Novel high-speed rail infrastructure virtual test system

Abstract

The invention relates to the technical field of high-speed rail virtual tests, in particular to a novel high-speed rail infrastructure virtual test system. The method comprises the following steps: screening out speed reduction demand track sections; for any speed reduction demand track segment, randomly generating a position point as a bird nest position, and executing a cuckoo search algorithm; the fitness of each nest position is obtained according to the position feature of each nest position on the track and the maximum operation adjusting speed of the track segment where the nest position is located and the next track segment; judging whether the bird nest position is abandoned or not by combining tunnel parameters and position features of different position points in a neighborhood range; if it is judged that the bird nest position is abandoned, iteratively updating the bird nest position to obtain a new bird nest position until the maximum number of iterations is reached, and taking the bird nest position corresponding to the maximum fitness value as an optimal coasting position point; and the high-speed rail is operated. According to the method, by obtaining the accurate fitness and the abandoning mode when the algorithm is carried out, the effectiveness of the operation decision is improved, and the effect of the virtual test is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of high-speed rail virtual test technology, and particularly relates to a new virtual test system for high-speed rail infrastructure. Background Art

[0002] In order to reduce the operation and maintenance costs of high-speed rail infrastructure, numerical simulation methods are often used for virtual experiments to reduce the losses of physical experiments. During the operation of high-speed rail, the cruising state has a high speed but high energy consumption, while the inert state has a low speed but low energy consumption. In order to reduce energy consumption and ensure the failure of high-speed rail, a reasonable high-speed rail operation strategy needs to be planned.

[0003] In the prior art, the cuckoo search algorithm is used to obtain the overall operation strategy of high-speed rail by continuously iterating, eliminating, and updating strategies; however, the operating environment of high-speed rail is changing, and the overall solution may not be applicable to the local operating environment; moreover, although the completely random discarding method of the cuckoo algorithm can jump out of the local optimal solution, there is also a possibility of losing the solution applicable to this environment, affecting the superiority of the final strategy, and the accuracy of virtual experiments is relatively poor. Summary of the Invention

[0004] In order to solve the technical problems of the overall strategy of the traditional cuckoo search algorithm and the random discarding method, with relatively poor accuracy of virtual experiments, the purpose of the present invention is to provide a new virtual test system for high-speed rail infrastructure, and the specific technical solution adopted is as follows: The present invention proposes a new virtual test system for high-speed rail infrastructure, including 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: Obtain the simulated track operation curve of the high-speed rail train, and obtain the position coordinates of each position point on the operation curve relative to the starting point of the track and the tunnel parameters; According to the tunnel parameters, height distribution, and curve change trend of different position points on the operation curve, obtain multiple track segments; according to the tunnel parameters, position characteristics, and preset maximum operating speed of different position points in each track segment, obtain the maximum operating adjustment speed of each track segment; according to the distribution of the maximum operating adjustment speeds of different track segments, screen out the track segments with speed reduction requirements; For any deceleration-demand track segment, randomly generate position points as the nest positions, and execute the cuckoo search algorithm; according to the position characteristics of each nest position on the track and the maximum operating adjustment speed between the current track segment and the next track segment, obtain the fitness of each nest position; according to the fitness of each nest position and the tunnel parameters and position characteristics of different position points within the corresponding neighborhood range, determine whether the nest position should be discarded; if it is determined to be discarded, iteratively update the nest position to obtain a new nest position until the maximum number of iterations is reached, and take the nest position corresponding to the maximum fitness as the optimal coasting position point; Operate the high-speed rail according to the optimal coasting position point of each deceleration-demand track segment.

[0005] Further, the method for obtaining the track segment includes: According to the tunnel parameters, height distribution, and curve change trend of different position points on the operation curve, obtain the track consistency between adjacent position points; If the track consistency between adjacent position points is greater than or equal to the preset consistency threshold, take the corresponding position points as consistency position points; select consecutive consistency position points to form a track segment, and obtain multiple consecutive track segments.

[0006] Further, the method for obtaining the track consistency includes: Obtain the exclusive OR value of the tunnel parameters between each position point and the previous adjacent position point; obtain the first sign value of the difference in coordinates in the height direction between each position point and the previous adjacent position point, and obtain the second sign value of the difference in coordinates in the height direction between each position point and the starting point; Obtain the curvature of each position point on the operation curve and normalize it as the curvature consistency; according to the mean absolute value of the exclusive OR value, the first sign value, and the second sign value between each position point and the previous adjacent position point, as well as the curvature consistency, obtain the track consistency between the corresponding adjacent position points. The exclusive OR value is negatively correlated with the track consistency, and the mean absolute value of the first sign value and the second sign value, as well as the curvature consistency, are positively correlated with the track consistency.

[0007] Further, the method for obtaining the maximum operating adjustment speed includes: Obtain the number of position points with non-zero tunnel parameters in each track segment as the tunnel length. If the tunnel parameters are all zero, the tunnel length is set to 1; Obtain the difference in coordinates in the height direction between 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 a negative correlation mapping as the average curvature radius of each track segment; Based on the preset maximum operating speed, tunnel length, height difference, and average curvature radius of each track segment, the maximum operating adjustment speed of each track segment is obtained. Both the preset maximum operating speed and the average curvature radius are positively correlated with the maximum operating adjustment speed, while both the tunnel length and the height difference are negatively correlated with the maximum operating adjustment speed.

[0008] Furthermore, the method for obtaining the track segment includes: Obtain the difference in the maximum operating adjustment speed between the previous track segment and the next track segment as the speed difference of each track segment. If the speed difference of the track means is greater than the preset difference threshold, the corresponding track segment is taken as the speed reduction required track segment.

[0009] Furthermore, the method for obtaining the fitness includes: Take the length between each bird's nest position and the last position point in the track segment as the remaining track length of each bird's nest position; Obtain the average value of the maximum operating adjustment speed between the track segment where each bird's nest position is located and the next track segment as the average operating speed; calculate the ratio of the remaining track length to the average operating speed as the additional time spent; Obtain the preset resistance in the cruise state or the coasting state during the operation of the high-speed rail, and obtain the product difference of the preset resistance, additional time spent, and average operating speed between different states as the energy saved by coasting; Obtain the ratio of the energy saved by coasting to the additional time spent as the fitness of each bird's nest position.

[0010] Furthermore, the determination of whether to discard the bird's nest position includes: Based on the tunnel parameters and position characteristics of different position points in the track segment where each bird's nest position is located, obtain the environmental impact degree of each bird's nest position; Obtain the ratio of the fitness of each bird's nest position to the environmental impact degree and perform normalization as the retention probability of each bird's nest position; If there is a retention probability of a bird's nest position less than the preset retention probability, it is determined that the bird's nest position needs to be discarded.

[0011] Furthermore, the method for obtaining the environmental impact degree includes: Obtain the product of the tunnel length and the height difference of each track segment as the first impact degree; Obtain the ratio of the average curvature radius of each track segment to the first impact degree and perform a normalized mapping as the environmental impact degree of each track segment.

[0012] Furthermore, the method for obtaining the neighborhood range includes: Taking each bird's nest position as a reference, the range formed by other position points after the bird's nest position on the segmented track where it is located is used as the neighborhood range of each bird's nest position.

[0013] Further, the method for obtaining the preset retention probability includes: Based on the cuckoo search algorithm, a random number is randomly generated during each iteration as the preset retention probability.

[0014] The present invention has the following beneficial effects: The present invention obtains multiple track segments according to the tunnel parameters, height distribution, and curve change trend of different position points on the operation curve, and analyzes the characteristics of different track segments more carefully based on the influence of different factors; according to the tunnel parameters, position characteristics, and preset maximum operating speed of different position points in each track segment, the track segments with deceleration requirements are screened out, and only the track segments with deceleration requirements are focused on and processed, avoiding unnecessary deceleration operations; for any track segment with deceleration requirements, a position point is randomly generated as the bird's nest position, and the cuckoo search algorithm is executed. By executing this algorithm, the best coasting position point can be efficiently searched within the track segment with deceleration requirements, 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 pros and cons of each bird's nest position as a coasting position point are quantitatively evaluated; according to the fitness of each bird's nest position and the tunnel parameters and position characteristics of different position points within the corresponding neighborhood range, it is determined whether the bird's nest position is discarded; if it is determined to be discarded, 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 coasting position point. Through continuous iterative update, 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 decision-making and optimizes the effect of virtual experiments by obtaining accurate fitness and discard methods during the algorithm operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of an implementation method of a new type of high-speed rail infrastructure virtual test system provided by an embodiment of the present invention; Figure 2Flowchart of a method for obtaining the maximum operating adjustment speed provided by an embodiment of the present invention. Detailed implementation manners

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following combines the accompanying drawings and preferred embodiments to elaborate in detail on a novel high-speed rail infrastructure virtual test system proposed according to the present invention, its specific implementation manners, structures, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0019] The following specifically describes the specific solution of a novel high-speed rail infrastructure virtual test system provided by the present invention with reference to the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of an implementation method of a novel high-speed rail infrastructure virtual test system provided by an embodiment of the present invention. The method specifically includes: Step S1: Obtain the simulated track running curve of the high-speed rail train, and obtain the position coordinates of each position point on the running curve relative to the track starting point and the tunnel parameters.

[0021] In the embodiment of the present invention, in order to retain as many excellent strategies that conform to the environmental characteristics as possible without being eliminated, and to reduce the overall energy consumption as much as possible while ensuring timeliness, it is necessary to simulate the environmental model of the high-speed rail train and allocate the state conversion between cruising and coasting of the high-speed rail. First, regard the entire high-speed rail train as a particle, use a single-particle model to model the high-speed rail track, use a scanner to collect the data of the railway basic model, perform physical modeling, rendering, and optimization on the track route, and obtain the virtual simulation experiment scenario of the train and the track route. Take the track starting point as the origin of the coordinate system, the horizontal plane as the plane, and the height as the Z-axis to form a three-dimensional space coordinate system, fit the track, obtain the simulated track running curve of the high-speed rail train. The high-speed rail train can be roughly divided into four running states during the running process, namely the traction state, the cruising state, the coasting state, and the braking state, and obtain the position coordinates of each position point on the running curve relative to the track starting point and the tunnel parameters; It should be noted that the tunnel parameters can be set in advance according to the actual situation. When the position point on the running curve is inside the tunnel, the tunnel parameter is set to 1, and when it is not inside the tunnel, the tunnel parameter is set to 0.

[0022] Step S2: Obtain multiple track segments according to the tunnel parameters, height distribution, and curve change trend at different position points on the operation curve; obtain the maximum operating adjustment speed for each track segment according to the tunnel parameters, position characteristics, and preset maximum operating speed at each position point in each track segment; screen out the track segments with speed reduction requirements according to the distribution of the maximum operating adjustment speeds of different track segments.

[0023] During the operation of high-speed trains, there will be track paths in various environments such as tunnels, curves, and slopes, which have different impacts on high-speed trains. In order to optimize the operation efficiency of high-speed trains, the track is segmented according to environmental characteristics; multiple track segments are obtained according to the tunnel parameters, height distribution, and curve change trend at different position points on the operation curve.

[0024] Preferably, in an embodiment of the present invention, the method for obtaining track segments includes: Obtain the track consistency between adjacent position points according to the tunnel parameters, height distribution, and curve change trend at different position points on the operation curve; Preferably, in an embodiment of the present invention, the method for obtaining track consistency includes: Obtain the exclusive OR value of the tunnel parameters between each position point and the adjacent previous position point; obtain the first sign value of the difference in coordinates in the height direction between each position point and the adjacent previous position point, and obtain the second sign value of the difference in coordinates in the height direction between each position point and the starting point; Normalize the curvature of each position point on the operation curve as the curvature consistency; obtain the track consistency between the corresponding adjacent position points according to the mean absolute value of the exclusive OR value, the first sign value, and the second sign value between each position point and the adjacent previous position point and the curvature consistency. The exclusive OR value is negatively correlated with the track consistency, and the mean absolute value of the first sign value and the second sign value and the curvature consistency are all positively correlated with the track consistency.

[0025] It should be noted that the exclusive OR 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 exclusive OR value, the greater the track consistency, showing a negative correlation; based on the sign function Obtain the sign value of the height difference, which reflects the change in slope. When the difference is negative, the sign value is -1, and the lower the slope. When the difference is positive, the sign value is 1, and the higher the slope. That is, the more consistent the sign values, the more consistent the mean absolute values of the first sign value and the second sign value, the more consistent the slope, and the greater the track consistency, showing a positive correlation; the curvature consistency reflects the degree of consistency of the track curve. The smaller the curvature, the smaller the curvature consistency, and the smaller the track consistency, showing a positive correlation.

[0026] In an embodiment of the present invention, the difference between the positive integer 1 and the exclusive OR value is obtained as the tunnel consistency; the mean 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. Therefore, the correlation relationship between the exclusive OR value, the first symbol value, the second symbol value, the curvature consistency, and the track consistency is constructed through the above basic mathematical operations, that is, the smaller the exclusive OR value, the larger the first symbol value, the larger the second symbol value, the larger the curvature consistency, and the larger the track consistency.

[0027] 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.

[0028] It should be noted that, in an 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 specifically set according to specific situations, and no limitation and elaboration are made here.

[0029] Different environmental characteristics have different degrees of influence on the maximum operating speed of high-speed trains. Therefore, by analyzing the environmental characteristics of each track segment, the maximum operating speed is adjusted to an appropriate value; that is, according to the tunnel parameters, position characteristics, and preset maximum operating speed of each position point in each track segment, the maximum operating adjustment speed of each track segment is obtained.

[0030] Preferably, in an embodiment of the present invention, for the method of obtaining the maximum operating adjustment speed, please refer to Figure 2 , which shows a flowchart of a method for obtaining the maximum operating adjustment speed, including: Step S201: The number of position points with non-zero tunnel parameters in each track segment is obtained as the tunnel length. If all tunnel parameters are zero, the tunnel length is set to 1.

[0031] The more position points with non-zero tunnel parameters, the longer the tunnel is, and the greater the impact on the operating speed.

[0032] Step S202: The difference in coordinates in the height direction between the last position point and the first position point in each track segment is obtained as the height difference.

[0033] The change situation in the height direction reflects the steepness of the track. The greater the change situation in the height direction, the greater the height difference, the steeper the track, and the greater the impact on the operating speed.

[0034] Step S203: The mean curvature of all position points in each track segment is obtained and subjected to a negative correlation mapping as the average curvature radius of each track segment.

[0035] It should be noted that in an embodiment of the present invention, curvature reflects the degree of bending of a curve at a certain position point, and the acquisition method is to perform a second-order derivative on each position point of the track segment; taking the reciprocal of the curvature can reflect the radius of curvature of the track segment, and the average curvature radius is obtained by taking the mean to quantify the bending degree of the track segment as a whole. The larger the average radius of curvature, the smaller the bending degree.

[0036] Step S204: According to the preset maximum operating speed, tunnel length, height difference, and average radius of curvature of each track segment, obtain the maximum operating adjustment speed of each track segment. Both the preset maximum operating speed and the average radius of curvature are positively correlated with the maximum operating adjustment speed, while both the tunnel length and the height difference are negatively correlated with the maximum operating adjustment speed.

[0037] It should be noted that in an embodiment of the present invention, the preset maximum operating speed is the maximum operating speed that a high-speed train can reach on a track with a regular horizontal height and no curvature, which can be pre-obtained by the implementer according to relevant professional knowledge; the specific means are well-known technical means to those skilled in the art and will not be elaborated here.

[0038] It should be noted that the tunnel length reflects the degree to which each is affected by the tunnel. The longer the tunnel, the greater the impact on the speed of the high-speed train, and the more necessary it is to reduce the speed. The maximum operating adjustment speed is smaller, showing a negative correlation; the average radius of curvature reflects the change of the track segment. The larger the average radius of curvature, the smaller the change of the track segment, the smaller the bending degree, and the smaller the impact on the operating speed. The maximum operating adjustment speed is larger, showing a positive correlation; the height difference reflects the slope of the track segment. The larger the height difference, the steeper the track segment, the greater the impact on the operating speed, and the more necessary it is to perform a speed reduction process. The maximum operating adjustment speed is smaller, showing a negative correlation.

[0039] In an embodiment of the present invention, obtain the product of the tunnel length and the height difference of each track segment, calculate the ratio of the average radius of curvature of each track segment to the product result, and perform a normalization mapping. Calculate the product between the normalization mapping result and the preset ideal maximum operating speed as the maximum operating adjustment speed; therefore, a correlation relationship between the tunnel length, height difference, average radius of curvature, preset maximum operating speed, and maximum operating adjustment speed is constructed through basic mathematical operations; that is, the larger the preset maximum operating speed, the larger the average radius of curvature, the smaller the height difference, the smaller the tunnel length, and the larger the maximum operating adjustment speed.

[0040] It should be noted that in the embodiments of the present invention, a linear normalization method or a normalization mapping function can be used for normalization processing, such as function. The specific means are well-known technical means to those skilled in the art and will not be limited or elaborated here.

[0041] During the process of a high-speed train transitioning from the traction state to the cruising state, the speed gradually increases until it reaches the maximum speed and remains constant. During the coasting and braking states, the speed will decrease. However, the braking state causes energy loss and a rapid decrease in speed. Therefore, it is necessary to reduce the speed as much as possible during the coasting state to reduce the energy consumption of the train. According to the maximum operating adjustment speed distribution of different track segments, the track segments with speed reduction requirements are screened out.

[0042] Preferably, in an embodiment of the present invention, the method for obtaining the track segments with speed reduction requirements includes: Obtain the difference in the maximum operating adjustment speed between the previous track segment and the next track segment as the speed difference for each track segment. If the speed difference of the track segment is greater than the preset difference threshold, the corresponding track segment is regarded as the track segment with speed reduction requirements.

[0043] It should be noted that, in an 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 will not be limited and elaborated herein.

[0044] In an embodiment of the present invention, obtain the difference in the maximum operating adjustment speed between each track segment and the next track segment. The larger the difference, the more the maximum operating adjustment needs to reduce the temperature, and the greater the corresponding track segment.

[0045] Step S3: For any track segment with speed reduction requirements, randomly generate a position point as the cuckoo nest position and execute the cuckoo search algorithm; obtain the fitness of each cuckoo nest position according to the position characteristics of each cuckoo nest position on the track and the maximum operating adjustment speed between the track segment where it is located and the next track segment; judge whether to discard the cuckoo nest position according to the fitness of each cuckoo nest position and the tunnel parameters and position characteristics of different position points in the track segment where it is located; if it is judged to be discarded, iteratively update the cuckoo nest position to obtain a new cuckoo nest position until the maximum number of iterations is reached, and take the cuckoo nest position corresponding to the maximum fitness as the optimal coasting position point.

[0046] The cruising speed is fast and the energy consumption is high, while the coasting speed is slow and the energy consumption is low. A reasonable operation plan can reduce the energy consumption of the train on the premise of achieving the speed reduction goal and the punctuality of the train. The environment where the train travels on the track will also affect the speed reduction rate during the coasting state, and evaluate the best position point for the train to start coasting; the cuckoo algorithm can reduce the complex energy consumption-speed relationship of the speed reduction segment and efficiently search for the optimal coasting position point. For any track segment with speed reduction requirements, randomly generate a position point as the cuckoo nest position and execute the cuckoo search algorithm.

[0047] The fitness function is the core bridge connecting the optimization objective and the algorithm search process. For the coasting optimization of high-speed rail track segments, the fitness needs to comprehensively reflect the local track characteristics at the location of each bird's nest and the speed adjustment requirements. According to the location characteristics of each bird's nest position on the track and the maximum operating adjustment speed between the current track segment and the next track segment, the fitness of each bird's nest position is obtained.

[0048] Preferably, in an embodiment of the present invention, the method for obtaining the fitness includes: Take the length between each bird's nest position and the last position point in the track segment as the remaining track length of each bird's nest position; Obtain the average value of the maximum operating adjustment speed between the track segment where each bird's nest position is located and the next track segment as the average operating speed; calculate the ratio of the remaining track length to the average operating speed as the additional time spent; Obtain the preset resistance in the cruise state or coasting state during high-speed rail operation, and obtain the product difference of the preset resistance, additional time spent, and average operating speed between different states as the energy saved by coasting; Obtain the ratio of the energy saved by coasting to the additional time spent as the fitness of each bird's nest position.

[0049] It should be noted that in the embodiment of the present invention, the magnitude of the preset resistance can be pre-obtained by the implementer according to relevant experience, and no limitation and elaboration are made here.

[0050] To avoid falling into a local optimal solution, some bird's nest positions need to be randomly discarded. To reduce the possibility of discarding bird's nest positions with higher fitness, it is determined whether to discard a bird's nest position according to the fitness of each bird's nest position and the tunnel parameters and location characteristics of different position points within the corresponding neighborhood range.

[0051] Preferably, in an embodiment of the present invention, determining whether to discard a bird's nest position includes: Obtain the degree of environmental impact of each bird's nest position according to the tunnel parameters and location characteristics of different position points within the corresponding neighborhood range of each bird's nest position; It should be noted that in an embodiment of the present invention, the neighborhood range is the range formed by each bird's nest position and other position points after the bird's nest position on the track segment where it is located. In other embodiments of the present invention, the neighborhood range can be specifically set according to specific circumstances, and no limitation and elaboration are made here.

[0052] Preferably, in an embodiment of the present invention, the method for obtaining the degree of environmental impact includes: For each neighborhood range corresponding to a bird's nest position, obtain the product of the tunnel length and height difference as the first degree of impact; Obtain the ratio of the average curvature radius to the first influence degree, and perform normalization mapping as the environmental influence degree within the corresponding neighborhood range.

[0053] It should be noted that the calculation methods of the tunnel length, height difference, and average curvature radius within the neighborhood range are the same as those of the track segmentation, that is, the corresponding range of the track segmentation is replaced with the neighborhood range for calculation.

[0054] Obtain the ratio of the fitness of each bird's nest position to the environmental influence degree, and perform normalization as the retention probability of each bird's nest position; If the retention probability of a bird's nest position is less than the preset retention probability, it is determined that the bird's nest position needs to be discarded.

[0055] It should be noted that in an embodiment of the present invention, the method for obtaining the preset retention probability is: randomly generate a random number during each iteration based on the cuckoo search algorithm as the preset retention probability. The specific means are well-known technical means to those skilled in the art and will not be elaborated here.

[0056] If it is determined to discard, iterate and update the bird's nest position to obtain a new bird's nest position until the maximum number of iterations is reached, and take the bird's nest position corresponding to the maximum fitness value as the optimal coasting position point.

[0057] 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 specific situations. In the cuckoo search algorithm, Levy flight is used for position update, enabling the intelligent algorithm to fully search the solution space during iteration, enhancing the global search ability of the algorithm, and making it easier for the algorithm to find the global optimal solution. The specific cuckoo algorithm and Levy flight are well-known technical means to those skilled in the art and will not be elaborated here.

[0058] Step S4: Operate the high-speed rail according to the optimal coasting position points of each deceleration requirement track segment.

[0059] Based on the obtained optimal coasting position points, a reasonable operation strategy can be arranged for the high-speed rail, and the coasting state conversion of the track segment can be carried out in a timely manner, and the state conversion between cruising and coasting of the high-speed rail can be allocated, avoiding excessive energy consumption due to too fast a reduction rate of the braking speed subsequently, so as to achieve the purpose of minimizing the overall energy consumption as much as possible while ensuring timeliness and safety, and improving the energy-saving and efficiency of the operation strategy.

[0060] In summary, the present invention screens out the track segments with deceleration requirements; for any track segment with deceleration requirements, randomly generate position points as the nest positions, and execute the cuckoo search algorithm; according to the position characteristics of each nest position on the track and the maximum operating adjustment speed of the track segment where it is located and the next track segment, obtain the fitness of each nest position; combine the tunnel parameters and position characteristics of different position points within the neighborhood range to determine whether the nest position is discarded; if it is determined to be discarded, iterate and update the nest position to obtain a new nest position until the maximum number of iterations is reached, and use the nest position corresponding to the maximum fitness value as the optimal coasting position point; and operate the high-speed rail. The present invention improves the effectiveness of operation decision-making and optimizes the effect of virtual tests by obtaining accurate fitness and discarding methods during the algorithm operation.

[0061] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0062] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A new virtual test system for high - speed rail infrastructure, 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 starting point of the track and the tunnel parameters; Obtain multiple track segments according to the tunnel parameters, height distribution and curve change trend of different position points on the running curve; Obtain the maximum running adjustment speed of each track segment according to the tunnel parameters, position characteristics and preset maximum running speed of different position points in each track segment; screen out the track segments with speed reduction requirements according to the distribution of the maximum running adjustment speeds of different track segments; For any track segment with a speed reduction requirement, randomly generate a position point as the cuckoo nest position and execute the cuckoo search algorithm; obtain the fitness of each cuckoo nest position according to the position characteristics of each cuckoo nest position on the track and the maximum running adjustment speeds of the track segment where it is located and the next track segment; judge whether the cuckoo nest position is discarded according to the fitness of each cuckoo nest position and the tunnel parameters and position characteristics of different position points within the corresponding neighborhood range; if it is judged to be discarded, iterate and update the cuckoo nest position to obtain a new cuckoo nest position until the maximum number of iterations is reached, and use the cuckoo nest position corresponding to the maximum fitness as the best coasting position point; Run the high-speed train according to the best coasting position point of each track segment with a speed reduction requirement.

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

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

4. A novel virtual test system for high - speed rail infrastructure according to claim 1, characterized in that, The method for obtaining the maximum running adjustment speed includes: Obtain the number of position points with non-zero tunnel parameters in each track segment as the tunnel length. If the tunnel parameters are all zero, the tunnel length is set to 1; Obtain 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; Obtain the mean curvature of all position points in each track segment and perform a negative correlation mapping to obtain the average curvature radius of each track segment; According to the preset maximum operating speed, tunnel length, height difference, and average curvature radius of each track segment, the maximum operating adjustment speed of each track segment is obtained. The preset maximum operating speed and the average curvature radius are both positively correlated with the maximum operating adjustment speed, while the tunnel length and the height difference are both negatively correlated with the maximum operating adjustment speed.

5. A novel virtual test system for high - speed rail infrastructure according to claim 1, characterized in that, The method for obtaining the track segment includes: Obtain the difference in the maximum operating adjustment speed between the previous track segment and the next track segment 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 taken as the speed reduction required track segment.

6. A novel virtual test system for high-speed rail infrastructure according to claim 1, characterized in that, The method for obtaining the fitness includes: Take the length between each bird's nest position and the last position point in the track segment as the remaining track length of each bird's nest position; Obtain the average value of the maximum operating adjustment speed between the track segment where each bird's nest position is located and the next track segment as the average operating speed; calculate the ratio of the remaining track length to the average operating speed as the additional time spent; Obtain the preset resistance in the cruise state or the coasting state during high-speed rail operation, and obtain the product difference of the preset resistance, additional time spent, and average operating speed between different states as the energy saved by coasting; Obtain the ratio of the energy saved by coasting to the additional time spent as the fitness of each bird's nest position.

7. A novel virtual test system for high - speed rail infrastructure according to claim 4, characterized in that, The judgment of whether to discard the bird's nest position includes: According to the tunnel parameters and position characteristics of different position points in the track segment where each bird's nest position is located, obtain the environmental impact degree of each bird's nest position; Obtain the ratio of the fitness and the environmental impact degree of each bird's nest position and perform normalization as the retention probability of each bird's nest position; If there is a retention probability of a bird's nest position less than the preset retention probability, it is judged that the bird's nest position needs to be discarded.

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

9. A novel virtual test system for high - speed rail infrastructure according to claim 1, characterized in that, The method for obtaining the neighborhood range includes: Taking each bird's nest position as a reference, the range formed by other position points after the bird's nest position on the track segment where it is located is used as the neighborhood range of each bird's nest position.

10. A novel virtual test system for high-speed rail infrastructure according to claim 7, characterized in that, The method for obtaining the preset retention probability includes: Based on the cuckoo search algorithm, a random number is randomly generated during each iteration as the preset retention probability.

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