A train dynamic sealing index calculation method, system and storage medium

Abstract

The present application relates to the technical field of train dynamic sealing index calculation, and particularly relates to a train dynamic sealing index calculation method, system and storage medium, which adopts a ternary search algorithm to search for an optimal train dynamic sealing index in a predicted dynamic sealing index distribution interval. Thus, the ternary search algorithm with logarithmic order time complexity is used to replace the traversal search method with linear order time complexity in the existing calculation method, so that the time consumption for calculating the train dynamic sealing index is significantly reduced, the efficiency is significantly improved, and the ternary search algorithm with logarithmic order time complexity is used to help the time consumption change insignificantly with the increase of the scale of the search interval, so that high calculation efficiency and high calculation accuracy coexist.

Description

Technical Field

[0001] This invention relates to the field of train dynamic sealing index calculation technology, and in particular to a train dynamic sealing index calculation method, system and storage medium. Background Technology

[0002] The dynamic sealing index of train carriages, as a targeted quantitative indicator for measuring the real-time airtightness of train carriages operating in tunnels, plays a crucial role in in-depth and systematic research on the airtightness performance and passenger comfort of operating trains. Currently, the process of searching for and determining the optimal dynamic sealing index within the estimated dynamic sealing index distribution interval adopts an ergonomic search approach. This involves discretizing the continuous estimated dynamic sealing index distribution intervals at equal intervals based on the expected dynamic sealing index calculation accuracy, and then judging the similarity of the actual dynamic sealing conditions of each estimated dynamic sealing index in the entire discrete interval sequence. Finally, the element with the optimal similarity is determined as the final dynamic sealing index calculation result. This entire calculation process is extremely time-consuming, and the calculation time increases linearly with the increase of the number of discrete elements in the estimated distribution interval, resulting in low computational efficiency. This limits the efficient development of high-precision research on the dynamic sealing index of trains, especially for very long tunnels. It is evident that existing dynamic sealing index calculation methods, based on a time-complex ergonomic search optimization process, suffer from significant problems of time-consuming calculations, low computational efficiency, and a significant discrepancy between computational efficiency and progress. Summary of the Invention

[0003] This invention provides a method, system, and storage medium for calculating the dynamic sealing index of trains, in order to solve the problems of existing dynamic sealing index calculation methods, which are based on a time-complex traversal search optimization process, resulting in serious computational time consumption, low computational efficiency, and significant differences between computational efficiency and computational progress.

[0004] To achieve the above objectives, the present invention employs the following technical solution:

[0005] In a first aspect, the present invention provides a method for calculating the dynamic sealing index of a train, comprising:

[0006] The first and second search points of the current search range are determined based on the set distribution range of the estimated dynamic sealing index value.

[0007] The pressure data sequence inside the first carriage corresponding to the first search point is calculated based on the linear assumption pressure transmission model, and the pressure data sequence inside the second carriage corresponding to the second search point is calculated.

[0008] Calculate a first similarity index between the calculated pressure data sequence inside the first carriage and the measured pressure data sequence inside the carriage, and a second similarity index between the calculated pressure data sequence inside the second carriage and the measured pressure data sequence inside the carriage.

[0009] The search range is updated based on the relationship between the first similarity index and the second similarity index;

[0010] If the current calculation accuracy does not reach the set calculation accuracy, the first and second search points are re-determined based on the updated search interval, and the search is performed again. The current calculation accuracy is determined based on the length of the current search interval. In this calculation process, the current calculation accuracy is measured by the length of the latest search interval. That is, when the length of the latest search interval is less than the designed calculation accuracy, the calculation accuracy is considered to meet the preset accuracy requirements.

[0011] When the current calculation accuracy reaches the required dynamic sealing index calculation accuracy, the final optimal calculation result of the current train car dynamic sealing index is output.

[0012] Optionally, the minimum value of the set estimated dynamic sealing index value distribution range is 0, and the maximum value is 200.

[0013] Optionally, determining the first and second search points of the current search interval based on the set estimated dynamic sealing index value distribution interval includes:

[0014] The current search interval is divided into three segments to obtain the first search point and the second search point. The first search point satisfies the following relationship:

[0015] τ mid =(τ max +τ min ) / 2.0;

[0016] Where, τ min τ is the minimum value of the predicted dynamic sealing index value distribution range. max τ is the maximum value of the predicted dynamic sealing index value distribution range. mid This is the first search point in the current search range;

[0017] The second search point satisfies the following relationship:

[0018] τ midmid =(τ max +τ mid ) / 2.0;

[0019] Where, τ midmid This is the second search point in the current search range.

[0020] Optionally, the calculation of the pressure data sequence inside the first carriage corresponding to the first search point and the calculation of the pressure data sequence inside the second carriage corresponding to the second search point satisfy the following relationship:

[0021] Based on existing measured external pressure data sequence p e (t), by numerically solving this differential equation, the dynamic sealing index τ is calculated as τ mid and τ midmid The time series p of the internal pressure corresponding to the time i (t);

[0022]

[0023] Where, p e (t) represents the existing measured external pressure data sequence, τ represents the dynamic sealing index, and τ is τ mid or τ midmid p i (t) is the calculated internal pressure data sequence obtained based on the measured external pressure data sequence, where t represents the discrete physical time sequence corresponding to the pressure acquisition process.

[0024] Optionally, updating the search interval based on the magnitude relationship between the first similarity index and the second similarity index includes:

[0025] If the first similarity index is less than or equal to the second similarity index, the right endpoint of the current search interval is shrunk to the second search point; conversely, if the first similarity index is greater than the second similarity index, the left endpoint of the current search interval is shrunk to the first search point.

[0026] Optionally, the final optimal calculation result of the dynamic sealing index of the current train carriage satisfies the following relationship, where τ min_final and τ max_final These represent the minimum and maximum values ​​of the final search interval required to achieve the expected accuracy of the dynamic sealing index calculation:

[0027] τ final =(τ max_final +τ min_final ) / 2.0.

[0028] Secondly, this application discloses a train dynamic sealing index calculation system, 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, it implements the steps of the method described in the first aspect above.

[0029] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in the first aspect.

[0030] Beneficial effects:

[0031] The train dynamic sealing index calculation method provided by this invention employs a ternary search algorithm to search for the optimal train dynamic sealing index within the estimated dynamic sealing index distribution interval. By using a ternary search algorithm with logarithmic time complexity instead of the linear time complexity traversal search method in existing calculation methods, the calculation time for the train dynamic sealing index is significantly reduced, resulting in a significant improvement in efficiency. Furthermore, thanks to the characteristic that the calculation time of the logarithmic time complexity ternary search algorithm does not change significantly with the increase of the search interval size, high computational efficiency and high computational accuracy are achieved simultaneously. Attached Figure Description

[0032] Figure 1 This is a flowchart of a method for calculating the dynamic sealing index of a train according to a selected embodiment of the present invention;

[0033] Figure 2 This is a sequence of measured external and internal pressure data of the train carriage to be analyzed in the selected embodiment of the present invention;

[0034] Figure 3 This is a distribution diagram of the similarity index of all search points in the selected embodiment of the present invention on the search interval. Detailed Implementation

[0035] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an" or "a" and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms "connected" or "linked" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship also changes accordingly.

[0037] Please see Figure 1 This application provides a method for calculating the dynamic sealing index of a train, including:

[0038] The first and second search points of the current search range are determined based on the set distribution range of the estimated dynamic sealing index value.

[0039] The pressure data sequence inside the first carriage corresponding to the first search point is calculated based on the linear assumption pressure transmission model, and the pressure data sequence inside the second carriage corresponding to the second search point is calculated.

[0040] Calculate a first similarity index between the calculated pressure data sequence inside the first carriage and the measured pressure data sequence inside the carriage, and a second similarity index between the calculated pressure data sequence inside the second carriage and the measured pressure data sequence inside the carriage.

[0041] The search range is updated based on the relationship between the first and second similarity indices;

[0042] If the current calculation precision does not reach the set calculation precision, the first and second search points are re-determined based on the updated search interval, and the search is performed again. The current calculation precision is determined based on the length of the current search interval.

[0043] When the current calculation accuracy reaches the required dynamic sealing index calculation accuracy, the final optimal calculation result of the current train car dynamic sealing index is output.

[0044] In this embodiment, the default estimated distribution range is [0, 200]. Setting the distribution range to this range comprehensively covers the distribution range of the actual dynamic sealing index of the currently operating train carriages. In this example, the expected dynamic sealing index calculation accuracy is specified as 0.1.

[0045] When determining the current calculation accuracy based on the current search interval length, the current calculation accuracy of this calculation process is measured by the latest search interval length. That is, if the length of the latest search interval is less than the designed calculation accuracy, the calculation accuracy is considered to meet the preset accuracy requirements. For example, if the current search interval length is less than the set calculation accuracy, it indicates that the current calculation accuracy has reached the expected calculation accuracy requirement for the dynamic sealing index, and the final calculation result of the dynamic sealing index can be output. Conversely, if the current search interval length is not less than the set calculation accuracy, it indicates that the current calculation accuracy has not yet reached the expected calculation accuracy requirement, and the new search process continues to be carried out repeatedly on the updated search interval.

[0046] The aforementioned method for calculating the train dynamic sealing index employs a ternary search algorithm to search for the optimal train dynamic sealing index within the estimated distribution interval. By replacing the linear-time traversal search method with a logarithmic time-complexity ternary search algorithm, the computation time for the train dynamic sealing index is significantly reduced, resulting in a substantial improvement in efficiency. Furthermore, thanks to the characteristic that the computation time of the logarithmic time-complexity ternary search algorithm does not change significantly with the increase in the search interval size, high computational efficiency and high computational accuracy are achieved simultaneously.

[0047] The step of determining the first and second search points of the current search interval based on the set estimated dynamic sealing index value distribution interval includes:

[0048] The current search interval is divided into three segments to obtain the first search point and the second search point. The first search point satisfies the following relationship:

[0049] τ mid =(τ max +τ min ) / 2.0;

[0050] Where, τ min τ is the minimum value (left endpoint) of the predicted dynamic sealing index value distribution range. max τ is the maximum value (right endpoint) of the predicted dynamic sealing index value distribution range. mid This is the first search point in the current search range;

[0051] The second search point satisfies the following relationship:

[0052] τ midmid =(τ max +τ mid ) / 2.0;

[0053] Where, τ midmid This is the second search point in the current search range.

[0054] The calculation of the pressure data sequence inside the first carriage corresponding to the first search point and the calculation of the pressure data sequence inside the second carriage corresponding to the second search point satisfy the following relationship:

[0055] Based on existing measured external pressure data sequence p e (t), by numerically solving this differential equation, the time series p of the internal pressure corresponding to the dynamic sealing index τ being τmid and τmidmid respectively are calculated. i (t).

[0056]

[0057] Where, p e (t) represents the existing measured external pressure data sequence, τ represents the dynamic sealing index, and τ is τ mid or τ midmid p i (t) is the calculated internal pressure data sequence obtained based on the measured external pressure data sequence, where t represents the discrete physical time sequence corresponding to the pressure acquisition process.

[0058] Optionally, updating the search interval based on the magnitude relationship between the first similarity index and the second similarity index includes:

[0059] If the first similarity index is less than or equal to the second similarity index, the right endpoint of the current search interval is shrunk to the second search point; conversely, if the first similarity index is greater than the second similarity index, the left endpoint of the current search interval is shrunk to the first search point.

[0060] In this example, the DTW (Dynamic Time Warping) algorithm is used to determine the difference index dmid (first similarity index) between the calculated pressure sequence inside the first carriage and the measured pressure sequence inside the carriage, and the difference index dmidmid (second similarity index) between the calculated pressure sequence inside the second carriage and the measured pressure sequence inside the carriage. By comparing the relative magnitudes of dmid and dmidmid, the similarity between the first search point and the second search point and the actual dynamic sealing index of the train carriage is determined.

[0061] Specifically, when the first similarity index is less than or equal to the second similarity index, the right endpoint of the current search interval is searched to the second search point; otherwise, the left endpoint of the search interval is searched to the first search point, so as to update the search interval.

[0062] Determine whether the length of the currently updated search interval (current calculation precision) meets the expected calculation precision of 0.1. If it meets the expected calculation precision requirement (i.e., the current updated search interval length is less than 0.1), then output the midpoint of the currently updated search interval as the final calculation result of the dynamic sealing index; otherwise, if it does not meet the expected calculation precision requirement (i.e., the current updated search interval length is not less than 0.1), use the updated search interval as the new search interval, and execute the search step again.

[0063] The final optimal calculation result of the dynamic sealing index of the current train carriage satisfies the following relationship, where τ min_final and τ max_final These represent the minimum and maximum values ​​(i.e., the left and right endpoints) of the final search interval to achieve the expected accuracy requirement for the dynamic sealing index calculation:

[0064] τ final=(τ max_final +τ min_final ) / 2.0.

[0065] In a complete example, considering the special condition of a train passing through a series of extra-long tunnels with a total length exceeding 25km, the calculation algorithm performed 17 interval updates based on the initial search interval [0,200], as shown in Table 1. After a total of 17 interval search calculations, the final calculated result of the dynamic sealing index was determined to be 79.2. This involved obtaining the measured data sequence of external and internal pressure of the train carriages to be analyzed, as shown in Table 1. Figure 2 As shown, Figure 3 The distribution of the similarity index (normalized DTW distance = DTW distance value / maximum DTW distance) of all searched points within the search interval further confirmed the reliability of the calculation results.

[0066] The dynamic sealing index calculation method of the present invention takes only 2.8 seconds to calculate the entire process of the embodiment, which is a significant improvement in calculation efficiency compared with the traditional dynamic sealing index calculation method.

[0067] Table 1. Calculation data for 17 interval searches.

[0068]

[0069]

[0070] This application also provides a train dynamic sealing index calculation system, 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, it implements the steps of the above-described method. This train dynamic sealing index calculation system can implement various embodiments of the above-described train dynamic sealing index calculation method and achieve the same beneficial effects; further details are omitted here.

[0071] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method steps described above. This readable storage medium can implement various embodiments of the above-described train dynamic sealing index calculation method and achieve the same beneficial effects; further details are omitted here.

[0072] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for calculating a train dynamic sealing index, characterized in that, The method comprises the following steps: determining a first search point and a second search point of a current search interval according to a set estimated dynamic sealing index value distribution interval; calculating a first car interior calculation pressure data sequence corresponding to the first search point and a second car interior calculation pressure data sequence corresponding to the second search point based on a linear assumed pressure transmission model; calculating a first similarity index between the first car interior calculation pressure data sequence and a car interior measured pressure data sequence, and a second similarity index between the second car interior calculation pressure data sequence and the car interior measured pressure data sequence; updating the search interval according to a size relationship between the first similarity index and the second similarity index; redetermining the first search point and the second search point in the updated search interval and performing a re-search when a current calculation precision does not reach a set calculation precision, wherein the current calculation precision is determined according to a current search interval length; outputting a final optimal calculation result of a current train car dynamic sealing index when the current calculation precision reaches a required dynamic sealing index calculation precision. The method further comprises the following steps: performing three-section segmentation on the current search interval to obtain the first search point and the second search point, wherein the first search point satisfies the following relationship: τ mid = (τ max + τ min ) / 2.0; wherein τ min is a minimum value of a set estimated dynamic sealing exponent value distribution interval, τ max is a maximum value of a set estimated dynamic sealing exponent value distribution interval, τ mid is a first search point of a current search interval; the second search point satisfies the following relationship: τ midmid = (τ max + τ mid ) / 2.0; wherein τ midmid is a second search point of the current search interval; the calculation of the first car interior calculation pressure data sequence corresponding to the first search point and the second car interior calculation pressure data sequence corresponding to the second search point satisfies the following relationship: Based on the existing measured external pressure data sequence , the dynamic sealing index is calculated by numerically solving the differential equation for τ mid and τ midmid , respectively mid ; ； wherein, represents a sequence of measured external pressure data, represents a dynamic sealing index, is τ mid or τ midmid , is a sequence of calculated internal pressure data based on the sequence of measured external pressure data, represents a sequence of discrete physical times corresponding to the pressure acquisition process.

2. The method of claim 1, wherein, the minimum value of the set estimated dynamic sealing index value distribution interval is 0, and the maximum value is 200.

3. The method of claim 1, wherein, The method further comprises the following steps: if the first similarity index is less than or equal to the second similarity index, the right end point of the current search interval is contracted to the second search point; otherwise, if the first similarity index is greater than the second similarity index, the left end point of the current search interval is contracted to the first search point.

4. The method of claim 1, wherein, The final optimal calculation result of the current train car dynamic sealing index satisfies the following relationship, where τ min_final and τ max_final respectively represent the minimum value and the maximum value of the final search interval to reach the expected dynamic sealing index calculation accuracy requirement: τ final = (τ max_final + τ min_final ) / 2.

0.

5. A train dynamic sealing index calculation system comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the method of any one of claims 1 to 4.

6. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the method steps of any one of claims 1 to 4.

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