Calculation method, device and system for train mileage and storage medium

Abstract

The embodiment of the invention provides a calculation method, device and system for train mileage and a storage medium, and relates to the technical field of rail transit data processing. The method comprises the steps that the speed of a train is determined according to multiple speed source signals of the train; and determining the mileage of the train according to the speed of the train. The train speed is comprehensively determined by utilizing the multiple speed source signals, and the introduction of the multiple speed source signals can avoid speed calculation deviation caused by abnormity of a single speed source or single dependence on a preset wheel diameter, so that the determined train speed is more accurate and reliable. Mileage calculation is carried out based on the more accurate and reliable train speed, and mileage calculation errors caused by speed deviation can be reduced, so that the overall accuracy of train mileage calculation is improved, and the requirement of urban rail trains for high precision of mileage data is met; and reliable data support is provided for subsequently formulating a reasonable journey repairing arrangement based on the mileage data, guaranteeing the running safety of the train and prolonging the service life of the train.

Description

Technical Field

[0001] This application relates to the field of rail transit data processing technology, specifically to a method, apparatus, system, and storage medium for calculating train mileage. Background Technology

[0002] Currently, the operating mileage of urban rail trains is one of the key indicators for determining train maintenance schedules, ensuring operational safety, and extending their service life. To ensure trains are in good operating condition, accurate mileage data is essential for developing maintenance plans. However, in practice, due to factors such as mechanical component wear and sensor errors, relying solely on a single data source for mileage statistics often fails to meet accuracy requirements, thus affecting the effectiveness of maintenance decisions.

[0003] To address the aforementioned issues, existing technologies typically employ a mechanical odometer installed in the train driver's cab, accumulating mileage by combining preset wheel diameters with axle speed signals. This method provides a rough estimate of train travel distance, offering basic data support for daily maintenance. Furthermore, some solutions predict mileage by analyzing daily train operation patterns or utilize time-sensitive networks to synchronize data between primary and backup equipment, thereby improving data availability.

[0004] In the process of implementing the embodiments of this application, at least the following problems were found in the related technology: Relying on a single axle speed signal and preset wheel diameter for speed and mileage calculation, when the preset wheel diameter is not updated in time or the axle speed sensor malfunctions, it is impossible to correct the calculation process with other effective speed signals, resulting in deviations in train speed determination and consequently, large errors in mileage calculation, making it difficult to meet the actual requirements of urban rail trains for high-precision mileage data. Summary of the Invention

[0005] This application provides a method, apparatus, system, and storage medium for calculating train mileage.

[0006] The first aspect of this application provides a method for calculating train mileage, comprising: The train speed is determined based on multiple speed source signals. The train's mileage is determined based on its speed.

[0007] In an optional embodiment of this application, determining the train speed based on multiple speed source signals includes: Perform validity filtering operations on multiple speed source signals of the train in a set order to obtain at least one valid speed; The train speed is determined based on at least one valid speed.

[0008] In an optional embodiment of this application, a validity screening operation is performed on multiple speed source signals of the train in a predetermined order to obtain at least one valid speed, including: Determine the target sequence for performing validity screening operations on multiple speed source signals of the train; Perform validity filtering operations on each velocity source signal in the order of the targets; When at least one valid value exists in the target velocity source signal being screened, the validity screening operation is stopped, and the valid value of the target velocity source signal is selected as the valid velocity.

[0009] In an optional embodiment of this application, the target sequence from front to back includes the drag shaft speed of braking feedback, the moving shaft speed of braking feedback, and the moving shaft speed of traction feedback.

[0010] In one optional embodiment of this application, the multiple speed sources of the train include the drag shaft speed of braking feedback, the moving shaft speed of braking feedback, and / or the moving shaft speed of traction feedback.

[0011] In an optional embodiment of this application, determining the train's mileage based on the train's speed includes: Based on the train's speed and the corresponding task scheduling cycle, mileage accumulation calculation is performed to obtain the cumulative mileage and small mileage data that is less than the set mileage. The system stores the cumulative mileage and short mileage data, and reads the stored data when the system is powered on to continue the mileage accumulation calculation.

[0012] In an optional embodiment of this application, performing mileage accumulation calculation includes: Calculate the displacement of the train within the corresponding task scheduling cycle based on the train's speed and the cycle time of the corresponding task scheduling cycle. The displacement is accumulated into the current small mileage data to obtain the accumulated small mileage data; Determine whether the accumulated mileage data is greater than or equal to the set mileage; When the accumulated mileage data is greater than or equal to the set mileage, the current accumulated mileage will be increased by the set mileage multiplier, and the accumulated mileage data will be subtracted from the set mileage multiplier.

[0013] A second aspect of this application provides a train mileage calculation device, including a processor and a memory storing program instructions, wherein the processor is configured to execute the train mileage calculation method as described in the first aspect of this application when running the program instructions.

[0014] A third aspect of this application provides a system comprising: The system itself; and, The train mileage calculation device, as described in the second aspect of the embodiments of this application, is installed on the system body.

[0015] A fourth aspect of the present application provides a computer-readable storage medium storing program instructions that, when executed, cause a computer to perform a method for calculating train mileage as described in the first aspect of the present application.

[0016] The method, apparatus, system, and storage medium for calculating train mileage provided in the embodiments of this application have the following beneficial effects: This application embodiment utilizes multiple speed source signals to comprehensively determine train speed. The introduction of multiple speed source signals avoids speed calculation deviations caused by anomalies in a single speed source or reliance solely on a preset wheel diameter, resulting in more accurate and reliable determined train speeds. Based on this more accurate and reliable train speed, mileage calculation can reduce mileage calculation errors caused by speed deviations, thereby improving the overall accuracy of train mileage calculation. This meets the high-precision mileage data requirements of urban rail trains and provides reliable data support for subsequent reasonable maintenance schedules based on mileage data, ensuring train operation safety, and extending train service life. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of a method for calculating train mileage provided in an embodiment of this application; Figure 2 This is a schematic diagram of a train mileage calculation device provided in an embodiment of this application.

[0018] Figure label: 800: Calculation device for train mileage; 801: Processor; 802: Memory; 803: Communication interface; 804: Bus. Detailed Implementation

[0019] To make the technical solutions and advantages of the embodiments of this application clearer, the exemplary embodiments of this application will be described in further detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not an exhaustive list of all embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0020] This application discloses a train mileage calculation system, comprising: multiple speed sensors for collecting train speed signals; a train central control unit for executing any of the following methods for calculating train mileage; a non-volatile memory for storing cumulative mileage and short mileage data; and a human-machine interface device for receiving mileage setting commands input by the user. The train central control unit can be configured with master-slave redundancy, and the two units synchronize data via a network.

[0021] Figure 1 This is a schematic diagram of a method for calculating train mileage provided in an embodiment of this application. Any of the following methods can be executed in the system, or in a server or terminal device or train central control unit that is connected to the system.

[0022] Based on the above-mentioned train mileage calculation system, such as Figure 1 As shown in the embodiment of this application, a method for calculating train mileage is provided, including: S01 determines the train speed based on multiple speed source signals.

[0023] S02, determine the train's mileage based on the train's speed.

[0024] The train mileage calculation method provided in this application utilizes multiple speed source signals to comprehensively determine the train speed. The introduction of multiple speed source signals avoids speed calculation deviations caused by anomalies in a single speed source or reliance on a single preset wheel diameter, resulting in a more accurate and reliable determined train speed. Mileage calculation based on this more accurate and reliable train speed reduces mileage calculation errors caused by speed deviations, thereby improving the overall accuracy of train mileage calculation. This meets the high-precision mileage data requirements of urban rail trains and provides reliable data support for subsequent reasonable maintenance schedules based on mileage data, ensuring train operation safety, and extending train service life.

[0025] In an optional embodiment of this application, determining the speed of a train based on multiple speed source signals includes: performing a validity screening operation on the multiple speed source signals of the train in a set order to obtain at least one valid speed; and determining the speed of the train based on the at least one valid speed.

[0026] In this embodiment of the application, performing the validity screening operation includes judging the numerical validity of each speed source signal. The judgment criteria include whether the signal value is within the reasonable speed range that the train can run at, or whether the signal is provided by a valid sensor.

[0027] By performing the validity screening operation in a predetermined order, the various speed source signals can be systematically checked, avoiding the inefficiency or omission of valid signals that may result from disordered screening. This makes it easier to reliably obtain at least one valid speed. Determining the train speed based on at least one valid speed obtained through screening, compared to calculating the speed based on a single speed source signal, reduces the impact of a single abnormal speed data point on the final speed result, making the determined train speed more accurate and reliable.

[0028] In an optional embodiment of this application, performing validity screening operations on multiple speed source signals of a train in a predetermined order to obtain at least one valid speed includes: determining a target order for performing validity screening operations on multiple speed source signals of a train; performing validity screening operations on each speed source signal in the target order; stopping the validity screening operation when the currently screened target speed source signal has at least one valid value, and selecting the valid value of the target speed source signal as the valid speed.

[0029] In this embodiment, determining the target order for performing validity screening operations on multiple speed source signals of the train refers to the priority processing order for performing validity screening on multiple speed source signals pre-set based on the stability, reliability, data accuracy, and other characteristics of different speed source signals of the train. Multiple speed source signals may include axle speed signals fed back by the braking system, axle speed signals fed back by the traction system, etc. For example, the target order could be to first perform validity screening operations on the drag axle speed signal fed back by the braking system, then on the drive axle speed signal fed back by the braking system, and finally on the drive axle speed signal fed back by the traction system; or it could be to first perform validity screening operations on the drive axle speed signal fed back by the traction system, then on the drive axle speed signal fed back by the braking system, and finally on the drag axle speed signal fed back by the braking system. The specific target order can be flexibly set according to the actual train operating scenario and the characteristics of the speed source signals.

[0030] In this embodiment, performing validity screening on each speed source signal sequentially according to the target order refers to checking whether the data of each speed source signal meets preset validity conditions in a predetermined target order. Preset validity conditions may include whether the data is within a reasonable speed range for normal train operation, whether there are no interruptions or interferences during data transmission, and whether the data has no significant deviations exceeding the normal fluctuation range. For example, if the target order is the drag axle speed signal from braking feedback, the drive axle speed signal from braking feedback, and the drive axle speed signal from traction feedback, then first, for the drag axle speed signal from braking feedback, check whether each data point it contains meets the preset validity conditions, and exclude invalid data that does not meet the conditions. If the speed source signal has no valid value after screening, then the same validity screening operation is performed on the next speed source signal, i.e., the drive axle speed signal from braking feedback, in the target order, and so on, until the screening of a certain speed source signal is completed or all speed source signals are traversed.

[0031] In other embodiments, valid values ​​can be confirmed through a combination of at least two of the following methods: numerical range determination, timestamp continuity determination, and signal check bit determination. Numerical range determination means that the numerical range is considered valid when the value of the velocity source signal is between a preset minimum threshold and a preset maximum threshold. Timestamp continuity determination means that the timestamp continuity is considered valid when the velocity source signal appears in three consecutive sampling periods and the time interval error is less than a set tolerance. Signal check bit determination means that the cyclic redundancy check code carried by the velocity source signal is considered valid when it matches the locally calculated result. The system marks the corresponding velocity source signal as a valid value only when at least two of the three determination methods are simultaneously satisfied, and stops subsequent filtering operations based on the marking results.

[0032] In this embodiment, when the currently selected target speed source signal has at least one valid value, the validity screening operation is stopped, and the valid value of the target speed source signal is selected as the valid speed. This means that after performing the validity screening operation on the current target speed source signal, if the number of data that meet the preset valid conditions after screening is one or more, the validity screening operation is no longer performed on subsequent speed source signals in the target sequence, and the data that meet the preset valid conditions in the current target speed source signal are directly determined as valid speeds. For example, if the currently selected target speed source signal is the brake feedback axle speed signal, after the validity screening operation, two invalid data that exceed the reasonable speed range are eliminated, and three data that meet the preset valid conditions remain, then it is determined that the target speed source signal has at least one valid value, the validity screening operation on the brake feedback axle speed signal and the traction feedback axle speed signal is stopped, and these three data that meet the preset valid conditions are taken as valid speeds. As another example, if the currently selected target speed source signal is the brake feedback axle speed signal, and only one data that meets the preset valid conditions remains after screening, the subsequent screening operation is also stopped, and this one data is taken as a valid speed.

[0033] In this way, by determining the target order and verifying the validity of each signal sequentially, the system can prioritize the use of signal sources with higher reliability (such as high-priority speed sources). This allows it to immediately stop subsequent verifications upon obtaining the first valid value, reducing computational overhead from redundant judgments and ensuring the priority use of more reliable data sources. When a speed source signal has at least one valid value, the system directly selects that valid value as the final output, avoiding calculation deviations caused by abnormalities or delays in subsequent signal sources. Simultaneously, by eliminating invalid values, the impact of noise or outliers on the results is reduced. While ensuring the accuracy of speed calculations, the logical design of orderly filtering and timely termination improves the system's real-time response capability and enhances its fault tolerance for single signal source failure scenarios, providing a more stable speed data foundation for train control.

[0034] In an optional embodiment of this application, the target sequence from front to back includes the drag shaft speed of braking feedback, the moving shaft speed of braking feedback, and the moving shaft speed of traction feedback.

[0035] In the embodiments of the present application, the trailing axle speed of the braking feedback refers to the speed signal collected and output by the train braking system during operation for the real-time running speed of the train's trailing axles (i.e., the axles that only carry the weight of the train itself and do not actively provide driving force), which can be generated by the braking state monitoring modules corresponding to the trailing axles of different carriages of the train. For example, the speed signal feedback by the braking monitoring module of the 3rd trailing axle of the first non-powered carriage of the train, the speed signal feedback by the braking monitoring module of the 1st trailing axle of the fifth non-powered carriage of the train, etc. Since the trailing axles do not directly participate in power transmission, their operating states are relatively less affected by factors such as wheel diameter wear and power system fluctuations, and the stability and accuracy of the speed signal are relatively high. Therefore, it is preferentially set as the first speed source type to be screened in the target order.

[0036] In the embodiments of the present application, the driving axle speed of the braking feedback refers to the speed signal collected and output by the train braking system during operation for the real-time running speed of the train's driving axles (i.e., the axles that carry the weight of the train and provide driving force through traction motors), which can be generated by the braking sensors corresponding to the driving axles of the train's powered carriages. For example, the speed signal feedback by the 2nd driving axle braking sensor of the second powered carriage of the train, the speed signal feedback by the 4th driving axle braking sensor of the fourth powered carriage of the train, etc. Compared with the driving axle speed of the traction feedback, this speed signal is only affected by the operating conditions of the braking system and is not interfered by factors such as traction system current fluctuations and motor load changes. The reliability of the speed signal is the second. Therefore, it is set as the second speed source type to be screened in the target order.

[0037] In the embodiments of the present application, the driving axle speed of the traction feedback refers to the speed signal collected and output by the train traction system during operation for the real-time running speed of the train's driving axles, which can be generated by the speed detection components supporting the train traction control unit or traction motors. For example, the 1st driving axle speed signal feedback by the traction control unit of the second powered carriage of the train, the 3rd driving axle speed signal feedback by the traction motor speed detection component of the fourth powered carriage of the train, etc. Since this speed signal is directly related to the power output state of the traction system and may be affected by factors such as traction current changes and motor temperature fluctuations, the stability of the speed signal is relatively low. Therefore, it is set as the third speed source type to be screened in the target order.

[0038] In this embodiment, a validity screening operation is performed on multiple speed source signals of the train in a predetermined order to obtain at least one valid speed. This includes: performing a validity screening operation on the drag axle speed of the braking feedback; when at least one valid value exists in the drag axle speed of the braking feedback, selecting that valid value as the valid speed; when no valid value exists in the drag axle speed of the braking feedback, performing a validity screening operation on the moving axle speed of the braking feedback; when at least one valid value exists in the moving axle speed of the braking feedback, selecting that valid value as the valid speed; when no valid value exists in the moving axle speed of the braking feedback, performing a validity screening operation on the moving axle speed of the traction feedback; when at least one valid value exists in the moving axle speed of the traction feedback, selecting that valid value as the valid speed; and when all speed sources have invalid valid values, there is no valid speed, and the train speed is set to zero.

[0039] In this way, the axle speed from braking feedback is less affected by factors such as wheel wear during train operation, and its signal stability is generally higher than that of the moving axle speed from braking feedback and the moving axle speed from traction feedback. When screening according to the above order, the validity check of the axle speed from braking feedback, which has higher stability, can be performed first. If a valid signal exists, this type of signal can be used as the source of valid speed, reducing speed fluctuations caused by prioritizing the use of a slightly less stable speed source signal. If there is no valid signal from the axle speed from braking feedback, the moving axle speed from braking feedback and the moving axle speed from traction feedback are then screened in sequence. This ensures that more stable speed signals are obtained first and avoids the problem of not being able to obtain valid speed due to the failure of a single speed source. By setting a priority speed source screening order, the possibility of deviations in speed calculation is reduced.

[0040] In practical applications, the trailing axle speed from braking feedback is prioritized. Invalid values ​​are removed from the trailing axle speed signal. When the number of valid values ​​is greater than or equal to 3, the maximum and minimum values ​​are removed, and the average of the remaining valid values ​​is taken. When the number of valid values ​​is greater than 0 and less than 3, the average of all valid values ​​is taken. When the valid value of the trailing axle speed from braking feedback is 0, the moving axle speed from braking feedback is selected as the signal source for calculating the train speed. Invalid values ​​are removed from the moving axle speed signal from braking feedback. When the number of valid values ​​is greater than or equal to 3, the maximum and minimum values ​​are removed, and the average of the remaining valid values ​​is taken. When the number of valid values ​​is greater than 0 and less than 3, the average of all valid values ​​is taken. When the number of valid values ​​for the axle speed from braking feedback is 0, the axle speed from traction feedback is selected as the signal source for calculating the train speed. Invalid values ​​are removed from the axle speed signal from traction feedback. If the number of valid values ​​is greater than or equal to 3, the maximum and minimum values ​​are removed, and the average of the remaining valid values ​​is taken. If the number of valid values ​​is greater than 0 but less than 3, the average of all valid values ​​is taken. When there are no valid values ​​for the drag axle speed from braking feedback, the axle speed from braking feedback, and the axle speed from traction feedback, the train speed is set to 0.

[0041] In one optional embodiment of this application, the multiple speed sources of the train include the drag shaft speed of braking feedback, the moving shaft speed of braking feedback, and / or the moving shaft speed of traction feedback.

[0042] In this way, the three speed sources originate from the train's braking and traction systems, respectively. The different signal acquisition methods reduce the impact of transient failures in a single system on the stability of the speed signal. For example, if a sensor related to the braking system experiences a brief anomaly, the traction feedback shaft speed may still remain normal and can serve as a valid speed signal source. Furthermore, clearly defining these three specific speed sources provides clear and concrete targets for performing validity screening operations on the speed source signals in a predetermined order. This avoids the disordered screening problem caused by multiple unclear speed source types, making the subsequent acquisition of valid speeds more targeted and ultimately helping to determine the train speed more accurately based on the valid speeds.

[0043] In an optional embodiment of this application, determining the train mileage based on the train speed includes: performing mileage accumulation calculation based on the train speed and the corresponding task scheduling cycle to obtain the accumulated mileage and small mileage data that is less than the set distance; storing the accumulated mileage and small mileage data, and reading the stored data when the system is powered on to continue performing mileage accumulation calculation.

[0044] In this embodiment, the train speed refers to a speed value that reflects the actual operating state of the train, determined after performing validity screening operations on multiple speed source signals. These multiple speed source signals may include the drag axle speed signal from braking feedback, the moving axle speed signal from braking feedback, etc. The corresponding task scheduling cycle refers to a fixed time interval during which the train's central control unit executes mileage calculation-related program tasks. This time interval can be set according to train control requirements, for example, a 100-millisecond task scheduling cycle or a 200-millisecond task scheduling cycle. A fixed task scheduling cycle ensures the regularity and accuracy of mileage accumulation calculation. The task scheduling cycle includes a fixed time period, an event triggering cycle, or an external synchronization cycle. The fixed time period is based on a millisecond-level clock tick, the event triggering cycle is based on the speed source signal update time, and the external synchronization cycle is based on the train network clock message. When the task scheduling cycle arrives, the system reads the current speed, multiplies the speed value by the cycle duration to obtain the cycle running distance, and accumulates the cycle running distance to the current small mileage data. When the small mileage data is greater than or equal to a set number of kilometers, the accumulated mileage increases by the set number of kilometers, the small mileage data decreases by the set number of kilometers, and the remaining portion continues to participate in the next accumulation.

[0045] In other embodiments, mileage accumulation calculation is performed based on the train's speed and the corresponding task scheduling cycle, including dynamically adjusting the cycle time of the task scheduling cycle using a multi-level scheduling strategy. This multi-level scheduling strategy can divide the operating mode according to train operating status parameters (such as acceleration and track gradient). For example, a fixed cycle time (e.g., 500 milliseconds) is used in constant speed mode, while an adaptive cycle time (e.g., 100 milliseconds) is used in acceleration or deceleration modes. Specifically, a sliding window algorithm can be used to analyze the speed change rate. When the speed change rate is less than a preset threshold, the system switches to a fixed cycle time; when the speed change rate is greater than the preset threshold, it switches to an adaptive cycle time. Through the design of this dynamic scheduling strategy, system resource consumption can be reduced while ensuring calculation accuracy.

[0046] In this embodiment, the cumulative mileage refers to the total distance traveled by the train from its first operation, mileage reset, or equipment replacement until the calculation restarts and the distance reaches the set number of kilometers. The unit is usually kilometers. This value increases accordingly as small mileage data that is less than the set number of kilometers is accumulated to the set number of kilometers. For example, if the set number of kilometers is 1 kilometer, when the small mileage data that is less than the set number of kilometers accumulates from 900 meters to 150 meters and reaches 1050 meters, the cumulative mileage increases by 1 kilometer (from the original 100 kilometers to 101 kilometers). If the subsequent small mileage data accumulates another 980 meters to reach 1030 meters, the cumulative mileage increases by another 1 kilometer (becoming 102 kilometers).

[0047] In this embodiment of the application, the "small mileage data that is less than the set mileage" refers to the difference between the current running displacement and the total displacement corresponding to the accumulated mileage during the mileage accumulation calculation process. This difference does not reach the set mileage, and its unit is usually meters. The set mileage can be set according to the mileage statistics requirements. For example, if the set mileage is 1 kilometer (1000 meters), when the accumulated mileage is 80 kilometers, if the current total displacement is 80650 meters, then the small mileage data that is less than the set mileage is 650 meters; if the set mileage is 2 kilometers (2000 meters), when the accumulated mileage is 50 kilometers, the current total displacement is 51200 meters, then the small mileage data that is less than the set mileage is 1200 meters.

[0048] In this embodiment, storing the cumulative mileage and small mileage data refers to using a non-volatile storage medium to persistently save the cumulative mileage updated after each mileage calculation and the small mileage data that is less than the set distance. The non-volatile storage medium can be a storage device that can retain data after power failure, such as a ferroelectric memory or an EEPROM (electrically erasable programmable read-only memory). After each train speed and task scheduling cycle calculates the displacement and updates the cumulative mileage or small mileage data, the latest two data are immediately written to the selected storage medium to prevent data loss due to system power failure.

[0049] In this embodiment, when the system is powered on, reading the stored data to continue the mileage accumulation calculation means that after the train's mileage calculation system or the train's central control unit switches from a power-off state to a power-on state, it first retrieves the previously stored cumulative mileage value and the small mileage data value that is less than the set distance from the non-volatile storage medium used to store the cumulative mileage and small mileage data. These two values ​​are used as the initial basic data for this mileage accumulation calculation. Then, combined with the newly acquired train speed and the corresponding task scheduling cycle, the displacement calculation and mileage accumulation operation are continued. For example, after the system is powered on, it reads the stored cumulative mileage as 150 kilometers and the small mileage data as 700 meters. Subsequently, based on the new train speed and task scheduling cycle, the displacement of 300 meters is calculated and added to the 700-meter small mileage data to reach 1000 meters. At this time, the cumulative mileage is updated to 151 kilometers and the small mileage data is updated to 0 meters, and the subsequent calculation continues.

[0050] In other embodiments, upon system power-up, stored cumulative mileage and short-mileage data are read to continue mileage accumulation calculation, including employing a data recovery verification mechanism to ensure data integrity. This data recovery verification mechanism may include timestamp consistency checks, numerical range verification, and historical data comparison analysis. For example, when reading cumulative mileage data, the expected mileage increment can be calculated by comparing the difference between the current timestamp and the stored timestamp, and cross-validated with stored short-mileage data; when reading short-mileage data, numerical accuracy can be verified through conversion between high-precision integer format and floating-point format. Through the design of a multi-dimensional verification process, the calculation state can be quickly restored upon system restart, avoiding cumulative errors caused by data anomalies.

[0051] In this way, when determining mileage based on train speed, mileage accumulation calculation is first performed based on the train speed and the corresponding task scheduling cycle to obtain the cumulative mileage and small mileage data that is less than the set distance. By combining this with a fixed task scheduling cycle, the train's running mileage within each scheduling cycle can be meticulously accumulated, avoiding the omission of small mileage data that is less than the set distance when calculating directly using the set distance as the unit, and reducing the accumulation error caused by discarding small mileage data. Storing the cumulative mileage and small mileage data and retrieving the stored data to continue the mileage accumulation calculation when the system is powered on prevents the loss of mileage data generated after a power outage, ensuring that mileage accumulation continues from the previous calculation node and avoiding the mileage data gaps or duplicate calculations that may occur when recalculating after a power outage. Using the above method, errors caused by the omission of small mileage data are reduced, and the continuity of mileage data accumulation is ensured, thereby improving the accuracy of train mileage calculation.

[0052] In an optional embodiment of this application, the mileage accumulation calculation includes: calculating the displacement of the train within the corresponding task scheduling cycle based on the train speed and the cycle time of the corresponding task scheduling cycle; accumulating the displacement into the read current small mileage data to obtain the accumulated small mileage data; determining whether the accumulated small mileage data is greater than or equal to a set number of kilometers; when the accumulated small mileage data is greater than or equal to the set number of kilometers, increasing the read current accumulated mileage by a set multiple of the set number of kilometers, and subtracting the accumulated small mileage data from the set multiple of the set number of kilometers.

[0053] In this embodiment, calculating the train's displacement within the corresponding task scheduling cycle refers to multiplying the train's speed value by the cycle time value of the task scheduling cycle to obtain an approximate distance traveled by the train within that cycle. For example, when the speed is in meters per second and the time is in seconds, the displacement unit is meters. Accumulating the displacement into the read current small mileage data means adding the calculated displacement value to the small mileage value read from the memory, updating the small mileage data value to reflect the latest accumulated distance status. Determining whether the accumulated small mileage data is greater than or equal to a set number of kilometers means comparing the accumulated small mileage value with a preset mileage unit threshold, typically set to 1000 meters or 1 kilometer, to trigger a mileage carry-over operation. Increasing the read current accumulated mileage by a set multiple of a set number of kilometers means that when the small mileage data reaches or exceeds the set number of kilometers, the accumulated mileage value is increased by one or more complete mileage units. For example, when the small mileage exceeds 1000 meters, the accumulated mileage is increased by 1 kilometer. Subtracting a set number of kilometers from the accumulated mileage data means subtracting the corresponding number of complete mileage units from the accumulated mileage data after the accumulated mileage has increased, and retaining the remaining mileage value. For example, subtracting 1000 meters from the accumulated mileage data.

[0054] In other embodiments, the displacement of the train within the corresponding task scheduling cycle is calculated based on the train's speed and the cycle time of the corresponding task scheduling cycle. This includes using a dynamic displacement calculation model that combines the integral relationship between speed and time. This dynamic displacement calculation model can select different integration algorithms based on train operating state parameters (such as acceleration and track gradient). For example, it can use the trapezoidal integral method during the constant speed phase and the Simpson integral method during the acceleration or deceleration phase. Specifically, a sliding window algorithm can be used to analyze the rate of change of speed. When the rate of change of speed is less than a preset threshold, the method is switched to the trapezoidal integral method; when the rate of change of speed is greater than the preset threshold, the method is switched to the Simpson integral method. Through the design of this dynamic integration strategy, the computational complexity can be reduced while ensuring displacement accuracy.

[0055] In other embodiments, the accumulated mileage data is obtained by adding the displacement to the read current mileage data, which may include storage and calculation using a high-precision data format. This high-precision data format can be configured as a floating-point format (such as IEEE 754 double-precision floating-point) or a high-precision integer format (such as a 64-bit unsigned integer). Specifically, the accumulation process of the mileage data can be handled using a fixed decimal representation or a dynamic range expansion algorithm. For example, in floating-point format, numerical precision can be preserved by setting a fixed exponent portion, avoiding rounding errors caused by frequent accumulation; in high-precision integer format, large-range decimal precision accumulation calculations can be achieved by expanding the bit width or using a segmented storage strategy. Through the design of a high-precision calculation mechanism, accumulated errors caused by low-precision data formats can be effectively avoided.

[0056] In other embodiments, determining whether the accumulated mileage data is greater than or equal to a set mileage can include using a multi-level threshold verification mechanism for hierarchical judgment. This multi-level threshold verification mechanism may include a preset primary threshold judgment and a secondary error compensation judgment. For example, the primary threshold judgment directly compares the accumulated mileage data with the set mileage, while the secondary error compensation judgment corrects the current judgment result by analyzing historical error accumulation trends. Specifically, error band compensation logic can be added after the primary threshold judgment. When the accumulated mileage data approaches the set mileage, dynamic correction is performed based on the error accumulation values ​​of the previous N task scheduling cycles. Through the design of the multi-level verification mechanism, the robustness of the threshold judgment can be improved, avoiding misjudgments caused by instantaneous errors.

[0057] In this way, by calculating displacement (i.e., speed multiplied by the cycle time) in units of task scheduling cycles, continuous speed fluctuations can be transformed into discrete displacement increments, thereby reducing the risk of accumulated integral errors caused by instantaneous speed changes. Subsequently, the displacement is accumulated into the small mileage data, and within each task cycle, it is determined whether a set mileage threshold has been reached. If so, the large mileage data and small mileage data are stored separately by increasing the accumulated mileage and adjusting the small mileage data. This avoids the accuracy loss caused by frequent accumulation of the decimal part and reduces the update frequency of the accumulated mileage (updates are triggered only when the small mileage reaches the threshold), thus reducing storage pressure and computational resource consumption. By improving accuracy through staged calculations and optimizing efficiency through layered storage, the system's real-time performance and stability can be ensured while maintaining the accuracy of mileage accumulation.

[0058] In an optional embodiment of this application, the method for calculating train mileage further includes: synchronizing mileage data between the master-slave redundant configuration of the train central control unit to keep the mileage data of the master and slave units consistent.

[0059] In this embodiment, master-slave redundancy configuration refers to a redundant architecture design in the train control system consisting of at least two central control units with identical functions, such as master-standby unit configuration or dual-machine hot standby configuration, where one unit operates as the master unit and the other unit stands by as the slave unit. The train central control unit refers to the processing unit in the train control system responsible for core calculation and control functions, such as the vehicle control unit or the central processing unit of the train control and management system, used to perform train mileage calculation and data management tasks. Mileage data synchronization refers to the process of exchanging mileage information, such as cumulative mileage values ​​and small mileage data values, between the master-slave redundant train central control units through a communication network, and using a specific strategy to keep the data consistent between the two sides. Maintaining consistency of mileage data between master and slave units means ensuring that the mileage values ​​stored in the master unit and slave unit are the same or within an acceptable error range through a data synchronization mechanism, such as by using the larger value principle or timestamp comparison to achieve data alignment, thereby ensuring the continuity of mileage calculation during master-slave switching. Specifically, mileage data synchronization includes: periodically exchanging life signals, cumulative mileage values, and minimum mileage values ​​between master and slave units; if one unit detects that the life signal of the other unit is normal and its cumulative mileage value is greater than its own, then it updates its own cumulative mileage value to the other unit's cumulative mileage value; if one unit detects that the life signal of the other unit is normal and its minimum mileage value is greater than its own, then it updates its own minimum mileage value to the other unit's minimum mileage value. Data synchronization between master and slave units can be achieved through train network communication.

[0060] In other embodiments, mileage data synchronization between the train central control units with master-slave redundancy configurations also includes employing a multi-channel redundant transmission mechanism to ensure data consistency. This multi-channel redundant transmission mechanism can be configured as parallel data channel synchronization or cross-validation channel synchronization. For example, in parallel data channel synchronization, the master unit simultaneously sends mileage data to the slave unit through multiple physical communication links (such as CAN bus and Ethernet). In cross-validation channel synchronization, the master and slave units verify data consistency by alternately sending checksums. Specifically, fault tolerance for multi-channel data transmission can be achieved through hardware redundancy design (such as a dual-MCU architecture) or software redundancy design (such as dual-thread processing), ensuring that data synchronization functionality is maintained even in the event of a single-channel failure.

[0061] In other embodiments, mileage data synchronization between the train central control units with master-slave redundancy configurations also includes using a timestamp alignment algorithm to eliminate data transmission delay differences. This timestamp alignment algorithm can be implemented through a hardware timestamp capture module or a software timestamp compensation algorithm. For example, in a hardware implementation, a timestamp is added to the transmitted data using a high-precision clock source from the master unit, and data delay compensation is performed at the slave unit receiving end based on the deviation between the timestamp and the local clock. In a software implementation, a moving average algorithm is used to dynamically correct the time offset between the master and slave units. Through the design of the timestamp alignment mechanism, the problem of mileage data asynchrony caused by communication link delay differences can be eliminated.

[0062] In other embodiments, mileage data synchronization between the central control units of the train with master-slave redundancy configuration also includes a state machine switching strategy to dynamically allocate the roles of master and slave units. This state machine switching strategy can automatically trigger master-slave role transitions based on the system's health status. For example, when the master unit detects that the difference between its accumulated mileage data and the slave unit's accumulated mileage data exceeds a preset threshold, it actively triggers a degradation process, promoting the slave unit to master. When the slave unit detects a communication interruption with the master unit, it takes over the master unit's functions according to preset priority rules. Specifically, automatic state machine switching can be achieved through a heartbeat signal monitoring mechanism (such as periodically sending health status messages) or an arbitration algorithm (such as priority arbitration based on MAC addresses), ensuring that the redundant system can maintain data synchronization functionality even in abnormal situations.

[0063] In this way, the master-slave redundancy configuration inherently possesses fault-to-failure capability. However, if the mileage data between the master and slave units is not synchronized in a timely manner, discrepancies may arise due to data differences left over from the master unit's fault switchover, leading to inconsistencies between the calculated results of the slave unit after takeover and the actual operating status. By employing periodic or event-triggered data synchronization mechanisms, real-time consistency of cumulative mileage and small mileage data between the master and slave units can be ensured within the task scheduling cycle. This allows the slave unit to seamlessly take over and continue accurate mileage calculations in the event of a master unit failure, avoiding data gaps or duplicate calculations caused by the switchover. By combining redundancy architecture with data synchronization logic, the system's reliability under hardware failure scenarios is improved, while the control risks caused by data inconsistency are reduced.

[0064] In an optional embodiment of this application, the method for calculating train mileage further includes: providing a human-machine interface for receiving mileage setting instructions input by a user to correct the train mileage.

[0065] In this embodiment, the human-machine interface (HMI) refers to an interactive device in the train control system that provides information display and operation input functions, such as a touch screen, physical button panel, or graphical user interface, used to realize information interaction between the operator and the train control system. The HMI can be integrated into the train driver's console, supporting mileage setting values ​​input via touchscreen or buttons. Receiving user-inputted mileage setting instructions means obtaining manually input mileage correction data through the HMI, such as inputting numbers via touchscreen or adjusting values ​​via buttons, for manual intervention and calibration of automatically calculated mileage results. Correcting the train's mileage means updating the mileage data stored in the train control system according to the user-inputted mileage setting instructions, such as directly modifying the cumulative mileage value or small mileage data value, to correct mileage calculation deviations caused by system errors, equipment replacement, or abnormal conditions.

[0066] In other embodiments, a human-machine interface is provided for receiving user-inputted mileage setting commands, including supporting user interaction through multimodal input methods. This multimodal input method can be configured as numeric keypad input, voice command input, or graphical operation input. For example, a numeric input box can be set up on a touchscreen interface for users to directly input values, or a voice recognition module can receive user voice commands and convert them into text-formatted mileage setting values, or a slider control can be used to visually adjust the values. This multimodal input design can meet the needs of users in different operating scenarios, improving input efficiency and operational flexibility.

[0067] In other embodiments, after the human-machine interface receives the mileage setting command input by the user, it includes an input validation mechanism to ensure the legality of the command. This input validation mechanism may include numerical range verification, format compliance checks, and historical data consistency analysis. For example, numerical range verification can restrict the mileage value input by the user to a preset physical range (e.g., 0 to 9999 kilometers), format compliance checks can verify whether the input value conforms to a preset data format (e.g., integer or floating-point number), and historical data consistency analysis can determine whether there are abnormal fluctuations by comparing the current input value with the differences of the most recent N input records. Through the design of a multi-level validation process, mileage data errors caused by accidental operations can be effectively prevented.

[0068] In other embodiments, the human-machine interface transmits the user-input mileage setting command to the mileage correction module, including data interaction using an event-driven communication mechanism. This event-driven communication mechanism can complete data transmission through a predefined message queue or callback function interface. For example, when the numeric input box is submitted, a "mileage setting update" event is triggered, encapsulating the input value into a standard data structure (such as JSON format) and sending it to the mileage correction module; or after voice command recognition is completed, the parsing result is directly injected into the mileage correction process through a callback interface. Through the design of the event-driven architecture, decoupling and asynchronous processing capabilities between modules can be achieved.

[0069] In other embodiments, after receiving the mileage setting command, the human-machine interface includes a real-time feedback mechanism to display the operation status to the user. This real-time feedback mechanism can be implemented through interface status indicator lights, pop-up prompts, or sound prompts. For example, after the input value is verified, a green status indicator light illuminates and displays the text "Correction Successful," or a red warning box pops up indicating "Input Out of Range" when an input anomaly is detected. This multi-dimensional feedback design helps users intuitively grasp the operation results and reduces operational doubts.

[0070] In other embodiments, the access control function of the human-machine interface includes using a hierarchical access control strategy to restrict mileage setting operations. This hierarchical access control strategy can be configured to be based on user role-based access (e.g., operators can only view mileage data, while administrators can modify it), or based on operating mode-based access (e.g., any user can input in debug mode, while only authorized users can input in run mode). Specifically, access levels can be dynamically switched through a preset user authentication mechanism (e.g., password verification or biometric recognition) to ensure the security and controllability of mileage setting operations.

[0071] In this way, discrepancies may arise between the accumulated mileage and the actual mileage during train operation due to speed calculation errors, system initialization anomalies, or external interference. By receiving correction commands from the user through the human-machine interface, manual intervention can be directly applied to the current accumulated mileage or small mileage data, quickly correcting errors in the system's automatic calculations. While ensuring the accuracy of the system's automatic calculations, an operable interface for manual calibration is provided, particularly suitable for initial calibration during the initial stages of train operation, data recovery after system reset, or intervention needs in scenarios where abnormal accumulation is detected. By embedding user-input correction logic into the mileage accumulation process, the system's adaptability to complex operating conditions is improved, and the risk of mileage deviation caused by the long-term accumulation of automatic calculation errors is reduced. Thus, through the synergy of automation and manual intervention, a more reliable data foundation is provided for train operation monitoring and data analysis.

[0072] Combination Figure 2As shown, this application provides a train mileage calculation device 800, including a processor 801 and a memory 802. Optionally, the device may further include a communication interface 803 and a bus 804. The processor 801, communication interface 803, and memory 802 can communicate with each other via the bus 804. The communication interface 803 can be used for information transmission. The processor 801 can call logical instructions in the memory 802 to execute the train mileage calculation method described in the above embodiment.

[0073] Furthermore, the logic instructions in the aforementioned memory 802 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0074] The memory 802, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this application. The processor 801 executes functional applications and data processing by running the program instructions / modules stored in the memory 802, that is, it implements the method for calculating train mileage in the above embodiments.

[0075] The memory 802 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 802 may include high-speed random access memory and may also include non-volatile memory.

[0076] This application provides a system including a system body and the aforementioned train mileage calculation device 800. The train mileage calculation device 800 is installed in the system body. The installation relationship described herein is not limited to placement within the system, but also includes installation and connection with other components of the system, including but not limited to physical connections, electrical connections, or signal transmission connections. Those skilled in the art will understand that the train mileage calculation device 800 can be adapted to feasible system bodies to achieve other feasible embodiments.

[0077] This application provides a computer-readable storage medium storing computer-executable instructions configured to execute the above-described method for calculating train mileage.

[0078] The technical solutions of this application embodiment can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this application embodiment. The aforementioned storage medium can be a non-transitory storage medium, including: USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, and other media capable of storing program code.

[0079] The technical solutions of this application embodiment can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this application embodiment. The aforementioned storage medium can be a non-transitory storage medium, including: USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, and other media capable of storing program code.

[0080] The foregoing description and accompanying drawings fully illustrate embodiments of this application to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., of the embodiments claimed, if they correspond to the method section of the embodiments claimed, then the relevant parts can be referred to the description of the method section.

[0081] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments claimed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0082] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0083] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for calculating train mileage, characterized in that, include: The train speed is determined based on multiple speed source signals. The train's mileage is determined based on its speed.

2. The method according to claim 1, characterized in that, The train speed is determined based on multiple speed source signals, including: Perform validity filtering operations on multiple speed source signals of the train in a set order to obtain at least one valid speed; The train speed is determined based on at least one valid speed.

3. The method according to claim 2, characterized in that, A validity screening operation is performed on multiple speed source signals of the train according to a set order to obtain at least one valid speed, including: Determine the target sequence for performing validity screening operations on multiple speed source signals of the train; Perform validity filtering operations on each velocity source signal in the order of the targets; When at least one valid value exists in the target velocity source signal being screened, the validity screening operation is stopped, and the valid value of the target velocity source signal is selected as the valid velocity.

4. The method according to claim 2, characterized in that, The target sequence, from front to back, includes the drag shaft speed of braking feedback, the moving shaft speed of braking feedback, and the moving shaft speed of traction feedback.

5. The method according to any one of claims 1 to 4, characterized in that, The train's multiple speed sources include the drag shaft speed of braking feedback, the driving shaft speed of braking feedback, and / or the driving shaft speed of traction feedback.

6. The method according to any one of claims 1 to 4, characterized in that, Determine the train's mileage based on its speed, including: Based on the train's speed and the corresponding task scheduling cycle, mileage accumulation calculation is performed to obtain the cumulative mileage and small mileage data that is less than the set mileage. The system stores the cumulative mileage and short mileage data, and reads the stored data when the system is powered on to continue the mileage accumulation calculation.

7. The method according to claim 6, characterized in that, Accumulated mileage calculation includes: Calculate the displacement of the train within the corresponding task scheduling cycle based on the train's speed and the cycle time of the corresponding task scheduling cycle. The displacement is accumulated into the current small mileage data to obtain the accumulated small mileage data; Determine whether the accumulated mileage data is greater than or equal to the set mileage; When the accumulated mileage data is greater than or equal to the set mileage, the current accumulated mileage will be increased by the set mileage multiplier, and the accumulated mileage data will be subtracted from the set mileage multiplier.

8. A device for calculating train mileage, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute, when running the program instructions, the method for calculating train mileage as described in any one of claims 1 to 7.

9. A system, characterized in that, include: System body; as well as, The calculation device for train mileage as described in claim 8 is installed in the system body.

10. A computer-readable storage medium storing program instructions, characterized in that, When the program instructions are executed, they cause the computer to perform the method for calculating train mileage as described in any one of claims 1 to 7.

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