships passing through the navigation channel within a certain period of time. The probability of train derailment due to ship-bridge collision in this application also refers to the total probability of train derailment due to ship-bridge collision within this period of time.

[0074] In an embodiment of the present application, in step S120, based on the ship-bridge collision finite element model, the ship-bridge collision time-history forces under cross-combinations of different graded ship speeds and the ship tonnages of each grade of ships formed are obtained.

[0075] Specifically, the data formed by cross-combining each level of ship speed after the ship speed of the ship to be analyzed and the ship tonnage of each level formed in step S110 are respectively input into the ship-bridge collision finite element model. The ship-bridge collision finite element model obtains the corresponding ship-bridge collision time-history force F(t) through finite element numerical simulation calculation.

[0076] For example, the speed of all ships is divided into K levels according to the size of the ship speed. The ship tonnage is divided into J levels, so the cross-combined data has a total of J*K groups. Then the corresponding simulation calculates the J*K groups of ship-bridge collision time-history forces F(t). The curve of the ship-bridge collision time-history force F(t) can be referred to Figure 3 .

[0077] Therefore, before performing step S120, the ship speeds to be analyzed need to be classified. The ship speeds of all ships can be classified according to the size of the ship speeds, for example, divided into K levels. The ship tonnage is divided into J levels, so the cross-combined data has a total of J*K groups.

[0078] In addition, before performing step S120, a finite element model of ship-bridge collision needs to be established. Figure 3 The finite element model of ship-bridge collision includes the bridge subsystem and the ship subsystem. The bridge subsystem is modeled in full scale according to the actual bridge site information. The collision ship selection of the ship subsystem is divided into barges and ships. Barges have shallow drafts, and ships have deep drafts. The ship collision speed adopts representative typical ones, such as the general speed of the largest tonnage ship in the actual waterway, the general speed of the ship with the largest navigation flow, etc.

[0079] When establishing the finite element model of ship-bridge collision, according to the actual channel information, the explicit dynamic finite element software LS-DYNA can be used to establish the ship-bridge collision finite element model composed of the bridge subsystem and the ship subsystem, and then the dynamic analysis can be carried out to extract the ship collision time-history force F(t).

[0080] In the embodiment of the present application, in step S130, the derailment coefficient, wheel load reduction rate and wheel axle lateral force are obtained based on the train-track-bridge coupling model. Figure 1 and Figure 2 , step S130 may include the following steps:

[0081] In step S131, according to the statistical analysis results of the actual running speed of the cross-waterway railway bridge train when crossing the bridge, the selected set train crossing speed is input into the train-track-bridge coupling model respectively.

[0082] In step S132, the obtained ship-bridge collision time history force is input into the train-track-bridge coupling model as an external excitation.

[0083] In step S133, the train-track-bridge coupling model outputs the derailment coefficient, wheel load reduction rate and wheel axle lateral force after simulation calculation.

[0084] Specifically, in step S131, according to the statistical analysis results of the actual running speed of the cross-waterway railway bridge train, the selected set train crossing speed is input into the train-track-bridge coupling model. Figure 2 The train-track-bridge coupling model is an existing model in the industry, such as a finite element model established using Simpack software. Figure 2 The example is a schematic diagram of the train-track-bridge coupling model when the impact speed is 3m / s, the impact ship is 1000DWT, and the impact position is 6m away from the pier. The selected set train crossing speed can include the minimum speed of the train crossing the bridge, the maximum speed of the train crossing the bridge, and the most frequent speed of the train crossing the bridge. First, the set train crossing speed is input into the train-track-bridge coupling model.

[0085] Next, a series of ship-bridge collision time-history forces F(t) obtained in step S120 are input as external excitations into the train-track-bridge coupling model. Finally, the train-track-bridge coupling model performs simulation analysis based on the input set train crossing speed and the ship-bridge collision time-history force F(t), and can directly obtain the three indicators of derailment coefficient Q / P, wheel weight reduction rate ΔP / P and wheel axle lateral force Q. Alternatively, the train-track-bridge coupling model performs simulation analysis based on the input set train crossing speed and the ship-bridge collision time-history force F(t) to obtain the wheel-rail interaction force, and then calculates the three indicators of derailment coefficient Q / P, wheel weight reduction rate ΔP / P and wheel axle lateral force Q from the extreme value of the wheel-rail interaction force.

[0086] Where Q is the lateral force of the wheel axle, that is, the lateral force acting on the wheel. P is the vertical force of the wheel axle, that is, the vertical force acting on the wheel. ΔP is the load reduction of the wheel on the load-reducing side, and P′ is the average static wheel weight of the wheel on the load-reducing and load-adding sides.

[0087] It is worth noting that it is not enough to judge the driving safety performance only by the derailment coefficient. The derailment coefficient only takes into account the balance of force on the wheels, while the wheel weight reduction rate takes into account the balance of force on the left and right wheels of a wheelset. The regulation of the axle lateral force is to avoid the danger caused by the movement of the guard plate due to excessive lateral force. Therefore, the three indicators of derailment system, wheel weight reduction rate and axle lateral force need to be calculated to comprehensively consider the probability of train derailment.

[0088] It is important to note that the ship-bridge collision is a time-varying process, in which the derailment coefficient, wheel weight reduction rate and axle lateral force also change with time. Therefore, the derailment coefficient, wheel weight reduction rate and axle lateral force obtained from the train-track-bridge coupling model are essentially a series of corresponding curves of these three indicators changing with time. Thus, the extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force can be obtained.

[0089] In order to make the calculation results more accurate and reliable, structural elastic-plasticity and wheel-rail non-contact can be considered in the simulation analysis of the train-track-bridge coupling model. Among them, structural elastic-plasticity is simulated by selecting elastic-plastic materials in the train-track-bridge coupling model, and Hertz nonlinear elastic contact theory is used to solve the wheel-rail interaction force (mainly the wheel axle lateral force Q and the wheel axle vertical force P) to consider the wheel-rail non-contact.

[0090] In an embodiment of the present application, in step S140, the probability of train derailment when each level of ship hits the bridge is determined based on the obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and wheel axle lateral force.

[0091] Since the three indicators of derailment coefficient, wheel weight reduction rate and axle lateral force are obtained in step S130, it is actually a series of corresponding curves of the three indicators changing with time. Based on this, the extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force are obtained.

[0092] Specifically, step S140 may include the following steps:

[0093] In step S141, the obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force are compared with the corresponding set standard values ​​to determine the number of events in which one or more of the extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force exceed the limit and take a guarantee rate of 90% to 95%.

[0094] In step S142, the number of events of ships hitting bridges at each level is called to determine the probability of train derailment when the i-th level ship hits the bridge. Among them, D i Indicates the event corresponding to the extreme value of derailment coefficient, wheel load reduction rate and axle lateral force exceeding the limit and taking the guarantee rate of 90% to 95%, B i Indicates the i-th level ship collision bridge event.

[0095] Specifically, in step S141, the corresponding set standard value, i.e., the evaluation standard for preventing wheel derailment stability, can refer to representative Chinese standards, European standards, and Japanese standards. As shown in Table 1, according to the safety limit value regulations given in the specification, the minimum value is selected as the safety limit value (set standard value) used in the present invention, i.e., derailment coefficient Q / P≤0.8, wheel weight reduction rate ΔP / P≤0.6, and wheel axle lateral force Q≤10+P st / 3(P st is the static axle weight).

[0096] Table 1 Regulations of various countries on train driving safety indicators

[0097]

[0098] It should be noted that high-speed train derailment is a continuous process, and it is not reasonable to judge that train derailment occurs by overrunning a single derailment index instantaneous value that is more common in the prior art. Therefore, the present application adopts one or more overrunning and taking 90% to 95% guarantee rate in the extreme value of derailment coefficient, wheel weight reduction rate and axle lateral force as the judgment method of train derailment, which is more accurate and fits the actual situation. When the extreme value of derailment coefficient, wheel weight reduction rate and axle lateral force is compared with the corresponding set standard value, statistical probability analysis method etc. is utilized to determine the number of events that one or more overrunning and taking 90% to 95% guarantee rate in the extreme value of derailment coefficient, wheel weight reduction rate and axle lateral force.

[0099] In addition, by comparing the obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and wheel axle lateral force with the corresponding set standard values, the safe speed threshold of high-speed trains crossing the bridge under different collision load intensities can also be obtained.

[0100] Specifically, in step S120, the cross combination of different graded ship speeds and the ship tonnage of each grade of ship is performed, each combination corresponds to a collision load intensity, and each collision load intensity is combined with different train bridge speeds, and then in Simpack software (train-track-bridge coupling model), the extreme values ​​(i.e., the extreme values ​​of derailment coefficient, wheel weight reduction rate, and wheel axle lateral force) of three derailment indices are analyzed and calculated. If a collision load intensity and b train bridge speed combination calculate three derailment index extreme values ​​and all do not exceed the specification requirements (i.e., the corresponding set standard value), then a collision load intensity and any combination of b train speed that is less than or equal to belong to the safe area. If three derailment index extreme values ​​all exceed the specification requirements, then a collision load intensity and any combination of b train speed that is greater than or equal to belong to the danger zone. Here, between the two types of situations, it is defined as the warning area. The maximum speed of train operation in the safe area under each collision load intensity is the high-speed train safe bridge speed threshold value, and if the train speed exceeds this threshold value under this collision load intensity, derailment may occur.

[0101] See also Figure 4 , which is a curve of the safe speed threshold for trains crossing a bridge, vividly shows the division of safe areas, dangerous areas and warning areas.

[0102] Next, in step S142, the number of events of ships hitting bridges at each level is called to determine the probability of train derailment when the i-th level ship hits the bridge. That is, the probability of train derailment under the i-th level ship hitting the bridge is is the conditional probability, which is equal to the number of events in which one or more of the extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force exceed the limit and take a guarantee rate of 90% to 95% divided by the number of events in which the i-th level ship hits the bridge.

[0103] Among them, D i Indicates the event corresponding to the extreme value of derailment coefficient, wheel load reduction rate and axle lateral force exceeding the limit and taking the guarantee rate of 90% to 95%, B i represents the i-th level ship collision bridge event. The number of each level of ship collision bridge events can be obtained by counting the ship-bridge collision accidents of other bridges in the bridge site area or other methods.

[0104] In the embodiment of the present application, the probability of a train running on a bridge when a ship-bridge collision occurs is called in step S150 to determine the sub-probability of train derailment when a ship-bridge collision occurs at each level. f，iSpecifically, the probability of derailment of the train when the i-th level ship hits the track is

[0105] Among them, P T It indicates the probability of a train running on a bridge when a ship-bridge collides. It can also be obtained by counting ship-bridge collision accidents on other bridges in the bridge site area or by other means.

[0106] In the embodiment of the present application, the total probability P of train derailment due to ship-bridge collision is determined in step S160. f The total probability of train derailment after ship-bridge collision is P f , using the total probability calculation principle, the probability P of all graded ships hitting the train derailment is f，i The sum of P f =∑P f，i .

[0107] Previous research methods on the probability of train derailment have many limitations, such as low calculation efficiency or failure to reflect the probability of external excitation, which are difficult to be accepted by actual projects. In addition, most of the current research literature on train derailment is based on earthquake effects, and research on the probability of train derailment caused by ship-bridge collision is rare. This application proposes a method for analyzing the probability of train derailment caused by ship-bridge collision from the perspective of full probability analysis and ship-bridge collision.

[0108] Based on the above description, according to the analysis method 100 of the embodiment of the present application, the probability of ship-bridge collision and the probability of the train on the bridge when the ship-bridge collision occurs are combined with the probability of ship collisions of various levels and types obtained based on the ship-bridge collision risk analysis, and the failure probability of the train passing through the cross-channel bridge under the risk of ship collision is finally calculated based on the full probability model, so that the probability of external excitation is reflected in the final probability of train derailment, which is in line with the actual engineering conditions. That is, a relatively simple and efficient method is adopted to realize the risk assessment of the low-probability event of train derailment caused by ship collisions with bridges, which provides a scientific basis for the safety protection and early warning of ship collisions on cross-channel railway bridges.

[0109] The above exemplary illustrates the method 100 for analyzing the probability of train derailment due to ship-bridge collision according to an embodiment of the present application. Figure 5 Another aspect of the present application provides an electronic device 200 .

[0110] Reference Figure 5The electronic device 200 is used to implement the method for analyzing the probability of train derailment due to ship-bridge collision according to the embodiment of the present application. The electronic device 200 may include one or more processors 221, one or more memories 222, and may also include an input device 223 and an output device 224. These components are interconnected via a bus system 225 and / or other forms of connection mechanisms (not shown). It should be noted that Figure 5 The components and structures of the electronic device 200 shown are merely exemplary and non-limiting. The electronic device may also have other components and structures as required.

[0111] The processor 221 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 220 to perform desired functions.

[0112] The memory 222 may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 221 may run the program instructions to implement the client functions (implemented by the processor) in the embodiments of the present application described herein and / or other desired functions. Various applications and various data may also be stored in the computer-readable storage medium, such as various data used and / or generated by the application, etc.

[0113] The input device 223 may be a device used by a user to input instructions, and may include one or more of a keyboard, a mouse, a microphone, a touch screen, etc. In addition, the input device 223 may also be any interface for receiving information.

[0114] The output device 224 can output various information (such as images or sounds) to the outside (such as a user), and can include one or more of a display, a speaker, etc. In addition, the output device 224 can also be any other device with an output function.

[0115] Exemplarily, the example electronic device 200 for implementing the analysis method 100 according to the embodiment of the present application can be applied to terminal devices (such as mobile phones), tablet computers, laptops, ultra-mobile personal computers (UMPCs), handheld computers, netbooks, personal digital assistants (PDAs), wearable devices (such as smart watches, smart glasses or smart helmets, etc.), augmented reality (AR) / virtual reality (VR) devices, smart home devices, car computers and other electronic devices, and the embodiments of the present application do not impose any restrictions on this.

[0116] refer to Figure 5 According to the embodiment of the present application, the electronic device 200 includes a processor 221 and a memory 222. The memory 222 stores an executable program run by the processor 221. When the executable program is run by the processor 221, the processor 221 executes the above-mentioned method 100 for analyzing the probability of train derailment after a ship-bridge collision according to the embodiment of the present application. Those skilled in the art can understand the specific operation of the electronic device according to the embodiment of the present application in combination with the above-mentioned contents. For the sake of brevity, the specific details are not repeated here, and only some main operations of the processor 221 are described.

[0117] In one embodiment of the present application, when the executable program is run by the processor 221, the processor 221 executes the following steps: obtaining the probability of each level of ship colliding with the bridge after processing in a preset grading manner; based on the ship-bridge collision finite element model, obtaining the ship-bridge collision time-history force under the cross-combination of different graded ship speeds and the ship tonnage of each level of ships formed; based on the train-track-bridge coupling model, obtaining the derailment coefficient, wheel weight reduction rate and axle lateral force; based on the obtained derailment coefficient, wheel weight reduction rate and axle lateral force, the probability of train derailment under each level of ship colliding with the bridge is determined; calling the probability of train driving on the bridge when the ship-bridge collision occurs, determining the sub-probability of train derailment under each level of ship collision; determining the total probability of train derailment under the ship-bridge collision.

[0118] In one embodiment of the present application, when the executable program is executed by the processor 221, the processor 221 executes the following steps: based on the ship collision probability calculation model, obtain the probability P of the i-th level ship colliding with the bridge O，i ;P O，i =(N i )(PA i )(PG i ), where i = 1, 2, .. J, J represents the number of ship tonnage classifications, Ni represents the traffic volume of the i-th type of ship, PA i represents the deviation probability of the i-th type of ship, PG i It represents the geometric probability of the possibility that the i-th type ship will hit the bridge after deviation.

[0119] In one embodiment of the present application, when the executable program is run by the processor 221, the processor 221 executes the following steps: compare the obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and wheel axle lateral force with the corresponding set standard values, and determine the number of events in which one or more of the extreme values ​​of the derailment coefficient, wheel weight reduction rate and wheel axle lateral force exceed the limit and take a guarantee rate of 90% to 95%; call the number of events of each level of ship colliding with the bridge, and determine the probability of train derailment when the i-th level ship collides with the bridge. Among them, D i Indicates the event corresponding to the extreme value of derailment coefficient, wheel load reduction rate and axle lateral force exceeding the limit and taking the guarantee rate of 90% to 95%, B i Indicates the i-th level ship collision bridge event.

[0120] In addition, according to the present application embodiment, the present application also provides a kind of storage medium, on the storage medium, a computer program is stored, when the computer program is run by the processor, it is used to perform the corresponding steps of the method for analyzing the probability of train derailment under the collision of the ship bridge of the present application embodiment. The storage medium can include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory or any combination of the above-mentioned storage medium. The computer-readable storage medium can be any combination of one or more computer-readable storage media.

[0121] Based on the above description, according to the train derailment probability analysis method due to ship-bridge collision in the embodiment of the present application, the train derailment probability analysis method based on total probability decomposes the probability calculation of train derailment caused by ship-bridge collision into the sum of multiple simple event probabilities, which has good effects in terms of both calculation efficiency and compliance with the actual calculation process, and is more scientific and reliable.

[0122] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely exemplary and are not intended to limit the scope of the present application to this. Those of ordinary skill in the art may make various changes and modifications therein without departing from the scope and spirit of the present application. All these changes and modifications are intended to be included within the scope of the present application as required by the appended claims.

[0123] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0124] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0125] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0126] Similarly, it should be understood that in order to streamline the present application and help understand one or more of the various inventive aspects, in the description of the exemplary embodiments of the present application, the various features of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the method of the present application should not be interpreted as reflecting the following intention: the claimed application requires more features than the features clearly stated in each claim. More specifically, as reflected in the corresponding claims, the inventive point is that the corresponding technical problem can be solved with features less than all the features of a single disclosed embodiment. Therefore, the claims following the specific embodiment are hereby explicitly incorporated into the specific embodiment, wherein each claim itself serves as a separate embodiment of the present application.

[0127] It will be understood by those skilled in the art that, except for mutually exclusive features, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this specification may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature that provides the same, equivalent or similar purpose.

[0128] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0129] The various component embodiments of the present application can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some modules according to the embodiments of the present application. The application can also be implemented as a device program (e.g., computer program and computer program product) for executing a part or all of the methods described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0130] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets should not be constructed as a limitation to the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names.

[0131] The above is only a specific implementation or description of a specific implementation of the present application, and the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. The protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for analyzing the probability of train derailment due to ship-bridge collision, characterized in that: The analysis method comprises: Obtain the probability of each class of ships hitting the bridge after classifying the ships according to their tonnage based on the actual waterway information; Based on the finite element model of ship-bridge collision, the time-history force of ship-bridge collision under different graded ship speeds and the cross-combination of ship tonnage of each grade formed is obtained; According to the statistical analysis results of the actual running speed of the cross-channel railway bridge train, the selected set train crossing speed is input into the train-track-bridge coupling model, and the obtained ship-bridge collision time history force is input into the train-track-bridge coupling model as the external excitation. After simulation calculation, the train-track-bridge coupling model outputs the derailment coefficient, wheel load reduction rate and wheel axle lateral force; The obtained extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force are compared with the corresponding set standard values ​​to determine the number of events in which one or more of the extreme values ​​of the derailment coefficient, wheel weight reduction rate and axle lateral force exceed the limit and take a guarantee rate of 90% to 95%; Call the number of events of each level of ship hitting the bridge to determine the probability of train derailment when the i-th level ship hits the bridge Among them, D i Indicates the event corresponding to the extreme value of derailment coefficient, wheel load reduction rate and axle lateral force exceeding the limit and taking the guarantee rate of 90% to 95%, B i represents the i-th level ship collision bridge event, i = 1, 2, ... J, J represents the number of ship tonnage classifications; The probability of a train running on a bridge when a ship-bridge collision occurs is called, and the sub-probability of train derailment when a ship-bridge collision occurs at each level is determined; Determine the total probability of train derailment following a ship-bridge collision.

2. The analysis method according to claim 1, characterized in that The obtaining of the probability of each level of ship colliding with the bridge formed after processing in a preset grading manner includes: Based on the probability calculation model of ship collision with bridge, the probability P of the i-th level ship colliding with the bridge is obtained. O,i ; P O,i =(N i )(PA i )(PG i ) Among them, N i represents the traffic volume of the i-th type of ship, PA i represents the deviation probability of the i-th type of ship, PG i It represents the geometric probability of the possibility that the i-th type ship will hit the bridge after deviation.

3. The analysis method according to claim 2, characterized in that Determining the sub-probability of derailment of the vehicle due to collision of each level of ship specifically refers to: The probability of derailment of the train when the i-th level ship hits it Among them, P T It represents the probability of the train running on the bridge when the ship and bridge collide.

4. The analysis method according to claim 1, characterized in that The set train bridge crossing speed includes the minimum speed of the train crossing the bridge, the maximum speed of the train crossing the bridge and the most frequent speed of the train crossing the bridge.

5. The analysis method according to claim 1, characterized in that The ship-bridge collision finite element model includes a bridge subsystem and a ship subsystem. The bridge subsystem is modeled in full scale entity according to the actual bridge site information. The collision ship type and ship collision speed of the ship subsystem are modeled according to the actual navigation information; wherein the collision ship type includes barges and ships, and the ship collision speed includes the general travel speed of the largest tonnage ship in the actual waterway and the general travel speed of the ship with the largest navigation flow; and / or The obtaining of the bridge collision time history force under the cross combination of different graded ship speeds and the formed ship tonnage of each grade of ships includes: The data formed by cross-combining each level of ship speed and each level of ship tonnage are respectively input into the ship-bridge collision finite element model; The finite element model of ship-bridge collision obtains the corresponding ship-bridge collision time-history force through finite element numerical simulation calculation.

6. An electronic device, characterized in that: The electronic device comprises: A memory for storing computer executable instructions; A processor, configured to implement the analysis method according to any one of claims 1 to 5 when executing the computer executable instructions stored in the memory.

7. A computer-readable storage medium storing computer-executable instructions, characterized in that: When the computer executable instructions are executed by a processor, the analysis method described in any one of claims 1 to 5 is implemented.

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