Train operation analysis method, device and equipment, storage medium and computer program

Abstract

The invention relates to a train operation analysis method and device, equipment, a storage medium and a computer program. The method comprises the steps that train information is obtained, train yard relation information is analyzed, and train entry and exit information, a train type, a passing type and an operation direction are obtained; according to the train entering and exiting information, the train type, the passing type and the running direction, interval running time is obtained through calculation; based on preset influence factor types, analyzing the interval operation time to obtain average operation time corresponding to each preset influence factor type; and determining the influence degree of each preset influence factor type on the interval operation time according to the average operation time corresponding to each preset influence factor type. The interval operation time is obtained through calculation, the influence degree of the interval operation time is calculated in combination with the preset influence factor types, different factors of the influence degree of the interval operation time are accurately judged, and the transportation capacity can be improved by adjusting the influence factor types and optimizing the interval operation time.

Description

Technical Field

[0001] The present disclosure relates to the technical field of train operation analysis, and in particular to a train operation analysis method, device, equipment, storage medium and computer program. Background Art

[0002] In the field of freight railways, railway transportation production equipment is the material basis for the formation of railway transportation capacity, mainly including immovable fixed equipment (such as railway sections, stations, locomotive depots and other production facilities) and movable mobile equipment (such as locomotives, vehicles and other transport power and vehicles). Railway transportation capacity depends not only on the number of fixed equipment and their mutual configuration structure, but also on the spatial and temporal configuration of mobile equipment, and on the mutual adaptation of fixed equipment and mobile equipment. Therefore, there is currently a lack of reasonable means to comprehensively evaluate the train transportation capacity, and it is impossible to fully improve the train transportation capacity. Summary of the invention

[0003] The present disclosure provides a train operation analysis method, device, equipment, storage medium and computer program.

[0004] In a first aspect, the present disclosure provides a train operation analysis method, comprising:

[0005] Acquire train information, wherein the train information includes a train ID and train yard relationship information;

[0006] Parsing the train yard relationship information to obtain train entry and exit information, train type, passing type and running direction;

[0007] Calculate the interval running time according to the train entry and exit information, the train type, the passing type and the running direction;

[0008] Based on the preset influencing factor types, the interval running time is analyzed to obtain the average running time corresponding to each of the preset influencing factor types;

[0009] The influence of each of the preset influencing factor types on the interval running time is determined according to the average running time corresponding to each of the preset influencing factor types.

[0010] In one embodiment, the step of calculating the interval running time according to the train type, the passing type and the running direction comprises:

[0011] According to the train entry and exit information, the arrival time and departure time of each train group are obtained;

[0012] Based on the departure time of the previous train group and the arrival time of the next train group, the pre-processing time of the section operation is calculated;

[0013] Determining a corresponding additional correction time according to the train type, the running direction and the passing type;

[0014] The preprocessing time of the interval operation is corrected by using the additional correction time to obtain the interval operation time.

[0015] In one embodiment, the step of determining the influence of each of the preset influencing factor types on the interval running time according to the average running time corresponding to each of the preset influencing factor types includes:

[0016] The variance between the average running time corresponding to each of the preset influencing factor types and the standard running time is calculated to obtain the time variance, and the influence of each of the preset influencing factor types on the interval running time is determined according to each of the time variances.

[0017] In one embodiment, it also includes:

[0018] Obtaining locomotive information and train formation information, wherein the locomotive information includes train ID and locomotive traction uncoupling information, and the train formation information includes train ID and train load information;

[0019] Calculate the measured transport volume of each section and / or each track according to the locomotive traction uncoupling information and the train load information;

[0020] Detecting whether each of the transport volumes to be measured is greater than a preset transport volume threshold;

[0021] When the measured transport volume is greater than the preset transport volume threshold, an early warning message is issued.

[0022] In one embodiment, it also includes:

[0023] Associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data;

[0024] Based on preset screening rules, the associated data is screened to obtain screened data;

[0025] The step of parsing the train yard relationship information to obtain the train type, passing type and running direction includes:

[0026] Parsing the train yard relationship information in the screening data to obtain the train type, passing type and running direction;

[0027] The step of calculating the measured transport volume of each section and / or each track according to the locomotive traction uncoupling information and the train load information comprises:

[0028] The transport volume to be measured for each section and / or each track is calculated based on the locomotive traction and uncoupling information and train load information in the filtered data.

[0029] In one embodiment, the step of associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data includes:

[0030] Based on the same train ID, the train information, the locomotive information and the train formation information are associated to obtain the associated data.

[0031] In a second aspect, the present disclosure provides a train operation analysis device, comprising:

[0032] A train information acquisition module, used to acquire train information, wherein the train information includes a train ID and train yard relationship information;

[0033] A relationship information analysis module is used to analyze the train yard relationship information to obtain train entry and exit information, train type, passing type and running direction;

[0034] An interval running time calculation module is used to calculate the interval running time according to the train entry and exit information, the train type, the passing type and the running direction;

[0035] An average running time calculation module, used to analyze the interval running time based on preset influencing factor types, and obtain the average running time corresponding to each preset influencing factor type;

[0036] The influence degree determination module is used to determine the influence degree of each preset influence factor type on the interval running time according to the average running time corresponding to each preset influence factor type.

[0037] In a third aspect, the present disclosure provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above aspects.

[0038] In a fourth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the above aspects when executed by a processor.

[0039] In a fifth aspect, the present disclosure provides a computer program product, including a computer program, which implements the steps of the method described in the above aspects when executed by a processor.

[0040] The present disclosure provides a train operation analysis method, device, equipment, storage medium and computer program, which calculate the interval operation time through the train entry and exit information, train type, passing type and operation direction, that is, the operation time of each train between two adjacent yards, and calculate the influence degree of the interval operation time in combination with the preset influencing factor type, so as to accurately judge the different factors affecting the interval operation time. In this way, the interval operation time can be optimized by adjusting the proportion or quantity of each influencing factor type, thereby improving the transportation capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0042] Figure 1 A flow chart of a train operation analysis method provided by an embodiment of the present disclosure;

[0043] Figure 2 A flow chart of a train operation analysis method provided in accordance with another embodiment of the present disclosure.

[0044] In the drawings, the same reference numerals are used for the same components, and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0046] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0047] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0048] Embodiment 1

[0049] Figure 1 The following is a flow chart of a train operation analysis method provided by an embodiment of the present disclosure. Figure 1 As shown, a train operation analysis method includes:

[0050] Step 110, obtaining train information, wherein the train information includes a train ID and train yard relationship information.

[0051] In this embodiment, the train information includes data such as train ID, yard ID, yard sequence, actual departure time at the yard, actual arrival time at the yard, and pass type, among which the train ID is the unique identification mark of the train, which is used to distinguish different trains, and the yard ID is the unique identification mark of the yard, which is used to distinguish different yards. The yard sequence is the order of the yards along the direction of the train's travel, the actual departure time at the yard is the time when the train departs from the yard, the actual arrival time at the yard is the time when the train arrives at the yard, and the pass type is the type of train passing through the yard, including: "arrival", "handover", "temporary stop", "final arrival", "origin", "access", and "arrival". In this embodiment, the yard ID, yard sequence, actual departure time at the yard, actual arrival time at the yard, and pass type all belong to the train yard relationship, reflecting the relationship between the train and the yard.

[0052] In this embodiment, the train timetable is queried, and the train timetable records the actual operation data of a train in each yard, and obtains data including train ID, yard ID, yard sequence, actual departure and actual arrival time at the yard, and pass type.

[0053] Step 120, parse the train yard relationship information to obtain train entry and exit information, train type, passing type and running direction.

[0054] In this embodiment, the train yard relationship information records the yard ID, yard sequence, actual departure time at the yard, actual arrival time at the yard, pass type and other data. The train entry and exit information includes the actual departure time of the train at the yard and the actual arrival time at the yard. The train types include unit trains, 10,000-ton trains and 16,000-ton trains. The pass types include: "arrival and departure", "handover", "temporary stop", "final arrival", "origin", "access", "arrival and departure", and the running direction includes the upward direction and the downward direction. For example, from yard A to yard B is the upward direction, and from yard B to yard A is the downward direction.

[0055] Step 130, calculating the interval running time according to the train entry and exit information, the train type, the passing type and the running direction.

[0056] In this embodiment, the train entry and exit information records the arrival time and departure time of the train at the yard, while the train type determines the stay time in the yard, and the pass type determines the way of arriving at and leaving the yard. In this way, the arrival time and departure time of the train, combined with the stay time and pass type corresponding to the train type, can be calculated to obtain the interval running time, which is the arrival time at the yard with the later sequence minus the departure time at the yard with the earlier sequence.

[0057] Step 140: Analyze the interval running time based on the preset influencing factor types to obtain the average running time corresponding to each of the preset influencing factor types.

[0058] In this embodiment, the preset influencing factor type is the type of factor that will affect the interval running time and cause the interval running time to change, for example, including: load type, driver and passenger type, locomotive traction type. In this embodiment, the interval running time corresponding to the load type, driver and passenger type, and locomotive traction type is analyzed respectively to obtain the average running time corresponding to the load type, driver and passenger type, and locomotive traction type.

[0059] Step 150: Determine the influence of each of the preset influencing factor types on the interval running time according to the average running time corresponding to each of the preset influencing factor types.

[0060] In this embodiment, each of the preset influencing factor types will have an impact on the interval running time. A large impact factor has a large impact on the interval running time, resulting in a large deviation in the average running time. A small impact factor has a small impact on the interval running time, resulting in a small deviation in the average running time. In this embodiment, the impact of the load type, the driver type, and the locomotive traction type on the interval running time is determined based on the average running time corresponding to the load type, the driver type, and the locomotive traction type.

[0061] In this embodiment, the influence of load type, driver and passenger type, and locomotive traction type on the section running time can be reflected from the average running time corresponding to the load type, driver and passenger type, and locomotive traction type. Therefore, the influence of load type, driver and passenger type, and locomotive traction type on the section running time can be determined through the average running time corresponding to the load type, driver and passenger type, and locomotive traction type.

[0062] In the above embodiment, the interval running time is calculated by using the train entry and exit information, train type, passing type and running direction, that is, the running time of each train between two adjacent yards is obtained, and the influence degree of the interval running time is calculated in combination with the preset influencing factor type, so as to accurately judge the different factors affecting the interval running time. In this way, the interval running time can be optimized by adjusting the proportion or quantity of each influencing factor type, thereby improving the transportation capacity.

[0063] Embodiment 2

[0064] Based on the above embodiment, the step of calculating the interval running time according to the train type, the passing type and the running direction in this embodiment includes:

[0065] According to the train entry and exit information, the arrival time and departure time of each train group are obtained;

[0066] Based on the departure time of the previous train group and the arrival time of the next train group, the pre-processing time of the section operation is calculated;

[0067] Determining a corresponding additional correction time according to the train type, the running direction and the passing type;

[0068] The preprocessing time of the interval operation is corrected by using the additional correction time to obtain the interval operation time.

[0069] In this embodiment, after obtaining the arrival time and departure time of each train group at the yard, according to the yard order, the arrival time of the next train group is subtracted from the triggering yard time of the previous train group, that is, the arrival time of the yard with the later yard order is subtracted from the departure time of the yard with the earlier order as the preprocessing time of this section operation, and then different train types, different sections and different up and down directions have different additional departure and arrival times. These times are determined by the station.

[0070] Specifically, the train table records the train number and train type, including unit trains, 10,000-ton trains and 16,000-ton trains. The interval table records the up and down directions of the interval. For example, from yard A to yard B is up, and from yard B to yard A is down. The additional correction time includes additional arrival time and additional departure time. The specific process is: the yard passing type in the latter sequence is not "through", such as "arrival and departure", "handover", "temporary stop", "final arrival", etc., and the additional arrival time needs to be subtracted from the processing operation time according to the train type and the up and down directions. The yard passing type in the former sequence is not "through", such as "originating", "access", "arrival and departure", etc., and the additional departure time needs to be subtracted according to the train type and the up and down directions. The running time obtained by the preprocessing time processed by the above steps is the interval running time. In this way, by correcting the preprocessing time with the additional correction time, a more accurate interval running time can be obtained.

[0071] Embodiment 3

[0072] On the basis of the above embodiment, the step of determining the influence of each of the preset influencing factor types on the interval running time according to the average running time corresponding to each of the preset influencing factor types in this embodiment includes:

[0073] The variance between the average running time corresponding to each of the preset influencing factor types and the standard running time is calculated to obtain the time variance, and the influence of each of the preset influencing factor types on the interval running time is determined according to each of the time variances.

[0074] In this embodiment, the through time refers to the time it takes for a train to pass through two adjacent stations. In this embodiment, in order to determine the influence of each preset influencing factor type on the interval running time, the standard through time and the average running time are used to calculate the variance, and the time variance corresponding to each preset influencing factor type is obtained. According to each time variance, it is determined which preset influencing factor type has a greater influence on the interval running time.

[0075] For example, a coordinate system is established with the load type, driver type, locomotive traction type and the corresponding average running time of the three, where different load types, different driver types, and different locomotive traction types are used as the horizontal coordinates, and the corresponding average running time is used as the vertical coordinate. The standard pass time is inserted into the scatter plot as a horizontal straight line, and the outliers with a large difference between the scatter points and the straight line are marked. Among them, each scatter point is the average running time corresponding to the load type, driver type, and locomotive traction type. The distance between the scatter points and the standard pass time reflects the variance. The larger the distance, the larger the variance. Therefore, it can be seen which preset influencing factor type has a greater impact on the interval running time.

[0076] Embodiment 4

[0077] On the basis of the above embodiment, in this embodiment, the method further includes:

[0078] Obtaining locomotive information and train formation information, wherein the locomotive information includes train ID and locomotive traction uncoupling information, and the train formation information includes train ID and train load information;

[0079] Calculate the measured transport volume of each section and / or each track according to the locomotive traction uncoupling information and the train load information;

[0080] Detecting whether each of the transport volumes to be measured is greater than a preset transport volume threshold;

[0081] When the measured transport volume is greater than the preset transport volume threshold, an early warning message is issued.

[0082] In this embodiment, the locomotive operation table is queried, and the locomotive operation table records the locomotive detachment data. By querying the locomotive operation table, data including locomotive ID, train ID, locomotive number, locomotive model, traction type, locomotive attachment time, locomotive detachment time, etc. are obtained, wherein the locomotive model, traction type, locomotive attachment time, and locomotive detachment time are locomotive traction detachment information; the train arrival marshaling main table is queried to obtain data including train ID, marshaling ID, yard ID, track, station reporting time, track on which the train is running, number of trains, load, dead weight, etc., so as to obtain the train arrival marshaling information; the train departure marshaling main table is queried to obtain data including train ID, marshaling ID, yard ID, track, station reporting time, track on which the train is running, number of trains, load, dead weight, etc., so as to obtain the train departure marshaling information; the train arrival marshaling sub-table is queried to obtain the marshaling ID, car code, the order of cars in a train, load, etc. Among them, the train load information includes the track on which it runs, the number of trains, the load, the dead weight, the car code, the order of the cars in a train, the load, etc.

[0083] In this embodiment, the departure marshaling information with the yard sequence in front and the arrival marshaling information with the yard sequence in the back of a train traveling in each section are calculated. The transportation volume of a train in this section can be calculated based on the load corresponding to the arrival marshaling information. The transportation volume of this section is obtained by accumulating the transportation volume of each train passing through the section, that is, the transportation volume to be measured is obtained.

[0084] From the train marshaling information, the departure marshaling information and arrival marshaling information of each train at a certain yard are obtained. If the yard is the initial station, there is only departure marshaling information. If the yard is the final station, there is only arrival marshaling information. If a piece of data contains departure marshaling information, the track name and load in the departure marshaling are recorded. If a piece of data contains arrival marshaling information, the track name and load in the arrival marshaling are recorded. The loads of the same track in different intervals are accumulated to obtain the measured transport volume of each track.

[0085] Check whether the measured traffic volume of each section and each track is greater than the preset traffic volume threshold. If the measured traffic volume is greater than the preset traffic volume threshold, issue a warning message to the track or section. By issuing a warning message, guide relevant staff to perform operations such as track maintenance or track replacement. When the threshold is reached, the result is cleared and the total amount is accumulated again.

[0086] Embodiment 5

[0087] Based on the above embodiment, in this embodiment, the method further includes:

[0088] Associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data;

[0089] Based on preset screening rules, the associated data is screened to obtain screened data;

[0090] The step of parsing the train yard relationship information to obtain the train type, passing type and running direction includes:

[0091] Parsing the train yard relationship information in the screening data to obtain the train type, passing type and running direction;

[0092] The step of calculating the measured transport volume of each section and / or each track according to the locomotive traction uncoupling information and the train load information comprises:

[0093] The transport volume to be measured for each section and / or each track is calculated based on the locomotive traction and uncoupling information and train load information in the filtered data.

[0094] In this embodiment, by associating train information, locomotive information and train formation information, more comprehensive data can be obtained. The associated data can be screened by preset selection rules to obtain more effective data.

[0095] For example, filtering out skylight data can effectively improve the accuracy of data. Specifically, skylights affect the accuracy of statistical data, so data on the day with a skylight is not counted. At the end of each month, the skylight plan for the next month is obtained. Based on the associated data, it is possible to query which day and time period has a skylight, and filter out all data on dates with skylights from the associated table to obtain filtered data.

[0096] For example, when processing interval operations: if it is an interval-starting operation, filter out the current data and the next data; if it is an interval-returning operation, filter out the current data, the previous data, and the next data; if it is an interval-opening operation, filter out the current data and the next data.

[0097] In addition, after the train information, locomotive information and train marshaling information are associated, it can be beneficial to query and obtain data. For example, the associated data after filtering is parsed, and the train type, passing type and running direction are queried from the filtered associated data; for example, the locomotive traction uncoupling information and train load information are obtained from the filtered associated data, and the measured transportation volume of each section and / or each track is calculated based on the locomotive traction uncoupling information and train load information. For example, the IDs of two adjacent yards in the same group in the associated data are matched with the two yard IDs of the section, and the departure marshaling information of a train running in this section with the yard sequence in the front and the arrival marshaling information with the yard sequence in the back are obtained; for example, each piece of data in the associated data contains the departure marshaling information and arrival marshaling information of a train at a certain yard, thereby obtaining the departure marshaling information and arrival marshaling information of each train at a certain yard.

[0098] It is worth mentioning that, in some embodiments, the associated data may also be referred to as an associated table.

[0099] Embodiment 6

[0100] On the basis of the above embodiment, in this embodiment, the step of associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data includes:

[0101] Based on the same train ID, the train information, the locomotive information and the train formation information are associated to obtain the associated data.

[0102] In order to associate the train information, locomotive information and train formation information, in this embodiment, the train information, locomotive information and train formation information corresponding to the same train ID are associated to form associated data.

[0103] Embodiment 7

[0104] Based on the above embodiments, this embodiment provides an application example. Figure 2 .

[0105] 1. Collect information on actual train operations, actual locomotive operation, train departure / arrival formations, and cargo

[0106] 1. Query the train timetable. The train timetable records the actual operation data of a train in each yard, and obtains data including train ID, yard ID, yard sequence, actual departure and arrival time at the yard, and pass type.

[0107] 2. Query the locomotive operation table. The locomotive operation table records the locomotive's coupling and uncoupling data, and obtains data including locomotive ID, train ID, locomotive number, locomotive model, traction type, locomotive coupling time, locomotive uncoupling time, etc.

[0108] 3. Query the train arrival marshaling master table to obtain data including train ID, marshaling ID, yard ID, track, station reporting time, track on which it runs, number of trains, load, deadweight, etc., so as to obtain train arrival marshaling information.

[0109] 4. Query the train departure marshaling main table to obtain data including train ID, marshaling ID, yard ID, track, station reporting time, track on which it runs, number of trains, load, deadweight, etc., so as to obtain the train departure marshaling information.

[0110] 5. Query the train arrival marshaling subtable to obtain information such as marshaling ID, car code, car sequence in a train, and load.

[0111] 2. Associate train, locomotive, marshaling and other information through train ID, yard and time

[0112] By associating the train schedule, locomotive operation table, arrival marshaling master table and departure marshaling master table through train ID, yard and time, we can get the operation information of a train and its locomotive, marshaling and cargo information. The resulting table is called an association table.

[0113] 3. Filtering data in related tables

[0114] 1. Group and sort the associated tables

[0115] 1.1. Group the association table according to the train id.

[0116] 1.2. The parking lot order is determined by the parking lot location. Adjacent parking lots are adjacent in order. Each set of data obtained above is sorted according to the parking lot order.

[0117] 1.3. Then filter the data by departure and arrival time from 18:00 the previous day to 18:00 the current day.

[0118] Through the above operation, you can know the departure and arrival time of each train at different yards on a line on that day.

[0119] 2. Handling of interval operations

[0120] 2.1. If it is an interval-initiated operation, filter out this data and the next data.

[0121] 2.2. If it is an interval return job, filter out the current data, the previous data, and the next data.

[0122] 2.3. If it is an interval-to-open operation, filter out this data and the next data.

[0123] 2.4. If it is an interval end operation, filter out this data and the previous data.

[0124] 3. Dealing with skylights

[0125] Skylights will affect the accuracy of statistical data, so data on the day with skylights will not be counted.

[0126] At the end of each month, we will get the skylight plan for the next month. Based on this plan, we can query which day and time period has skylights. The associated table filters out the data of all dates with skylights.

[0127] 4. For two adjacent data in the same group, the arrival time of the parking lot in the later order minus the departure time of the parking lot in the earlier order is the preprocessing time of the operation of this interval.

[0128] Different train types, different sections and different up and down directions have different extra departure and arrival times. These times are determined by the station. To get the exact time, you need to subtract the extra departure and arrival time from the pre-processing time according to the situation. The specific operation is as follows:

[0129] 1. The train table records the train number and train type. The train types include unit trains, 10,000-ton trains and 16,000-ton trains. The associated data is classified by train type by linking the train table with the associated table.

[0130] 2. The interval table records the up and down directions of the interval. From yard A to yard B is up, and from yard B to yard A is down. By connecting the interval table and the association table, the trains are classified according to the interval direction.

[0131] 3. Query the train passing type in the association table, and then classify the trains according to the passing type.

[0132] 4. If the passing type of the yard in the later sequence is not "pass", such as "arrival and departure", "handover", "temporary stop", "final arrival", etc., the extra arrival time needs to be subtracted from the pending running time according to the train type and the up and down directions. If the passing type of the yard in the earlier sequence is not "pass", such as "originating", "access", "arrival and departure", etc., the extra departure time needs to be subtracted according to the train type and the up and down directions.

[0133] 5. The running time obtained by the preprocessing time processed by the above steps is the final accurate time.

[0134] 5. Consider off-plane parking

[0135] The situation of off-board parking will not be reflected in the timetable, so we have set it so that if the calculated running time of a certain section exceeds 1.3 times the total time specified by the station, this data will not be recorded.

[0136] 6. Calculate the interval volume, track cumulative volume, and total empty and loaded vehicles, and issue track change warnings based on the cumulative volume

[0137] 1. Calculate the volume of a certain section

[0138] 1.1. Match the IDs of two adjacent yards in the same group in the association table with the two yard IDs of the section, and obtain the departure marshaling information with the yard sequence in the front and the arrival marshaling information with the yard sequence in the back of a train running in this section.

[0139] 1.2. The train's transport volume in this section can be obtained through the load in the arrival marshaling information.

[0140] 1.3. Add up the traffic volume of each train passing through the section to get the traffic volume of the section.

[0141] 2. Calculate the cumulative volume of the track

[0142] 2.1. Each data in the association table contains the departure marshaling information and arrival marshaling information of a train at a certain yard. If the yard is the initial station, there is only the departure marshaling information; if the yard is the final station, there is only the arrival marshaling information.

[0143] 2.2. If a data contains departure marshaling information, the track name and load in the departure marshaling are recorded. If a data contains arrival marshaling information, the track name and load in the arrival marshaling are recorded.

[0144] 2.3. For different tracks in different intervals, add up the results to get the transport volume of different tracks in different intervals.

[0145] 2.4. Count the total volume of each track. When the total volume reaches a certain threshold, issue an early warning and instruct relevant staff to inspect or replace the track. When the threshold is reached, clear the result and re-accumulate the total volume.

[0146] 3. Calculate the total number of empty and loaded vehicles

[0147] 3.1. Match the IDs of the two adjacent yards in the same group in the association table with the two yard IDs of the section, and obtain the departure marshaling information with the yard sequence in the front and the arrival marshaling information with the yard sequence in the back of a train running in this section.

[0148] 3.2. By matching the marshaling ID in the marshaling information of the later arriving marshaling in the yard sequence with the marshaling ID in the arrival marshaling subtable, the number of empty and loaded cars in a train passing through this section can be obtained.

[0149] 3.3. Add up the number of empty and loaded cars of each train passing through the section to get the number of empty and loaded cars in the section.

[0150] 7. Create a new record table to import statistical data

[0151] 1. Create a new record table and regularly store the total number of train runs of different types of trains in different up and down directions in each section that you want to count from 18:00 the previous day to 18:00 the current day, the total time, maximum, minimum time, average time, total transport volume, and the number of empty and loaded trains passing through.

[0152] 2. Create a new record table and regularly store the total volume of different tracks in different sections from 18:00 the previous day to 18:00 the current day.

[0153] If the departure time is before 18:00 on the same day, and the arrival at the next parking lot is after 18:00 on the same day, these data are also stored according to the date of the day.

[0154] 8. Analyze the factors affecting the interval running time from multiple dimensions such as load type, driver and passenger, and locomotive traction type

[0155] 1. The operating time of a certain section of the day is counted separately according to the heavy load type (unit, 10,000 tons).

[0156] 2. The running time of a certain section of the day is counted separately according to the locomotive traction type.

[0157] 3. The running time of a certain section of the day is counted separately by drivers and passengers.

[0158] 4. Calculate the variance of the average running time and the standard running time of the sections with different heavy load types, different locomotive traction types, and different drivers and passengers, and determine which factor has the greatest impact on the section running time.

[0159] 5. Create three xy scatter plots, with the horizontal axis representing different heavy load types, different locomotive traction types, and driver and passenger names, and the vertical axis representing the average interval running time. Insert the total time as a horizontal line into the scatter plot, and mark the outliers that differ greatly from the straight line.

[0160] Embodiment 8

[0161] In this embodiment, a train operation analysis device is provided, including:

[0162] A train information acquisition module, used to acquire train information, wherein the train information includes a train ID and train yard relationship information;

[0163] A relationship information analysis module is used to analyze the train yard relationship information to obtain train entry and exit information, train type, passing type and running direction;

[0164] An interval running time calculation module is used to calculate the interval running time according to the train entry and exit information, the train type, the passing type and the running direction;

[0165] An average running time calculation module, used to analyze the interval running time based on preset influencing factor types, and obtain the average running time corresponding to each preset influencing factor type;

[0166] The influence degree determination module is used to determine the influence degree of each preset influence factor type on the interval running time according to the average running time corresponding to each preset influence factor type.

[0167] In one embodiment, the interval running time calculation module includes:

[0168] An arrival and departure time acquisition unit, used to acquire the arrival and departure time of each train group according to the train entry and exit information;

[0169] A preprocessing time calculation unit, used to calculate the preprocessing time of the section operation based on the departure time of the previous train group and the arrival time of the next train group;

[0170] an additional correction time determination unit, configured to determine a corresponding additional correction time according to the train type, the running direction and the passing type;

[0171] The correction unit is used to correct the preprocessing time of the interval operation by using the additional correction time to obtain the interval operation time.

[0172] In one embodiment, the impact determination module is also used to calculate the variance between the average running time corresponding to each of the preset influencing factor types and the standard running time to obtain the time variance, and determine the impact of each of the preset influencing factor types on the interval running time based on each of the time variances.

[0173] In one embodiment, the apparatus further comprises:

[0174] A locomotive and train formation information acquisition module, used to acquire locomotive information and train formation information, wherein the locomotive information includes train ID and locomotive traction uncoupling information, and the train formation information includes train ID and train load information;

[0175] A module for calculating the amount of traffic to be measured, used to calculate the amount of traffic to be measured for each section and / or each track according to the locomotive traction uncoupling information and the train load information;

[0176] A transport volume detection module, used to detect whether each of the transport volumes to be measured is greater than a preset transport volume threshold;

[0177] The early warning module is used to issue an early warning message when the measured transportation volume is greater than the preset transportation volume threshold.

[0178] In one embodiment, the apparatus further comprises:

[0179] An association module, used for associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data;

[0180] A screening module, used to screen the associated data based on preset screening rules to obtain screened data;

[0181] The relationship information parsing module is also used to parse the train yard relationship information in the screening data to obtain the train type, passing type and running direction;

[0182] The module for calculating the volume to be measured is also used to calculate the volume to be measured for each section and / or each track based on the locomotive traction and uncoupling information and train load information in the screening data.

[0183] In one embodiment, the association module is further used to associate the train information, the locomotive information and the train formation information based on the same train ID to obtain the association data.

[0184] Embodiment 9

[0185] On the basis of the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0186] In some implementations of this 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 of the method described in the above embodiment are implemented.

[0187] In some implementations of this embodiment, a computer program product is provided, including a computer program, which implements the steps of the method described in the above embodiment when executed by a processor.

[0188] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components to execute the method in the above embodiments.

[0189] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (such as hard disks, floppy disks, solid-state drives, removable disks, Blu-ray disks, etc.).

[0190] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0191] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.), etc.

[0192] The processor may communicate with external devices via an I / O bus via a wired or wireless network.

[0193] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0194] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0195] It should be noted that in the present disclosure, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element limited by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0196] Although the embodiments disclosed in the present disclosure are as above, the above contents are only embodiments adopted for facilitating the understanding of the present disclosure and are not intended to limit the present disclosure. Any technician in the technical field to which the present disclosure belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present disclosure, but the scope of patent protection of the present disclosure shall still be subject to the scope defined in the attached claims.

Claims

1. A train operation analysis method, characterized in that: include: Acquire train information, wherein the train information includes a train ID and train yard relationship information; Parsing the train yard relationship information to obtain train entry and exit information, train type, passing type and running direction; Calculate the interval running time according to the train entry and exit information, the train type, the passing type and the running direction; Based on the preset influencing factor types, the interval running time is analyzed to obtain the average running time corresponding to each of the preset influencing factor types; The influence of each of the preset influencing factor types on the interval running time is determined according to the average running time corresponding to each of the preset influencing factor types.

2. The method according to claim 1, characterized in that The step of calculating the interval running time according to the train type, the passing type and the running direction comprises: According to the train entry and exit information, the arrival time and departure time of each train group are obtained; Based on the departure time of the previous train group and the arrival time of the next train group, the pre-processing time of the section operation is calculated; Determining a corresponding additional correction time according to the train type, the running direction and the passing type; The preprocessing time of the interval operation is corrected by using the additional correction time to obtain the interval operation time.

3. The method according to claim 1, characterized in that The step of determining the influence of each of the preset influencing factor types on the interval running time according to the average running time corresponding to each of the preset influencing factor types comprises: The variance between the average running time corresponding to each of the preset influencing factor types and the standard running time is calculated to obtain the time variance, and the influence of each of the preset influencing factor types on the interval running time is determined according to each of the time variances.

4. The method according to claim 1, characterized in that: Also includes: Obtaining locomotive information and train formation information, wherein the locomotive information includes train ID and locomotive traction uncoupling information, and the train formation information includes train ID and train load information; Calculate the measured transport volume of each section and / or each track according to the locomotive traction uncoupling information and the train load information; Detecting whether each of the transport volumes to be measured is greater than a preset transport volume threshold; When the measured transport volume is greater than the preset transport volume threshold, an early warning message is issued.

5. The method according to claim 4, characterized in that Also includes: Associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data; Based on preset screening rules, the associated data is screened to obtain screened data; The step of parsing the train yard relationship information to obtain the train type, passing type and running direction includes: Parsing the train yard relationship information in the screening data to obtain the train type, passing type and running direction; The step of calculating the measured transport volume of each section and / or each track according to the locomotive traction uncoupling information and the train load information comprises: The transport volume to be measured for each section and / or each track is calculated based on the locomotive traction and uncoupling information and train load information in the filtered data.

6. The method according to claim 5, characterized in that The step of associating the train information, the locomotive information and the train formation information based on a preset association rule to obtain associated data comprises: Based on the same train ID, the train information, the locomotive information and the train formation information are associated to obtain the associated data.

7. A train operation analysis device, characterized in that: include: A train information acquisition module, used to acquire train information, wherein the train information includes a train ID and train yard relationship information; A relationship information analysis module is used to analyze the train yard relationship information to obtain train entry and exit information, train type, passing type and running direction; An interval running time calculation module is used to calculate the interval running time according to the train entry and exit information, the train type, the passing type and the running direction; An average running time calculation module, used to analyze the interval running time based on preset influencing factor types, and obtain the average running time corresponding to each preset influencing factor type; The influence degree determination module is used to determine the influence degree of each preset influence factor type on the interval running time according to the average running time corresponding to each preset influence factor type.

8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

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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