Heavy haul railway track quality detection method, device, equipment, readable storage medium and program product

Abstract

The invention relates to a heavy haul railway track quality detection method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: dividing a target line into unit sections corresponding to each line type according to line type distribution information of the target line; obtaining unit quality evaluation parameters of each unit section according to the track detection data of each unit section at the plurality of detection time points; obtaining a unit quality detection result of each unit section according to the unit quality evaluation parameter of each unit section and the type quality control parameter corresponding to the line type of the unit section; and obtaining a track quality detection result of the target line according to the unit quality detection result of each unit section. By adopting the method, targeted detection of the heavy haul railway track quality can be realized, and the track quality detection precision and the track maintenance work efficiency are improved.

Description

Technical Field

[0001] The present application relates to the field of railway engineering technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for detecting the quality of heavy-load railway tracks. Background Art

[0002] Track quality is a key factor in ensuring heavy-haul railway safety. Problems such as track unevenness and structural deterioration can seriously impact train safety. Therefore, continuous inspection and maintenance of track quality are crucial for heavy-haul railways.

[0003] In related technologies, railway maintenance generally divides the line into equal-length sections, formulating corresponding inspection and maintenance strategies based on the changing trends in the track quality status of each section. However, in actual line operation, different sections often experience differences in environmental conditions, track structure forms, design parameters, and operating loads. Related technologies fail to account for these differences in different sections of the line, making it difficult to achieve targeted inspections of track quality in different parts of the line, failing to highlight weak links in the line, and thus affecting the accuracy of railway track quality inspections and the efficiency of track maintenance. Summary of the Invention

[0004] Based on this, it is necessary to provide a heavy-load railway track quality detection method, device, computer equipment, computer-readable storage medium and computer program product to address the above technical problems.

[0005] In a first aspect, the present application provides a method for detecting the quality of heavy-load railway tracks, comprising:

[0006] Dividing the target line into unit sections corresponding to each line type according to line type distribution information of the target line;

[0007] Obtaining unit quality assessment parameters of each unit section based on track detection data of each unit section at multiple detection time points;

[0008] Obtaining a unit quality detection result of each unit section according to the unit quality assessment parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section;

[0009] According to the unit quality detection results of each unit section, the track quality detection result of the target line is obtained.

[0010] In one embodiment, before obtaining the unit quality detection result of each unit section based on the unit quality assessment parameter of each unit section and the type quality control parameter corresponding to the line type of the unit section, the method includes: for each line type, collecting statistics on the first distribution information of the unit quality assessment parameter of each unit section corresponding to the line type; and determining the type quality control parameter of each line type based on the first distribution information and a first accumulation condition corresponding to each line type.

[0011] In one embodiment, the unit quality assessment parameters of each unit segment are obtained based on the track detection data of each unit segment at multiple detection time points, including: calculating the unit quality index of the unit segment at each detection time point based on the track detection data of the unit segment at each detection time point; obtaining the unit quality management index of the unit segment based on the second distribution information and second accumulation condition of each unit quality index of the unit segment; calculating the unit quality degradation rate of the unit segment based on the time change trend of each unit quality index; and constructing the unit quality assessment parameters including the unit quality management index and the unit quality degradation rate.

[0012] In one embodiment, the unit quality detection result of each unit segment is obtained based on the unit quality assessment parameters and the type quality control parameters of each unit segment, including: comparing the unit quality management index of the unit segment with the quality management index threshold in the type quality control parameters to obtain a first comparison result; comparing the unit quality degradation rate of the unit segment with the quality degradation rate threshold in the type quality control parameters to obtain a second comparison result; and obtaining the unit quality detection result of the unit segment based on the first comparison result and the second comparison result.

[0013] In one embodiment, obtaining the unit quality detection result of the unit section based on the first comparison result and the second comparison result includes: obtaining the unit quality grade of the unit section based on the first comparison result and the second comparison result of the unit section; obtaining the unit quality detection result based on the unit quality grade; after obtaining the track quality detection result of the target line based on the unit quality detection results of each unit section, it also includes: obtaining a segmented maintenance plan for the target line based on the unit quality grade of each unit section in the target line.

[0014] In one embodiment, before obtaining the unit quality assessment parameters of each unit segment based on the track detection data of each unit segment at multiple detection time points, the method includes: obtaining initial track detection data and detection environment parameters of the unit segment at multiple time points in a target period; and cleaning the initial track detection data according to the detection environment parameters to obtain the track detection data.

[0015] In a second aspect, the present application further provides a heavy-load railway track quality detection device, comprising:

[0016] a unit division module, configured to divide the target line into unit sections corresponding to each line type according to line type distribution information of the target line;

[0017] a quality statistics module, configured to obtain a unit quality assessment parameter of each unit section based on the track detection data of each unit section at a plurality of detection time points;

[0018] a unit detection module, configured to obtain a unit quality detection result of each unit section according to the unit quality evaluation parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section;

[0019] The result acquisition module is used to obtain the track quality detection result of the target line according to the unit quality detection result of each unit section.

[0020] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0021] Dividing the target line into unit sections corresponding to each line type according to line type distribution information of the target line;

[0022] Obtaining unit quality assessment parameters of each unit section based on track detection data of each unit section at multiple detection time points;

[0023] Obtaining a unit quality detection result of each unit section according to the unit quality assessment parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section;

[0024] According to the unit quality detection results of each unit section, the track quality detection result of the target line is obtained.

[0025] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0026] Dividing the target line into unit sections corresponding to each line type according to line type distribution information of the target line;

[0027] Obtaining unit quality assessment parameters of each unit section based on track detection data of each unit section at multiple detection time points;

[0028] Obtaining a unit quality detection result of each unit section according to the unit quality assessment parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section;

[0029] According to the unit quality detection results of each unit section, the track quality detection result of the target line is obtained.

[0030] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0031] Dividing the target line into unit sections corresponding to each line type according to line type distribution information of the target line;

[0032] Obtaining unit quality assessment parameters of each unit section based on track detection data of each unit section at multiple detection time points;

[0033] Obtaining a unit quality detection result of each unit section according to the unit quality assessment parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section;

[0034] According to the unit quality detection results of each unit section, the track quality detection result of the target line is obtained.

[0035] The above-mentioned heavy-haul railway track quality inspection method, apparatus, computer device, computer-readable storage medium, and computer program product first divide the target line into unit sections corresponding to each line type based on the line type distribution information of the target line. Then, based on the track inspection data of each unit section at multiple inspection time points, the unit quality assessment parameters of each unit section are obtained. Then, based on the unit quality assessment parameters of each unit section and the type quality control parameters corresponding to the line type of the unit section, the unit quality inspection results of each unit section are obtained. Finally, based on the unit quality inspection results of each unit section, the track quality inspection results of the target line are obtained. This scheme, by dividing the target line into unit sections based on the line type distribution information of the target line, can make each unit section correspond to a single line type, avoiding the complex situation where the same unit section contains units corresponding to multiple line types. After calculating the unit quality assessment parameters of each unit section, the unit quality assessment parameters of each unit section are analyzed and evaluated using the type quality control parameters corresponding to the line type to which each unit section belongs. This allows the quality analysis of each unit section using targeted standards according to the line type to which it corresponds, resulting in more accurate and targeted unit quality inspection results. Subsequently, the track quality inspection results of the target line obtained based on the unit quality inspection results of each unit section can accurately reflect the quality conditions of different sections in the target line, which is beneficial for maintenance personnel to accurately identify weak areas in the line, so that targeted repairs can be carried out on the track within the short window time of heavy-load railways, which is beneficial to improving the efficiency and accuracy of heavy-load railway maintenance work. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 Schematic diagram of a flow chart of a heavy-load railway track quality inspection method according to one embodiment;

[0038] Figure 2 Schematic diagram of a process for obtaining unit quality assessment parameters in one embodiment;

[0039] Figure 3 A schematic flow chart of a method for inspecting heavy-load railway track quality in another embodiment;

[0040] Figure 4 is a cumulative distribution graph of unit quality index in one embodiment;

[0041] Figure 5 This is a structural block diagram of a heavy-load railway track quality detection device in one embodiment;

[0042] Figure 6 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0044] In one embodiment, Figure 1 As shown, a method for detecting the quality of heavy-load railway tracks is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0045] Step S101 : dividing the target line into unit sections corresponding to each line type according to line type distribution information of the target line.

[0046] Specifically, the target line may be a heavy-load railway requiring track quality inspection. The target line's line type distribution information may include information such as the various line types included in the target line (including but not limited to curves, bridges, tunnels, switches, etc.), the number of line sections corresponding to each line type, and the location of the line sections corresponding to each line type within the target line. In this step, each line section corresponding to each line type may be treated as a unit section based on the target line's line type distribution information. For example, the target line may be divided into multiple curve sections, multiple bridge sections, multiple tunnel sections, and multiple switch sections. A curve section may correspond to a curve within the target line, a bridge section may correspond to a bridge within the target line, a tunnel section may correspond to a tunnel within the target line, and a switch section may correspond to a switch section within the target line.

[0047] Optionally, when dividing the line types, the up track and the down track can also be distinguished, for example, they can be classified into up curve, up bridge, up tunnel, up switch, down curve, down bridge, down tunnel, down switch, etc.

[0048] Step S102 : obtaining unit quality assessment parameters of each unit segment based on the track detection data of each unit segment at multiple detection time points.

[0049] The track inspection data can be obtained by inspecting the geometric deviations of the target line using an inspection vehicle. For example, the inspection vehicle can be used to collect track inspection data for the target line. Then, based on the division of the target line into unit sections, the track inspection data corresponding to each unit section can be extracted from the track inspection data corresponding to the entire target line. For example, the track inspection data can include geometric deviation values ​​corresponding to multiple geometric irregularity indicators, where the geometric irregularity indicators can include left height difference, right height difference, left track direction, right track direction, track gauge, level, and triangular pit.

[0050] In this step, track inspection data for each unit section collected at multiple inspection time points within the target period can be obtained and then statistically analyzed to obtain unit quality assessment parameters for each unit section. Optionally, the unit quality assessment parameters for each unit section can include, but are not limited to, one or more data such as the unit quality management index and the unit quality degradation rate of the unit section. The unit quality management index can indicate the overall track irregularity of the unit section during the target period; the unit quality degradation rate can indicate the development trend of the track irregularity of the unit section during the target period.

[0051] Step S103 : obtaining a unit quality detection result of each unit section according to the unit quality evaluation parameter of each unit section and the type quality control parameter corresponding to the line type of the unit section.

[0052] For each unit section, corresponding type quality control parameters can be obtained based on its corresponding line type. The type quality control parameters corresponding to each line type can be set based on the distribution characteristics of the unit quality assessment parameters of each unit section corresponding to that line type. These parameters can be used to analyze and evaluate the unit quality assessment parameters of the unit sections belonging to that line type to determine the unit section's defect risk. Exemplarily, the type quality control parameters may include a quality management index threshold corresponding to the unit quality management index and / or a quality degradation rate threshold corresponding to the unit quality degradation rate.

[0053] Among them, for each unit section, it is possible to determine whether the unit quality assessment parameter of the unit section meets one or more quality control conditions based on the relationship between its corresponding type quality control parameter and the unit quality assessment parameter, and then obtain the unit quality detection result corresponding to the unit section. For example, when there is one quality control condition, if the unit quality assessment parameter meets the condition, a unit quality detection result indicating that there is no defect in the track of the unit section can be obtained; otherwise, a unit quality detection result indicating that there is a defect in the track of the unit section can be obtained. For another example, when there are multiple quality control conditions, the track quality of the unit section can be graded according to the number of quality control conditions that the unit quality assessment parameter meets, and a unit quality detection result indicating the quality level corresponding to the track quality of the unit section can be obtained.

[0054] Step S104 , obtaining the track quality detection result of the target line according to the unit quality detection result of each unit section.

[0055] By combining the unit quality test results of each unit section, the track quality test results corresponding to the entire target line can be obtained. For example, the track quality test results for the target line may include the unit quality test results of each unit section, the distribution of different types of unit quality test results obtained based on the unit quality test results of each unit section, and the distribution of different types of unit quality test results in the unit sections corresponding to each line type.

[0056] In the above-mentioned heavy-haul railway track quality inspection method, by dividing the target line into unit sections according to the line type distribution information of the target line, each unit section can correspond to a separate line type, avoiding the complex situation where the same unit section contains sections corresponding to multiple line types; and after calculating the unit quality assessment parameters of each unit section, the unit quality assessment parameters of the unit section are analyzed and evaluated using the type quality control parameters corresponding to the line type to which each unit section belongs. It is then possible to perform a quality analysis on each unit section according to the line type to which it corresponds, using targeted standards, to obtain more accurate and targeted unit quality inspection results. Subsequently, the track quality inspection results of the target line obtained based on the unit quality inspection results of each unit section can accurately reflect the quality of different sections in the target line, which is beneficial for maintenance personnel to accurately identify weak areas in the line, so that targeted repairs can be carried out on the track within the short window time of the heavy-haul railway, which is beneficial to improving the efficiency and accuracy of heavy-haul railway maintenance work.

[0057] In an exemplary embodiment, before obtaining the unit quality detection results of each unit section based on the unit quality assessment parameters of each unit section and the type quality control parameters corresponding to the line type of the unit section, it can include: for each of the line types, statistically analyzing the first distribution information of the unit quality assessment parameters of each of the unit sections corresponding to the line type; and determining the type quality control parameters of each line type based on the first distribution information corresponding to each line type and the first accumulation condition.

[0058] Specifically, the type quality control parameter for each line type can be obtained based on the unit quality assessment parameters of each corresponding unit segment. For each line type, the unit quality assessment parameters of each corresponding unit segment can be collected and statistically analyzed to obtain corresponding first distribution information. Based on the first distribution information, a value of the unit quality assessment parameter that satisfies the first accumulation condition can be determined and used as the type quality control parameter for the line type.

[0059] For example, in this embodiment, for each line type, first distribution information of the unit quality assessment parameters for each unit section corresponding to the same line type can be statistically analyzed by plotting a cumulative distribution graph, fitting a cumulative distribution function, or other methods. Based on this first distribution information, the value of the unit quality assessment parameter that satisfies a first cumulative condition can be determined. For example, the first cumulative condition can be that the cumulative proportion of the unit quality assessment parameters is no less than a preset probability threshold (e.g., 80%). Based on this first cumulative condition, the value of the type quality control parameter can be determined in the cumulative distribution graph or cumulative distribution function.

[0060] It is understandable that when the unit quality assessment parameter includes multiple types of data, the corresponding control parameters can be determined based on the first accumulation condition for the distribution information of each type of data, and then a type quality control parameter including the multiple control parameters can be constructed. For example, taking the example of the unit quality assessment parameter including the unit quality management index and the unit quality degradation rate, in this embodiment, the first distribution information of the unit quality management index and the unit quality degradation rate of each unit section corresponding to the same line type can be first statistically analyzed, and then, based on the first accumulation condition, the quality management index threshold corresponding to the unit quality management index and the quality degradation rate threshold corresponding to the unit quality degradation rate can be determined, and then the type quality control parameter including the quality management index threshold and the quality degradation rate threshold can be constructed.

[0061] In this embodiment, by statistically analyzing the first distribution information of the unit quality assessment parameters of each corresponding unit section for each line type, and then determining the type quality control parameters corresponding to the line type in combination with the first accumulation condition, the type quality control parameters corresponding to each line type can be determined based on the general characteristics of the quality status of the unit sections corresponding to different line types in the target line. The parameters can then be used to achieve a more targeted and accurate assessment of the track quality of the unit sections, thereby obtaining quality inspection results with more reference value.

[0062] In an exemplary embodiment, Figure 2 As shown, based on the track inspection data of each unit section at multiple inspection time points, the unit quality evaluation parameters of each unit section are obtained, which may include:

[0063] Step S201 : calculating the unit quality index of the unit segment at each detection time point based on the track detection data of the unit segment at each detection time point.

[0064] In this step, for each detection time point, the unit quality index of the unit segment at the time point can be calculated using the track detection data corresponding to the time point.

[0065] The track inspection data of a unit section may include geometric deviation values ​​corresponding to multiple geometric irregularity indicators such as left height, right height, left track direction, right track direction, track gauge, level, and triangular pits, collected at multiple sampling points within the unit section. By calculating the standard deviation of the geometric deviation values ​​of various geometric irregularity indicators of the unit section at a certain inspection time point and then summing them, the track irregularity quality index (TQI) of the unit section at the corresponding inspection time point can be obtained and used as the unit quality index of the unit section. For example, the calculation process of the unit quality index of the unit section can be expressed as:

[0066]

[0067]

[0068]

[0069] Where, is the track irregularity quality index of the unit section (i.e., unit quality index), For the The standard deviation of the geometric deviation value of the geometric irregularity index, For the The geometric irregularity index is The geometric deviation value of the sampling points, is the number of sampling points in the unit segment.

[0070] Step S202 : obtaining a unit quality management index of the unit segment according to the second distribution information and the second accumulation condition of each unit quality index of the unit segment.

[0071] In this step, statistics can be collected for multiple unit quality indices corresponding to multiple detection time points for the same unit segment to obtain corresponding second distribution information. Based on the second distribution information, a unit quality index value that satisfies the second accumulation condition can be determined and used as the unit quality management index corresponding to the unit segment.

[0072] For example, in this embodiment, for each unit segment, second distribution information of multiple unit quality indices corresponding to multiple detection time points for the same unit segment can be statistically analyzed by plotting a cumulative distribution graph, fitting a cumulative distribution function, or other methods. Based on this second distribution information, the value of the unit quality index that satisfies a second cumulative condition can then be determined. For example, the second cumulative condition can be that the cumulative proportion of the unit quality indices is no less than a preset probability threshold (e.g., 80%). Based on this second cumulative condition, the value of the unit quality management index can be determined in a cumulative distribution graph or cumulative distribution function.

[0073] Step S203 : calculating the unit quality degradation rate of the unit section according to the time variation trend of each unit quality index.

[0074] In this step, based on the multiple unit quality indices corresponding to multiple detection time points of each unit segment obtained previously, the unit quality degradation rate of the unit segment in the target period can be calculated according to the time sequence relationship of the multiple unit quality indices.

[0075] For example, the calculation process of the unit quality degradation rate can be expressed as:

[0076]

[0077] Where, is the unit quality degradation rate of the unit section (unit can be mm / month), Indicates the The unit quality index corresponding to each detection time point (unit can be mm), is the total number of detection time points in the target period.

[0078] Step S204 : constructing unit quality evaluation parameters including a unit quality management index and a unit quality degradation rate.

[0079] In this step, the unit quality assessment parameters corresponding to each unit segment can be constructed based on the unit quality management index and unit quality degradation rate corresponding to each unit segment. The unit quality assessment parameters corresponding to each unit segment can include the unit quality management index and unit quality degradation rate of the unit segment.

[0080] In this embodiment, by first calculating the unit quality index of a unit section at each inspection time point, and then calculating the unit quality management index of the unit section across multiple inspection time points, a comprehensive assessment of the track quality of the unit section within the target period can be performed, which helps improve the accuracy of the unit section's quality inspection results. By calculating the unit quality degradation rate of the unit section, the temporal trend of the unit section's track quality can be quantified. Subsequently, by constructing a unit quality assessment parameter that includes the unit quality management index and the unit quality degradation rate, the unit quality assessment parameter can more accurately and comprehensively reflect the track quality of the unit section during the target period, facilitating a more accurate assessment of the unit section's track quality later on.

[0081] In an exemplary embodiment, obtaining the unit quality detection result of each unit segment based on the unit quality assessment parameters and type quality control parameters of each unit segment may include: comparing the unit quality management index of the unit segment with the quality management index threshold in the type quality control parameter to obtain a first comparison result; comparing the unit quality degradation rate of the unit segment with the quality degradation rate threshold in the type quality control parameter to obtain a second comparison result; and obtaining the unit quality detection result of the unit segment based on the first comparison result and the second comparison result.

[0082] Specifically, the type quality control parameters corresponding to each line type may include a quality management index threshold and a quality degradation rate threshold corresponding to that line type. The quality management index threshold can be determined based on the distribution characteristics of the unit quality management indexes of each unit segment corresponding to the same line type in the target line. It can be a representative parameter that covers the unit quality management indexes of most unit segments in that line type. Similarly, the quality degradation rate threshold can also be determined based on the distribution characteristics of the unit quality degradation rates of each unit segment corresponding to the same line type in the target line. It can be a representative parameter that covers the unit quality degradation rates of most unit segments in that line type.

[0083] Based on this, in this embodiment, the unit quality management index corresponding to each unit section can be compared with the quality management index threshold to obtain a first comparison result. The first comparison result may include whether the size relationship between the unit quality management index and the quality management index threshold satisfies a preset quality control condition. The quality control condition may be that the unit quality management index is less than the quality management index threshold. Thus, when the first comparison result indicates that the unit quality management index corresponding to the unit section is not less than the quality management index threshold, it can be determined that the unit quality management index of the unit section deviates from the normal range of the line type, that is, it can be determined that the overall track irregularity of the unit section during the target period deviates from the normal range; conversely, it can be determined that the overall track irregularity of the unit section during the target period is within the normal range.

[0084] Similarly, in this embodiment, the unit quality degradation rate corresponding to each unit section can also be compared with the quality degradation rate threshold to obtain a second comparison result. The second comparison result may include whether the size relationship between the unit quality degradation rate and the quality degradation rate threshold satisfies a preset quality control condition. The quality control condition may be that the unit quality degradation rate is less than the quality degradation rate threshold. Thus, when the second comparison result indicates that the unit quality degradation rate corresponding to the unit section is not less than the quality degradation rate threshold, it can be determined that the unit quality degradation rate of the unit section deviates from the normal range of the line type, that is, it can be determined that the development trend of the track irregularity of the unit section in the target period deviates from the normal range; conversely, it can be determined that the development trend of the track irregularity of the unit section in the target period is within the normal range.

[0085] After obtaining the first comparison result and the second comparison result, the two can be combined to obtain the unit quality detection result of the unit section. For example, when the first comparison result of the unit section indicates that the size relationship between the unit quality management index and the quality management index threshold satisfies the preset quality control condition, and the second comparison result indicates that the size relationship between the unit quality degradation rate and the quality degradation rate threshold satisfies the preset quality control condition, a unit quality detection result indicating that the track of the unit section is free of defects can be obtained; and when at least one of the first comparison result and the second comparison result indicates that the preset quality control condition is not satisfied, a unit quality detection result indicating that the track of the unit section is defective can be obtained.

[0086] In this embodiment, by comparing the unit quality management index of the unit section with the quality management index threshold, and comparing the unit quality degradation rate with the quality degradation rate threshold, and then combining the two comparison results to obtain the unit quality detection result of the unit section, a multi-dimensional evaluation of the track quality and quality degradation of the unit section can be achieved, thereby improving the comprehensiveness, stability and accuracy of the unit quality detection results.

[0087] In an exemplary embodiment, a unit quality detection result of a unit section is obtained based on a first comparison result and a second comparison result, including: obtaining a unit quality grade of the unit section based on the first comparison result and the second comparison result of the unit section; obtaining a unit quality detection result based on the unit quality grade; after obtaining a track quality detection result of a target line based on the unit quality detection results of each unit section, it also includes: obtaining a segmented maintenance plan for the target line based on the unit quality grade of each unit section in the target line.

[0088] Specifically, in this embodiment, the first comparison result and the second comparison result of the unit section can be combined to determine the severity of the disease risk in the unit section, thereby grading the track quality of the unit section and obtaining the unit quality grade of the unit section.

[0089] Exemplarily, if the first comparison result of the unit segment indicates that the size relationship between the unit quality management index and the quality management index threshold satisfies the preset quality control condition (for example, the unit quality management index is less than the quality management index threshold), and the second comparison result of the unit segment indicates that the size relationship between the unit quality degradation rate and the quality degradation rate threshold satisfies the preset quality control condition (for example, the unit quality degradation rate is less than the quality degradation rate threshold), then it can be determined that the unit segment is an excellent unit segment with no defects, and thus its corresponding unit quality grade can be determined to be the first level.

[0090] Exemplarily, when the first comparison result of the unit segment indicates that the size relationship between the unit quality management index and the quality management index threshold does not meet the preset quality control conditions (for example, the unit quality management index is not less than the quality management index threshold), or the second comparison result of the unit segment indicates that the size relationship between the unit quality degradation rate and the quality degradation rate threshold does not meet the preset quality control conditions (for example, the unit quality degradation rate is not less than the quality degradation rate threshold), then it can be determined that the unit segment is a conventional unit segment with a conventional disease risk, and thus its corresponding unit quality grade can be determined to be the second level.

[0091] Exemplarily, when the first comparison result of the unit segment indicates that the size relationship between the unit quality management index and the quality management index threshold does not meet the preset quality control conditions (for example, the unit quality management index is not less than the quality management index threshold), and the second comparison result of the unit segment indicates that the size relationship between the unit quality degradation rate and the quality degradation rate threshold does not meet the preset quality control conditions (for example, the unit quality degradation rate is not less than the quality degradation rate threshold), then it can be determined that the unit segment is a risky unit segment with a serious disease risk, and its corresponding unit quality level can be determined to be the third level.

[0092] After the track quality of the unit section is graded, a unit quality test result including the unit quality grade of the unit section can be obtained.

[0093] After obtaining the track quality inspection results for the target line, a segmented maintenance plan for the target line can be further determined. The segmented maintenance plan can include maintenance strategy information for each unit section in the target line, and the maintenance strategy information can be determined based on the unit quality level corresponding to the unit section.

[0094] For example, for a unit section with a unit quality level of the first level, the corresponding maintenance strategy information may be an instruction to perform monthly inspections and preventive repairs on the unit section at a first frequency; for a unit section with a unit quality level of the second level, the corresponding maintenance strategy information may be an instruction to promptly rectify any defects in the unit section and to perform inspections and targeted maintenance on the unit section at a second frequency; and for a unit section with a unit quality level of the third level, the corresponding maintenance strategy information may be an instruction to promptly rectify any defects in the unit section and to perform inspections and targeted maintenance on the unit section at a third frequency. The relationship among the first frequency, the second frequency, and the third frequency may be: first frequency ≤ second frequency ≤ third frequency.

[0095] In this embodiment, the track quality of the unit sections is graded according to the first comparison result and the second comparison result of the unit sections, and a segmented maintenance plan is obtained according to the unit quality grade of each unit section in the target line. This allows for targeted maintenance and repair based on the track quality characteristics of different sections in the line, which is beneficial for the rational allocation of maintenance and repair resources in a shorter window time and improves maintenance efficiency.

[0096] In an exemplary embodiment, before obtaining the unit quality assessment parameters of each unit segment based on the track detection data of each unit segment at multiple detection time points, the process may include: obtaining initial track detection data and detection environment parameters of the unit segment at multiple time points in a target period; and cleaning the initial track detection data based on the detection environment parameters to obtain track detection data.

[0097] In this embodiment, initial track detection data and detection environment parameters of each unit section at multiple time points in the target period can be obtained first, and then the initial track detection data can be cleaned to obtain track detection data for subsequent statistical unit quality assessment parameters.

[0098] The initial track inspection data for a unit section at a specific time point can be extracted from the initial track inspection data for the target line at the corresponding time point. The initial track inspection data for the target line can be data collected at each time point using equipment such as an inspection vehicle to inspect the track condition of the target line at preset time intervals during a target period. The inspection environment parameters for the unit section at each time point can include weather data at that time point, inspection vehicle operation data, and other data.

[0099] Among them, based on the detection environment parameters of the unit section at a certain point in time, it is possible to determine the interference factors that may exist when testing the track status of the unit section at that point in time. For example, based on weather data, the sunlight status and whether extreme weather conditions occurred during the testing process can be determined, while based on the operation data of the testing vehicle, the testing speed, the presence of reverse curves, the presence of lateral crossings, etc. during the testing process can be determined. Therefore, based on the detection environment parameters of the unit section at a certain point in time, the initial track testing data at that point in time can be cleaned, including but not limited to eliminating invalid data and correcting interfered data, to obtain track testing data at multiple testing time points that can be used for statistical analysis of subsequent unit quality assessment parameters.

[0100] In this embodiment, by obtaining initial track detection data and detection environment parameters, and then cleaning the initial track detection data according to the detection environment parameters to obtain track detection data for subsequent processing, the interference of environmental factors on the track detection data can be eliminated, which is conducive to improving the accuracy and reliability of subsequent track quality assessment.

[0101] In an exemplary embodiment, Figure 3 As shown, a method for detecting the quality of heavy-load railway tracks is provided, which may specifically include the following steps:

[0102] Step S1 : Divide the target line into unit sections corresponding to each line type according to the line type distribution information of the target line.

[0103] Specifically, in this step, the various line types involved in the target route can be determined based on the target route's line type distribution information. The target route can then be divided into unit sections corresponding to each line type, based on the location of the line sections corresponding to each line type within the target route. For example, if the target route involves different line types, such as curves, bridges, tunnels, and switches, the unit sections can be divided according to each line type. Furthermore, the differences between uplink and downlink tracks can be taken into account to further subdivide the line types.

[0104] Step S2: obtaining unit quality assessment parameters of each unit section based on the track detection data of each unit section at multiple detection time points.

[0105] During maintenance of the target line, an inspection vehicle can be used to inspect the track condition of the target line at preset time intervals (e.g., one month), and initial track inspection data for the target line can be collected at each time point. This initial track inspection data can include geometric deviation data (e.g., left height difference, right height difference, left track direction, right track direction, track gauge, level, triangular pits, etc.) collected at multiple sampling points along the target line at preset sampling point intervals (e.g., 0.25 meter). Furthermore, when inspecting the track condition of the target line, corresponding inspection environment parameters can also be collected simultaneously. These inspection environment parameters can include weather data, inspection vehicle operation data, and so on.

[0106] In this step, initial track inspection data and inspection environment parameters for the target line at multiple time points can be obtained. Based on the location distribution of each unit section on the target line, initial track inspection data and inspection environment parameters corresponding to each unit section can be extracted. Then, based on the inspection environment parameters, the initial track inspection data can be cleaned to remove invalid data affected by factors such as lateral crossings and low driving speeds. Furthermore, interference caused by sunlight interference, extreme weather conditions, inspection speed, and reverse curves can be eliminated. This results in track inspection data from multiple inspection time points that can be used to calculate statistical unit quality assessment parameters.

[0107] Among them, according to the track detection data of each unit section at multiple detection time points, the unit quality index of each unit section at each detection time point can be calculated separately. Then, according to the second distribution information and the second accumulation condition of the unit quality index of the same unit segment at multiple detection time points, the unit quality management index of the unit segment is obtained. At the same time, the corresponding unit quality degradation rate can be calculated based on the time variation trend of the unit quality index of the same unit section at multiple detection time points. , so that the unit quality assessment parameters of the unit segment can be constructed. Among them, the unit quality assessment parameters can include the unit quality management index and unit quality degradation rate .

[0108] For example, the unit quality index of the unit segment at multiple detection time points is The second distribution information may be a unit quality index The second cumulative condition can be the unit quality index The cumulative proportion of is not less than a preset probability threshold (for example, 80%), so that according to the second cumulative condition, the unit quality management index can be determined in the cumulative distribution diagram The value of .

[0109] For example, please refer to Figure 4 , Figure 4 Part (a) shows the unit quality index of the unit section samples (corresponding to curve units, turnout units, bridge units and tunnel units) selected for each line type in the uplink track of the target line. The cumulative distribution plot of Figure 4 Part (b) shows the unit quality index of the unit section samples (corresponding to curve units, turnout units, bridge units and tunnel units) selected for each line type in the down track of the target line. Based on the cumulative distribution diagram, the unit quality management index corresponding to each unit section can be determined according to the second cumulative condition. , of which the unit quality management index Not less than unit quality index The cumulative share is 80%.

[0110] Step S3: For each line type, first distribution information of unit quality assessment parameters of each unit section corresponding to the line type is collected, and type quality control parameters of each line type are determined based on the first distribution information and the first accumulation condition corresponding to each line type.

[0111] Specifically, different line types in railways usually correspond to different environmental conditions, track structure forms, design parameters and operating loads, so different line types usually have different quality characteristics. Based on this, in this step, for each line type, the unit quality management index of multiple unit sections belonging to the same line type can be calculated. and unit quality degradation rate Statistics are performed separately to obtain the first distribution information corresponding to the two data. For example, the first distribution information of the unit quality assessment parameter can be a cumulative distribution graph, and the first cumulative condition can be a unit quality management index. and unit quality degradation rate The cumulative proportion of each is not less than the preset probability threshold (for example, 80%). Thus, according to the first cumulative condition, the unit quality management index The quality management index threshold is determined in the cumulative distribution diagram of The quality degradation rate threshold is determined from the cumulative distribution diagram of . Thus, the type quality control parameters of this line type can be constructed.

[0112] Step S4 , obtaining a unit quality detection result of each unit section according to the unit quality evaluation parameter of each unit section and the type quality control parameter corresponding to the line type of the unit section.

[0113] In this step, the unit quality management index of each unit section can be The first comparison result is obtained by comparing the quality management index threshold of the corresponding line type, and the unit quality degradation rate of each unit section is calculated. The second comparison result is compared with the quality degradation rate threshold corresponding to the line type. The track quality of the unit section can then be graded based on the first and second comparison results to obtain a unit quality grade for the unit section. A unit quality detection result including the unit quality grade for the unit section can then be obtained.

[0114] Wherein, if the first comparison result of the unit segment indicates the unit quality management index is less than the quality management index threshold, the second comparison result indicates the unit quality degradation rate If the value of the quality degradation rate is less than the quality degradation rate threshold, the unit section can be determined to be an excellent unit section without any defects, and thus the corresponding unit quality grade can be determined to be the first grade.

[0115] Wherein, if the first comparison result of the unit segment indicates the unit quality management index is not less than the quality management index threshold, or the second comparison result indicates the unit quality degradation rate is not less than the quality degradation rate threshold, that is, when only one of the two situations occurs, the unit section can be determined to be a conventional unit section with conventional disease risks, and thus its corresponding unit quality grade can be determined to be the second level.

[0116] Wherein, if the first comparison result of the unit segment indicates the unit quality management index is not less than the quality management index threshold, and the second comparison result indicates the unit quality degradation rate If the value is not less than the quality degradation rate threshold, the unit section can be determined to be a risk unit section with a serious disease risk, and thus the corresponding unit quality grade can be determined to be the third level.

[0117] Step S5: obtaining the track quality detection result of the target line according to the unit quality detection result of each unit section.

[0118] Among them, by combining the unit quality inspection results of each unit section, the track quality inspection results corresponding to the entire target line can be obtained.

[0119] Step S6: Obtain a segmented maintenance plan for the target line based on the unit quality level of each unit section included in the track quality inspection result.

[0120] The segmented maintenance plan may include maintenance strategy information for each unit section in the target line, and the maintenance strategy information may be determined according to the unit quality level corresponding to the unit section.

[0121] For example, for a unit section with a unit quality level of level 1, the corresponding maintenance strategy information may be to reasonably arrange preventive repairs at a first frequency to ensure the equipment is in good technical condition. For a unit section with a unit quality level of level 2, the corresponding maintenance strategy information may be to promptly remediate existing defects in the unit section, conduct condition surveys at a second frequency, and perform targeted maintenance to keep the equipment in good condition. For a unit section with a unit quality level of level 3, the corresponding maintenance strategy information may be to promptly remediate existing defects in the unit section, and conduct inspections and targeted maintenance at a third frequency. Here, the first frequency ≤ the second frequency ≤ the third frequency.

[0122] This embodiment breaks the traditional equal-length section management model used in railway maintenance and divides the target line into unit sections according to line type, enabling targeted analysis of the track quality of different types of line sections. By statistically analyzing the unit quality management index and unit quality degradation rate of each unit section, a targeted analysis of the overall quality and quality development trend of each unit section can be conducted. At the same time, in this embodiment, for each line type, the distribution of the unit quality management index and unit quality degradation rate of each corresponding unit section is statistically analyzed to determine the corresponding quality management index threshold and quality degradation rate threshold. This threshold is then used to divide the track quality grade of the unit sections of the corresponding line type. This allows for a targeted assessment of the track quality of the unit sections based on the quality characteristics of each line type, resulting in a more valuable unit quality test result. Moreover, in this embodiment, after obtaining the track quality inspection results of the target line, a segmented maintenance plan for the target line is obtained according to the unit quality grade of each unit section, which can realize segmented and graded management of the target line, and can reasonably arrange planned maintenance and temporary repairs within a shorter window time, effectively prevent and rectify line diseases and extend the service life of equipment, and can accurately match on-site operation and maintenance capabilities, improve effective operations and reduce repeated labor input, and realize high-precision inspection and efficient maintenance management of heavy-load railways.

[0123] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0124] Based on the same inventive concept, embodiments of the present application also provide a heavy-haul railway track quality testing device for implementing the aforementioned heavy-haul railway track quality testing method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the heavy-haul railway track quality testing device provided below can be found in the above-described limitations of the heavy-haul railway track quality testing method and will not be further elaborated here.

[0125] In an exemplary embodiment, Figure 5 As shown, a heavy-load railway track quality detection device 500 is provided, comprising:

[0126] The unit division module 501 is configured to divide the target line into unit sections corresponding to each line type according to the line type distribution information of the target line.

[0127] The quality statistics module 502 is configured to obtain a unit quality evaluation parameter of each unit segment based on the track detection data of each unit segment at multiple detection time points.

[0128] The unit detection module 503 is configured to obtain a unit quality detection result of each unit section according to the unit quality evaluation parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section.

[0129] The result acquisition module 504 is configured to obtain the track quality detection result of the target line according to the unit quality detection results of each unit section.

[0130] In an exemplary embodiment, the device further includes: a distribution statistics module for counting first distribution information of each unit quality assessment parameter corresponding to each line type according to the line type of each unit section; and a control parameter acquisition module for determining the type quality control parameter of each line type according to the first distribution information and first accumulation condition corresponding to each line type.

[0131] In an exemplary embodiment, the quality statistics module 502 is used to: calculate the unit quality index of the unit segment at each of the detection time points based on the track detection data of the unit segment at each of the detection time points; obtain the unit quality management index of the unit segment based on the second distribution information and second accumulation condition of each of the unit quality indexes of the unit segment; calculate the unit quality degradation rate of the unit segment based on the time change trend of each of the unit quality indexes; and construct the unit quality assessment parameters including the unit quality management index and the unit quality degradation rate.

[0132] In an exemplary embodiment, the quality statistics module 502 is used to: compare the unit quality management index of the unit section with the quality management index threshold in the type quality control parameter to obtain a first comparison result; compare the unit quality degradation rate of the unit section with the quality degradation rate threshold in the type quality control parameter to obtain a second comparison result; and obtain the unit quality detection result of the unit section based on the first comparison result and the second comparison result.

[0133] In an exemplary embodiment, the quality statistics module 502 is used to: obtain the unit quality level of the unit section based on the first comparison result and the second comparison result of the unit section; obtain the unit quality detection result based on the unit quality level; the device also includes: a plan acquisition module, used to obtain the segmented maintenance plan of the target line based on the unit quality level of each of the unit sections in the target line.

[0134] In an exemplary embodiment, the device further includes: a data acquisition module for acquiring initial track detection data and detection environment parameters of the unit section at multiple time points in a target period; and a data cleaning module for cleaning the initial track detection data according to the detection environment parameters to obtain the track detection data.

[0135] Each module in the heavy-haul railway track quality inspection device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0136] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data such as line type distribution information, track detection data, type quality control parameters, etc. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for detecting the quality of heavy-load railway tracks is implemented.

[0137] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0138] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0139] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0140] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0141] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0142] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0143] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0144] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A heavy-load railway track quality detection method, characterized in that: The method comprises: Dividing the target line into unit sections corresponding to each line type according to line type distribution information of the target line; Obtaining unit quality assessment parameters of each unit section based on track detection data of each unit section at multiple detection time points; Obtaining a unit quality detection result of each unit section according to the unit quality assessment parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section; According to the unit quality detection results of each unit section, the track quality detection result of the target line is obtained.

2. The method according to claim 1, characterized in that Before obtaining the unit quality detection result of each unit section according to the unit quality assessment parameter of each unit section and the type quality control parameter corresponding to the line type of the unit section, the method includes: For each of the line types, collecting statistics on first distribution information of the unit quality assessment parameter of each of the unit sections corresponding to the line type; The type quality control parameter of each line type is determined according to the first distribution information and the first accumulation condition corresponding to each line type.

3. The method according to claim 1 or 2, characterized in that The obtaining of unit quality assessment parameters of each unit section based on the track detection data of each unit section at multiple detection time points includes: Calculating a unit quality index of the unit segment at each of the detection time points based on the track detection data of the unit segment at each of the detection time points; Obtaining a unit quality management index of the unit section according to the second distribution information of each unit quality index of the unit section and a second accumulation condition; Calculating the unit quality degradation rate of the unit section according to the time variation trend of each unit quality index; The unit quality evaluation parameter including the unit quality management index and the unit quality degradation rate is constructed.

4. The method according to claim 3, characterized in that Obtaining a unit quality detection result of each unit section according to the unit quality assessment parameter and the type quality control parameter of each unit section includes: Comparing the unit quality management index of the unit segment with a quality management index threshold in the type quality control parameter to obtain a first comparison result; comparing the unit quality degradation rate of the unit segment with a quality degradation rate threshold in the type quality control parameter to obtain a second comparison result; The unit quality detection result of the unit section is obtained according to the first comparison result and the second comparison result.

5. The method according to claim 4, characterized in that Obtaining the unit quality detection result of the unit segment according to the first comparison result and the second comparison result includes: Obtaining a unit quality grade of the unit section according to the first comparison result and the second comparison result of the unit section; and obtaining the unit quality detection result according to the unit quality grade; After obtaining the track quality detection result of the target line according to the unit quality detection results of each unit section, the method further includes: A section maintenance plan for the target line is obtained according to the unit quality level of each unit section in the target line.

6. The method according to claim 1, characterized in that Before obtaining the unit quality assessment parameter of each unit section based on the track detection data of each unit section at multiple detection time points, the method includes: Acquiring initial track detection data and detection environment parameters of the unit section at multiple time points in a target period; The initial track detection data is cleaned according to the detection environment parameters to obtain the track detection data.

7. A heavy-load railway track quality detection device, characterized in that: The device comprises: a unit division module, configured to divide the target line into unit sections corresponding to each line type according to line type distribution information of the target line; a quality statistics module, configured to obtain a unit quality assessment parameter of each unit section based on the track detection data of each unit section at a plurality of detection time points; a unit detection module, configured to obtain a unit quality detection result of each unit section according to the unit quality evaluation parameter of each unit section and a type quality control parameter corresponding to the line type of the unit section; The result acquisition module is used to obtain the track quality detection result of the target line according to the unit quality detection result of each unit section.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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