A virtual test system for high-speed rail infrastructure

Abstract

The present invention relates to the technical field of high-speed rail virtual testing, and in particular to a high-speed rail infrastructure virtual testing system. The present invention screens out track segments that require speed reduction; for any track segment that requires speed reduction, randomly generates a location point as a bird's nest location, and executes a cuckoo search algorithm; obtains the fitness of each bird's nest location based on the location characteristics of each bird's nest location on the track, and the maximum operating adjustment speed between the track segment where it is located and the next track segment; determines whether the bird's nest location should be discarded by combining the tunnel parameters and location characteristics of different location points within the neighborhood; if it is determined to be discarded, it iteratively updates the bird's nest location to obtain a new bird's nest location until the maximum number of iterations is reached, and uses the bird's nest location corresponding to the maximum fitness value as the optimal idling location point; and operates the high-speed rail. The present invention improves the effectiveness of operational decisions and optimizes the effects of virtual testing by obtaining accurate fitness and discarding methods when the algorithm is in progress.

Description

Technical Field

[0001] The present invention relates to the technical field of high-speed rail virtual testing, and in particular to a high-speed rail infrastructure virtual testing system. Background Art

[0002] In order to reduce the operation and maintenance costs of high-speed rail infrastructure, numerical simulation methods are often used to conduct virtual experiments to reduce the losses of physical experiments. During the operation of high-speed rail, the cruising state is fast but the energy consumption is high, and the inert state is slow but the energy consumption is low. In order to reduce energy consumption and ensure the failure of high-speed rail, reasonable high-speed rail operation strategy planning is needed.

[0003] In the existing technology, the cuckoo search algorithm is used to obtain the overall operation strategy of the high-speed rail through continuous iteration, elimination, and updating of strategies. However, the operating environment of the high-speed rail is changing, and the overall solution may not be applicable to the local operating environment. Moreover, although the completely random abandonment method of the cuckoo algorithm can jump out of the local optimal solution, there is also the possibility of losing the solution applicable to the environment, which affects the superiority of the final strategy and the accuracy of the virtual experiment is poor. Summary of the Invention

[0004] In order to solve the technical problem of poor accuracy of virtual experiments due to the overall strategy of the traditional cuckoo search algorithm and the random rejection method, the purpose of the present invention is to provide a high-speed rail infrastructure virtual testing system. The technical solutions adopted are as follows:

[0005] The present invention proposes a high-speed rail infrastructure virtual testing system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0006] Obtain the simulated track running curve of the high-speed train, and obtain the position coordinates of each position point on the running curve relative to the track starting point and the tunnel parameters;

[0007] Based on the tunnel parameters, height distribution, and curve change trends at different points on the operating curve, multiple track segments are obtained. Based on the tunnel parameters, location characteristics, and preset maximum operating speed at different points in each track segment, the maximum operating adjustment speed of each track segment is obtained. Based on the distribution of the maximum operating adjustment speeds of different track segments, track segments requiring speed reduction are screened out.

[0008] For any track segment requiring speed reduction, randomly generate a location point as the bird's nest location and execute the cuckoo search algorithm. The fitness of each bird's nest location is obtained based on its location characteristics on the track and the maximum operating adjustment speed between the track segment and the next track segment. Based on the fitness of each bird's nest location and the tunnel parameters and location characteristics of different locations within the corresponding neighborhood, determine whether the bird's nest location should be discarded. If it is discarded, it iteratively update the bird's nest location to obtain a new one until the maximum number of iterations is reached. The bird's nest location corresponding to the maximum fitness value is then determined as the optimal coasting location.

[0009] The high-speed rail is operated according to the optimal coasting position point of each track section where speed reduction is required.

[0010] Furthermore, the method for obtaining the track segmentation includes:

[0011] According to the tunnel parameters, height distribution and curve change trend of different points on the running curve, the track consistency between adjacent points is obtained;

[0012] If the track consistency between adjacent position points is greater than or equal to a preset consistency threshold, the corresponding position points are taken as consistent position points; continuous consistent position points are selected to form a track segment, and multiple continuous track segments are obtained.

[0013] Furthermore, the method for obtaining the track consistency includes:

[0014] Obtaining an exclusive OR value of the tunnel parameters between each position point and the adjacent previous position point; obtaining a first sign value of the difference in the height direction between the coordinates of each position point and the adjacent previous position point, and obtaining a second sign value of the difference in the height direction between the coordinates of each position point and the starting point;

[0015] The curvature of each position point on the running curve is obtained and normalized as the curvature consistency; the track consistency between the corresponding adjacent position points is obtained according to the XOR value, the mean absolute value of the first symbol value and the second symbol value, and the curvature consistency between each position point and the adjacent previous position point. The XOR value is negatively correlated with the track consistency, and the mean absolute value of the first symbol value and the second symbol value and the curvature consistency are both positively correlated with the track consistency.

[0016] Furthermore, the method for obtaining the maximum operating adjustment speed includes:

[0017] The number of locations where the tunnel parameters are non-zero in each track segment is obtained as the tunnel length. If all tunnel parameters are zero, the tunnel length is set to 1.

[0018] Obtaining the difference in the height direction between the coordinates of the last position point and the first position point in each track segment as the height difference;

[0019] Obtain the mean curvature of all position points in each track segment and perform negative correlation mapping as the average curvature radius of each track segment;

[0020] The maximum operating adjustment speed of each track segment is obtained based on the preset maximum operating speed, tunnel length, height difference and average curvature radius of each track segment. The preset maximum operating speed and average curvature radius are positively correlated with the maximum operating adjustment speed, while the tunnel length and height difference are negatively correlated with the maximum operating adjustment speed.

[0021] Furthermore, the method for obtaining the track segmentation includes:

[0022] The difference in the maximum operating adjustment speed between the previous track segment and the next track segment is obtained as the speed difference of each track segment. If the speed difference of the track segment is greater than the preset difference threshold, the corresponding track segment is used as the track segment requiring speed reduction.

[0023] Furthermore, the method for obtaining the fitness includes:

[0024] The length between each nest location and the last location point in the track segment is taken as the remaining track length of each nest location;

[0025] Obtain the average of the maximum running adjustment speeds between the track segment where each bird's nest is located and the next track segment as the average running speed; calculate the ratio of the remaining track length to the average running speed as the additional time;

[0026] Obtain the preset resistance of the high-speed rail in the cruising state or coasting state, and obtain the product difference of the preset resistance, additional time and average running speed between different states as the coasting energy saving;

[0027] The ratio of energy saved by idling to the extra time spent was obtained as the fitness of each nest location.

[0028] Furthermore, the determining whether the bird's nest location is abandoned includes:

[0029] The environmental impact of each bird's nest location is obtained based on the tunnel parameters and location characteristics of different locations in the track segment where each bird's nest location is located;

[0030] Obtain the ratio of the fitness of each nest location to the degree of environmental impact, and normalize it as the retention probability of each nest location;

[0031] If the probability of retaining a bird's nest location is less than the preset retention probability, it is determined that the bird's nest location needs to be discarded.

[0032] Furthermore, the method for obtaining the degree of environmental impact includes:

[0033] The product of the tunnel length and the height difference of each track segment is obtained as the first impact degree;

[0034] The ratio of the average curvature radius of each track segment to the first impact degree is obtained and normalized and mapped as the environmental impact degree of each track segment.

[0035] Furthermore, the method for obtaining the neighborhood range includes:

[0036] Taking each bird's nest location as the benchmark, the range formed by other location points after the bird's nest location on the track segment is used as the neighborhood range of each bird's nest location.

[0037] Furthermore, the method for obtaining the preset retention probability includes:

[0038] Based on the cuckoo search algorithm, a random number is randomly generated at each iteration as the preset retention probability.

[0039] The present invention has the following beneficial effects:

[0040] The present invention obtains multiple track segments based on the tunnel parameters, height distribution and curve change trends of different position points on the operating curve, and analyzes the characteristics of different track segments in more detail based on the influence of different factors; based on the tunnel parameters, position characteristics and preset maximum operating speed of different position points in each track segment, the track segments with speed reduction requirements are screened out, and only the track segments with speed reduction requirements are focused on and processed, avoiding unnecessary speed reduction operations; for any track segment with speed reduction requirements, a position point is randomly generated as the bird's nest position, and the cuckoo search algorithm is executed. By executing the algorithm, the best idling position point can be efficiently searched within the track segment with speed reduction requirements, thereby improving the optimization effect. ; According to the position characteristics of each bird's nest position on the track, and the maximum operating adjustment speed between the track segment where it is located and the next track segment, the fitness of each bird's nest position is obtained, and the quality of each bird's nest position as an idling position point is quantitatively evaluated; According to the fitness of each bird's nest position, and the tunnel parameters and position characteristics of different position points in the corresponding neighborhood, it is judged whether the bird's nest position should be abandoned; If it is judged to be abandoned, the bird's nest position is iteratively updated to obtain a new bird's nest position until the maximum number of iterations is reached, and the bird's nest position corresponding to the maximum fitness value is used as the best idling position point. Through continuous iterative updates, the algorithm can continuously search in the solution space and gradually approach the optimal solution; The high-speed rail is operated. The present invention improves the effectiveness of operation decisions and optimizes the effect of virtual experiments by obtaining accurate fitness and abandonment methods when the algorithm is running. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A flowchart of an implementation method of a high-speed rail infrastructure virtual test system provided by one embodiment of the present invention;

[0043] Figure 2 A flow chart of a method for obtaining a maximum operating adjustment speed provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0044] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a high-speed rail infrastructure virtual testing system proposed in accordance with the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0045] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0046] The specific scheme of the high-speed railway infrastructure virtual test system provided by the present invention is described in detail below with reference to the accompanying drawings.

[0047] See also Figure 1 , which shows a flow chart of an implementation method of a high-speed rail infrastructure virtual test system provided by one embodiment of the present invention, the method specifically includes:

[0048] Step S1: Obtain a simulated track operation curve of a high-speed train, and obtain the position coordinates of each position point on the operation curve relative to the track starting point and tunnel parameters.

[0049] In the embodiment of the present invention, in order to retain the excellent strategies that meet the environmental characteristics as much as possible and not be eliminated, and to reduce the overall energy consumption as much as possible under the premise of ensuring timeliness, it is necessary to simulate the environmental model of the high-speed rail train and allocate the state transition of the high-speed rail between cruising and coasting; first, the entire high-speed rail train is regarded as a particle, and the high-speed rail track is modeled using a single particle model. The railway basic model data is collected using a scanner, and the track route is physically modeled, rendered and optimized to obtain a virtual simulation experimental scene of the train and the track route; the starting point of the track is used as the origin of the coordinate system, and the horizontal plane is used as the origin. The plane is taken as the Z axis to form a three-dimensional space coordinate system. The track is fitted to obtain the simulated track operation curve of the high-speed train. The high-speed train can be roughly divided into four operating states during operation, namely traction state, cruising state, coasting state and braking state. The position coordinates of each position point on the operation curve relative to the track starting point and the tunnel parameters are obtained;

[0050] It should be noted that the tunnel parameters can be pre-set according to actual conditions. When the position point on the running curve is in the tunnel, the tunnel parameter is set to 1; when it is not in the tunnel, the tunnel parameter is set to 0.

[0051] Step S2: Based on the tunnel parameters, height distribution, and curve change trends of different points on the operating curve, multiple track segments are obtained; based on the tunnel parameters, location characteristics, and preset maximum operating speed of each point in each track segment, the maximum operating adjustment speed of each track segment is obtained; based on the distribution of the maximum operating adjustment speeds of different track segments, the track segments requiring speed reduction are screened out.

[0052] During the operation of high-speed railways, track paths will appear in various environments such as tunnels, curves, and slopes, which will have different impacts on the high-speed railway. In order to optimize the operation efficiency of high-speed railways, the tracks are segmented according to environmental characteristics; multiple track segments are obtained based on the tunnel parameters, height distribution, and curve change trends at different positions on the operating curve.

[0053] Preferably, in one embodiment of the present invention, the method for obtaining track segments includes:

[0054] According to the tunnel parameters, height distribution and curve change trend of different points on the running curve, the track consistency between adjacent points is obtained;

[0055] Preferably, in one embodiment of the present invention, the method for obtaining track consistency includes:

[0056] Obtaining an exclusive OR value of the tunnel parameters between each position point and the adjacent previous position point; obtaining a first sign value of the difference in the height direction between the coordinates of each position point and the adjacent previous position point, and obtaining a second sign value of the difference in the height direction between the coordinates of each position point and the starting point;

[0057] The curvature of each position point on the running curve is obtained and normalized as the curvature consistency; the track consistency between the corresponding adjacent position points is obtained according to the XOR value, the mean absolute value of the first symbol value and the second symbol value, and the curvature consistency between each position point and the adjacent previous position point. The XOR value is negatively correlated with the track consistency, and the mean absolute value of the first symbol value and the second symbol value and the curvature consistency are both positively correlated with the track consistency.

[0058] It should be noted that the XOR value can reflect whether the tunnel states of the position points are the same. If the tunnel states are different, that is, one is in the tunnel and the other is not in the tunnel, then 1 is output; if the tunnel states are the same, that is, both are in the tunnel or both are not in the tunnel, then 0 is output. Therefore, the smaller the XOR value, the greater the track consistency, which is negatively correlated. Based on the sign function The sign value of the height difference is obtained to reflect the change in slope. When the difference is negative, the sign value is -1, and the lower the slope is. When the difference is positive, the sign value is 1, and the higher the slope is. That is, the more consistent the sign value is, the more consistent the mean absolute value of the first sign value and the second sign value is, the more consistent the slope is, the greater the track consistency is, and they are positively correlated. The curvature consistency reflects the consistency of the track curve. The smaller the curvature, the smaller the curvature consistency, and the smaller the track consistency is, and they are positively correlated.

[0059] In one embodiment of the present invention, the difference between the positive integer 1 and the XOR value is obtained as the tunnel consistency; the average absolute value of the first symbol value and the second symbol value is obtained as the slope consistency; the product of the tunnel consistency, the slope consistency and the curvature consistency is calculated as the track consistency, and thus the correlation between the XOR value, the first symbol value, the second symbol value and the curvature consistency and the track consistency is constructed through the above basic mathematical operations, that is, the smaller the XOR value, the larger the first symbol value, the larger the second symbol value, the greater the curvature consistency and the greater the track consistency.

[0060] If the track consistency between each position point and the previous position point is greater than or equal to a preset consistency threshold, the corresponding point is taken as a consistency point; continuous consistency points are selected to form a track segment, and multiple continuous track segments are obtained.

[0061] It should be noted that, in one embodiment of the present invention, the size of the preset consistency threshold is 0.6. In other embodiments of the present invention, the size of the preset consistency threshold can be set according to specific circumstances, which is not limited or elaborated here.

[0062] Different environmental characteristics have different degrees of impact on the maximum operating speed of high-speed rail. Therefore, by analyzing the environmental characteristics of each track segment, the appropriate maximum operating speed is adjusted; that is, the maximum operating adjustment speed of each track segment is obtained based on the tunnel parameters, location characteristics and preset maximum operating speed of each location point in each track segment.

[0063] Preferably, in one embodiment of the present invention, the method for obtaining the maximum operating adjustment speed is as follows: Figure 2 , which shows a flow chart of a method for obtaining the maximum operating adjustment speed, including:

[0064] Step S201: Obtain the number of locations in each track segment where the tunnel parameters are non-zero as the tunnel length. If all tunnel parameters are zero, the tunnel length is set to 1.

[0065] The more locations where the tunnel parameters are not zero, the longer the tunnel is and the greater the impact on the running speed.

[0066] Step S202: obtaining the difference in the height direction of the coordinates between the last position point and the first position point in each track segment as the height difference.

[0067] The change in height direction reflects the steepness of the track. The greater the change in height direction, the greater the height difference, the steeper the track, and the greater the impact on the running speed.

[0068] Step S203: Obtain the mean curvature of all position points in each track segment, and perform negative correlation mapping to obtain the mean curvature radius of each track segment.

[0069] It should be noted that, in one embodiment of the present invention, the curvature reflects the degree of bending of the curve at a certain position point, and the method for obtaining it is to perform the second-order derivative of the track segment at each position point; taking the inverse of the curvature can reflect the curvature radius of the track segment, and the degree of bending of the track segment is quantified as a whole by taking the average value. The larger the average curvature radius, the smaller the degree of bending.

[0070] Step S204: Obtain the maximum operating adjustment speed of each track segment based on the preset maximum operating speed, tunnel length, height difference, and average curvature radius of each track segment. The preset maximum operating speed and average curvature radius are both positively correlated with the maximum operating adjustment speed, while the tunnel length and height difference are both negatively correlated with the maximum operating adjustment speed.

[0071] It should be noted that, in one embodiment of the present invention, the preset maximum operating speed is the maximum operating speed that the high-speed rail can reach on a track with no curvature at a conventional horizontal height, which can be obtained in advance by the implementation personnel based on relevant professional knowledge; the specific means are technical means well known to those skilled in the art and will not be elaborated here.

[0072] It should be noted that the length of the tunnel reflects the degree to which each part is affected by the tunnel. The longer the tunnel, the greater the impact on the high-speed rail speed, the more it needs to be reduced in speed, and the smaller the maximum operating adjustment speed, which is a negative correlation; the average curvature radius reflects the changes in the track segment. The larger the average curvature radius, the smaller the changes in the track segment, the smaller the curvature, the smaller the impact on the operating speed, and the larger the maximum operating adjustment speed, which is a positive correlation; the height difference reflects the slope of the track segment. The greater the height difference, the steeper the track segment, the greater the impact on the operating speed, the more it needs to be reduced in speed, and the smaller the maximum operating adjustment speed, which is a negative correlation.

[0073] In one embodiment of the present invention, the product of the tunnel length and the height difference of each track segment is obtained, the ratio of the average curvature radius of each track segment and the product result is calculated, and normalized mapping is performed, and the product between the normalized mapping result and the preset ideal maximum operating speed is calculated as the maximum operating adjustment speed; therefore, the correlation between the tunnel length, height difference, average curvature radius, and the preset maximum operating speed and the maximum operating adjustment speed is constructed through basic mathematical operations; that is, the greater the preset maximum operating speed, the greater the average curvature radius, the smaller the height difference, the smaller the tunnel length, and the greater the maximum operating adjustment speed.

[0074] It should be noted that, in the embodiment of the present invention, a linear normalization method or a normalization mapping function may be used for normalization processing, such as Function, the specific means are technical means well known to those skilled in the art and will not be limited or elaborated here.

[0075] As a high-speed train transitions from traction to cruising, its speed gradually increases until the maximum speed remains constant. The speed decreases during coasting and braking, but braking causes energy loss and a rapid drop in speed. Therefore, it is necessary to reduce the speed as much as possible during coasting to minimize energy consumption. The speed distribution is adjusted based on the maximum operating speed of different track segments, selecting track segments that require speed reduction.

[0076] Preferably, in one embodiment of the present invention, the method for obtaining the speed reduction required track segment includes:

[0077] The difference in the maximum operating adjustment speed between the previous track segment and the next track segment is obtained as the speed difference of each track segment. If the speed difference of the track segment is greater than the preset difference threshold, the corresponding track segment is used as the track segment requiring speed reduction.

[0078] It should be noted that, in one embodiment of the present invention, the size of the preset difference threshold is 0. In other embodiments of the present invention, the size of the preset difference threshold is a technical means well known to those skilled in the art and is not limited or elaborated here.

[0079] In one embodiment of the present invention, the difference in maximum operating adjustment speed between each track segment and the next track segment is obtained. The larger the difference, the more the maximum operating adjustment requires to reduce the temperature, and the larger the corresponding track segment.

[0080] Step S3: For any track segment with a speed reduction requirement, randomly generate a location point as the bird's nest location and execute the cuckoo search algorithm; obtain the fitness of each bird's nest location based on the location characteristics of each bird's nest location on the track and the maximum operating adjustment speed between the track segment where it is located and the next track segment; determine whether the bird's nest location should be abandoned based on the fitness of each bird's nest location and the tunnel parameters and location characteristics of different location points in the track segment where it is located; if it is determined to be abandoned, iteratively update the bird's nest location to obtain a new bird's nest location until the maximum number of iterations is reached, and take the bird's nest location corresponding to the maximum fitness value as the optimal idling location point.

[0081] Cruising speed is fast and energy-intensive, while inertia speed is slow and energy-efficient. Reasonable operation planning can reduce train energy consumption while achieving speed reduction and ensuring on-time performance. The impact of the track environment on which the train travels also affects the speed reduction rate during inertia, thus assessing the optimal location for the train to begin inertia. The cuckoo algorithm can efficiently search for the optimal inertia location based on the complex energy-speed relationship of the inertia segment. For any track segment requiring inertia reduction, a randomly generated location point is used as the nesting location, and the cuckoo search algorithm is executed.

[0082] The fitness function is the core bridge connecting the optimization goal and the algorithm search process. For the coasting optimization of high-speed rail track segments, the fitness must comprehensively reflect the local track characteristics and speed adjustment requirements of the bird's nest location. The fitness of each bird's nest location is obtained based on the position characteristics of each bird's nest location on the track and the maximum operating adjustment speed between the track segment where it is located and the next track segment.

[0083] Preferably, in one embodiment of the present invention, the method for obtaining fitness includes:

[0084] The length between each nest location and the last location point in the track segment is taken as the remaining track length of each nest location;

[0085] Obtain the average of the maximum running adjustment speeds between the track segment where each bird's nest is located and the next track segment as the average running speed; calculate the ratio of the remaining track length to the average running speed as the additional time;

[0086] Obtain the preset resistance of the high-speed rail in the cruising state or coasting state, and obtain the product difference of the preset resistance, additional time and average running speed between different states as the coasting energy saving;

[0087] The ratio of energy saved by idling to the extra time spent was obtained as the fitness of each nest location.

[0088] It should be noted that, in the embodiment of the present invention, the magnitude of the preset resistance can be obtained in advance by the implementer based on relevant experience, and is not limited or elaborated herein.

[0089] In order to avoid falling into the local optimal solution, some bird nest locations need to be randomly discarded. In order to reduce the possibility of discarding bird nests with higher fitness, the fitness of each bird nest location and the tunnel parameters and location characteristics of different locations in the corresponding neighborhood are used to determine whether the bird nest location should be discarded.

[0090] Preferably, in one embodiment of the present invention, determining whether the bird's nest location is abandoned includes:

[0091] The environmental impact of each bird's nest location is obtained based on the tunnel parameters and location characteristics of different points in the neighborhood corresponding to each bird's nest location.

[0092] It should be noted that, in one embodiment of the present invention, the neighborhood range is based on each bird's nest position and is composed of other position points after the bird's nest position on the track segment. In other embodiments of the present invention, the neighborhood range can be set according to specific circumstances and is not limited or elaborated here.

[0093] Preferably, in one embodiment of the present invention, the method for obtaining the degree of environmental impact includes:

[0094] For each nest location in the corresponding neighborhood, the product of tunnel length and height difference is obtained as the first impact degree;

[0095] The ratio of the average curvature radius to the first impact degree is obtained and normalized and mapped as the environmental impact degree within the corresponding neighborhood.

[0096] It should be noted that the calculation method for tunnel length, height difference and average curvature radius within the neighborhood range is consistent with the calculation method for track segments, that is, the range corresponding to the track segment is replaced by the neighborhood range for calculation.

[0097] Obtain the ratio of the fitness of each nest location to the degree of environmental impact, and normalize it as the retention probability of each nest location;

[0098] If the probability of retaining a bird's nest location is less than the preset retention probability, it is determined that the bird's nest location needs to be discarded.

[0099] It should be noted that, in one embodiment of the present invention, the method for obtaining the preset retention probability is to randomly generate a random number at each iteration based on the cuckoo search algorithm as the preset retention probability. The specific method is well known to those skilled in the art and will not be described in detail here.

[0100] If it is determined to be discarded, the nest position is iteratively updated to obtain a new nest position until the maximum number of iterations is reached, and the nest position corresponding to the maximum fitness value is taken as the optimal idling position point.

[0101] It should be noted that, in the cuckoo algorithm, the number of randomly generated position points and the maximum number of iterations can be set according to the specific situation. In the cuckoo search algorithm, Levy flight is used to update the position, so that the intelligent algorithm can fully search the solution space during iteration, thereby enhancing the global search capability of the algorithm and making it easier for the algorithm to find the global optimal solution. The specific cuckoo algorithm and Levy flight are technical means well known to those skilled in the art and will not be elaborated here.

[0102] Step S4: operating the high-speed rail according to the optimal coasting position point of each track segment requiring deceleration.

[0103] Based on the obtained optimal coasting position point, a reasonable operation strategy arrangement can be made for the high-speed rail, the coasting state transition of the track section can be carried out in time, and the state transition of the high-speed rail between cruising and coasting can be distributed to avoid the subsequent braking speed reduction rate being too fast and consuming a lot of energy, so as to achieve the goal of keeping the overall energy consumption as low as possible while ensuring timeliness and safety, and improve the energy saving and efficiency of the operation strategy.

[0104] In summary, the present invention screens out track segments that require speed reduction; for any track segment that requires speed reduction, randomly generates a position point as the bird's nest position, and executes the cuckoo search algorithm; obtains the fitness of each bird's nest position based on the position characteristics of each bird's nest position on the track, and the maximum operating adjustment speed of the track segment where it is located and the next track segment; determines whether the bird's nest position should be discarded in combination with the tunnel parameters and position characteristics of different position points within the neighborhood; if it is determined to be discarded, it iteratively updates the bird's nest position to obtain a new bird's nest position until the maximum number of iterations is reached, and uses the bird's nest position corresponding to the maximum fitness value as the optimal idling position point; and operates the high-speed rail. The present invention improves the effectiveness of operational decisions and optimizes the effects of virtual experiments by obtaining accurate fitness and discarding methods when the algorithm is in progress.

[0105] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0106] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A high-speed rail infrastructure virtual test system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: Obtain the simulated track running curve of the high-speed train, and obtain the position coordinates of each position point on the running curve relative to the track starting point and the tunnel parameters; Obtain multiple track segments based on tunnel parameters, height distribution, and curve change trends at different points on the operating curve; Based on the tunnel parameters, location characteristics, and preset maximum operating speed of different points in each track segment, the maximum operating adjustment speed of each track segment is obtained; based on the distribution of the maximum operating adjustment speeds of different track segments, the track segments requiring speed reduction are screened out; For any track segment requiring speed reduction, randomly generate a location point as the bird's nest location and execute the cuckoo search algorithm. The fitness of each bird's nest location is obtained based on its location characteristics on the track and the maximum operating adjustment speed between the track segment and the next track segment. Based on the fitness of each bird's nest location and the tunnel parameters and location characteristics of different locations within the corresponding neighborhood, determine whether the bird's nest location should be discarded. If it is discarded, it is iteratively updated to obtain a new bird's nest location until the maximum number of iterations is reached. The bird's nest location corresponding to the maximum fitness value is then determined as the optimal coasting location point. The high-speed train is operated according to the optimal coasting position point of each track section requiring speed reduction; The method for obtaining the fitness includes: The length between each nest location and the last location point in the track segment is taken as the remaining track length of each nest location; Obtain the average of the maximum running adjustment speeds between the track segment where each bird's nest is located and the next track segment as the average running speed; calculate the ratio of the remaining track length to the average running speed as the additional time; Obtain the preset resistance of the high-speed rail in the cruising state or coasting state, and obtain the product difference of the preset resistance, additional time and average running speed between different states as the coasting energy saving; The ratio of energy saved by idling to the extra time spent was obtained as the fitness of each nest location.

2. A high-speed rail infrastructure virtual test system according to claim 1, characterized in that: The method for obtaining the track segmentation includes: According to the tunnel parameters, height distribution and curve change trend of different points on the running curve, the track consistency between adjacent points is obtained; If the track consistency between adjacent position points is greater than or equal to a preset consistency threshold, the corresponding position points are taken as consistent position points; continuous consistent position points are selected to form a track segment, and multiple continuous track segments are obtained.

3. A high-speed rail infrastructure virtual test system according to claim 2, characterized in that: The method for obtaining the track consistency includes: Obtaining an exclusive OR value of the tunnel parameters between each position point and the adjacent previous position point; obtaining a first sign value of the difference in the height direction between the coordinates of each position point and the adjacent previous position point, and obtaining a second sign value of the difference in the height direction between the coordinates of each position point and the starting point; The curvature of each position point on the running curve is obtained and normalized as the curvature consistency; the track consistency between the corresponding adjacent position points is obtained according to the XOR value, the mean absolute value of the first symbol value and the second symbol value, and the curvature consistency between each position point and the adjacent previous position point. The XOR value is negatively correlated with the track consistency, and the mean absolute value of the first symbol value and the second symbol value and the curvature consistency are both positively correlated with the track consistency.

4. A high-speed rail infrastructure virtual test system according to claim 1, characterized in that: The method for obtaining the maximum operating adjustment speed includes: The number of locations where the tunnel parameters are non-zero in each track segment is obtained as the tunnel length. If all tunnel parameters are zero, the tunnel length is set to 1. Obtaining the difference in the height direction between the coordinates of the last position point and the first position point in each track segment as the height difference; Obtain the mean curvature of all position points in each track segment and perform negative correlation mapping as the average curvature radius of each track segment; The maximum operating adjustment speed of each track segment is obtained based on the preset maximum operating speed, tunnel length, height difference and average curvature radius of each track segment. The preset maximum operating speed and average curvature radius are positively correlated with the maximum operating adjustment speed, while the tunnel length and height difference are negatively correlated with the maximum operating adjustment speed.

5. The high-speed rail infrastructure virtual test system according to claim 1, characterized in that: The method for obtaining the track segmentation includes: The difference in the maximum operating adjustment speed between the previous track segment and the next track segment is obtained as the speed difference of each track segment. If the speed difference of the track segment is greater than the preset difference threshold, the corresponding track segment is used as the track segment requiring speed reduction.

6. A high-speed rail infrastructure virtual test system according to claim 4, characterized in that: The step of determining whether the bird's nest location is abandoned includes: The environmental impact of each bird's nest location is obtained based on the tunnel parameters and location characteristics of different locations in the track segment where each bird's nest location is located; Obtain the ratio of the fitness of each nest location to the degree of environmental impact, and normalize it as the retention probability of each nest location; If the probability of retaining a bird's nest location is less than the preset retention probability, it is determined that the bird's nest location needs to be discarded.

7. A high-speed rail infrastructure virtual test system according to claim 6, characterized in that: The method for obtaining the degree of environmental impact includes: The product of the tunnel length and the height difference of each track segment is obtained as the first impact degree; The ratio of the average curvature radius of each track segment to the first impact degree is obtained and normalized and mapped as the environmental impact degree of each track segment.

8. The high-speed rail infrastructure virtual test system according to claim 1, characterized in that: The method for obtaining the neighborhood range includes: Taking each bird's nest location as the benchmark, the range formed by other location points after the bird's nest location on the track segment is used as the neighborhood range of each bird's nest location.

9. A high-speed rail infrastructure virtual test system according to claim 6, characterized in that: The method for obtaining the preset retention probability includes: Based on the cuckoo search algorithm, a random number is randomly generated at each iteration as the preset retention probability.

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