Railway wagon empty weight system optimization method and device

Abstract

This invention discloses an optimization method and device for an empty freight car weighing system, belonging to the field of track scale measurement and weighing technology. First, the load-bearing structure of the tippler track scale is reinforced by adding lateral limiting supports to optimize the mechanical transmission path. A potentiometer-less sensor junction box and intelligent instrument are configured, utilizing their analog-to-digital conversion, automatic location selection, and parameter correction functions to improve signal acquisition stability. A digital indicating track scale is set up as the control weighing instrument, and the temporary standardization function for freight cars enables traceability and comparison of values ​​between the tippler track scale and standard weighing instruments. Then, a progressive error compensation algorithm is executed, relying on the automatic correction capability of the intelligent instrument to dynamically compensate for weighing data to suppress drift. This invention significantly improves the long-term accuracy and system reliability of empty car weighing through the synergy of structural optimization, intelligent monitoring, standard traceability, and algorithm compensation.

Description

Technical Field

[0001] This invention relates to the field of railway weighing and measurement technology, and in particular to an optimization method, device, equipment and storage medium for an empty railway freight car weighing system. Background Technology

[0002] In the coal transportation and metering system of large power plants, unloading of railway freight cars mainly relies on tipplers, and the corresponding weighing and metering has traditionally used tippler rail scales. However, such scales have inherent structural and technical defects in practical applications, resulting in serious challenges in terms of weighing accuracy, long-term stability, and compliance with metrological regulations.

[0003] As unloading equipment, tipplers are designed to meet the demands of high-intensity, high-frequency mechanical tipping. Manufacturers typically do not design and manufacture their platform structures according to the precision metrological standards of rail scales. According to national rail scale manufacturing standards, high-precision rail scales require extremely high rigidity in their load-bearing structure. A typical indicator is that when a 40-ton weight trolley acts on the mid-span of the load-bearing structure, the resulting deflection should not exceed one-thousandth (high-precision requirements may even reach 0.5 per thousand). However, the rigidity of the original load-bearing structure of tipplers generally cannot meet these metrological standards. To ensure that the modified tippler rail scale passes calibration, the modifier is often forced to reduce the calibration graduation, essentially relaxing the legally permissible error range to mask the inherent, non-negligible weighing system error caused by insufficient structural rigidity.

[0004] The fundamental lack of rigidity in this structure has led to persistent measurement inaccuracies during actual operation. Periodic verification by the Shanghai branch of the National Rail Weighing Metrology Station revealed that when the standard 40-ton weight trolley reached the center of the tippler's weighing platform, the weighing error exhibited a significant positive deviation, stabilizing at approximately 1 ton. Based on the linear characteristics of the weighing system, this error would result in a deviation of approximately 2 tons in the overall vehicle weighing result and approximately 0.6 tons in the empty vehicle weighing result. This not only proves that excessive deflection of the load-bearing structure under load is the main source of system error, but also reveals that the weighing instrument experiences gradual data drift during its service life, with a continuous decline in metrological performance. In the 2023 periodic verification record, the verification agency explicitly stated the conclusion of "aging of the weighing body and electrical components, data inconsistencies, and a major overhaul recommended," and warned that without substantial rectification, subsequent periodic verifications would not be arranged, meaning its legal metrological qualification would face termination.

[0005] Given the aforementioned insurmountable accuracy and reliability issues of tippler rail scales, their reliability as a basis for trade settlement has been severely damaged. Therefore, the current industry trend clearly shifts towards more independent and specialized metrology solutions. Many newly built power plants have completely abandoned the model of using tipplers as weighing instruments, instead installing high-precision digital indicating rail scales or automatic rail scales independently on the tippler entry and exit lines. Many older plants are also undergoing similar technological upgrades. The core purpose of this shift is to decouple the unloading function from the high-precision metrology function. By adopting rail scales specifically designed for precision weighing, independently installed, and with strictly compliant structural rigidity and stability, the accuracy, repeatability, and long-term stability of freight car and empty car weighing data are fundamentally ensured, meeting stringent trade metrology and management requirements. Summary of the Invention

[0006] The present invention aims to at least partially solve one of the technical problems in the related art.

[0007] To address this, this invention discloses an optimization method for an empty freight car weighing system. By strengthening the stiffness and optimizing the mechanical path of the tippler's track scale bearing structure, a potentiometer-free intelligent sensor network is constructed to achieve accurate signal acquisition and parameter self-correction. Furthermore, a measurement traceability system based on the controlled weighing instrument is established to ensure metrological traceability. Finally, a progressive dynamic error compensation algorithm is executed to suppress data drift. Through the synergistic effect of structural enhancement, intelligent sensing, standard comparison, and algorithm compensation, a significant improvement in the accuracy of empty car weighing and the long-term stability of the system is achieved.

[0008] Another objective of this invention is to provide an optimization device for an empty railway freight car weighing system.

[0009] The third objective of this invention is to provide a computer device.

[0010] The fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0011] To achieve the above objectives, this invention proposes an optimization method for an empty railway freight car weighing system, comprising: S1, the load-bearing structure of the tippler track scale is reinforced and modified to improve its rigidity, and a lateral limiting support foundation is added to optimize the force transmission path. S2 is equipped with a potentiometer-less sensor junction box and an intelligent meter, which enables analog-to-digital conversion, automatic addressing, and parameter correction of the weighing sensor. S3, set up a digital indicator rail scale as a control weighing instrument, and use the temporary standard setting function of freight cars to conduct a traceability comparison of the value of the tipper rail scale and the digital indicator rail scale; S4 executes a progressive error compensation algorithm, which dynamically compensates for empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift.

[0012] An optimization method for an empty railway freight car weighing system according to an embodiment of the present invention may also have the following additional technical features: In one embodiment of the present invention, the stiffness enhancement modification of the load-bearing structure of the tippler track scale, and the addition of lateral limiting support foundations to optimize the force transmission path, includes: S11, anti-climb foundations are added to both ends of the original top vehicle platform foundation to prevent track displacement; S12, sensor bearing foundation and lateral limiting support foundation are set in the foundation pit, and the force transmission path is evenly distributed by optimizing the spacing of the lateral limiting supports.

[0013] In one embodiment of the present invention, the step of setting a digital indicating rail scale as a control weighing instrument and using the temporary benchmarking function for freight cars to perform a traceability comparison between the tipper rail scale and the digital indicating rail scale includes: S31 is verified through periodic comparison using M-level standard weights; S32 uses a T8 type weight weighing vehicle to perform on-site testing and generate traceability comparison records of measurement values.

[0014] In one embodiment of the present invention, the execution of the progressive error compensation algorithm, which dynamically compensates for empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift, includes: S41, calculate the compensation coefficient based on the linear change trend of the sensor output; S42 uses the distributed analog-to-digital conversion module of the smart instrument to independently compensate and correct the output of each sensor.

[0015] In one embodiment of the present invention, it further includes: S5, through the limit switch, is linked with the automatic vehicle number recognition system and the rebalancing machine control system to control the rebalancing machine to pull the heavy-duty freight car to the effective weighing area of ​​the rail scale; The S6 integrates the weighing management software with the fuel management system, enabling remote synchronous transmission of weighing data, vehicle number information, and video monitoring data.

[0016] To achieve the above objectives, another aspect of the present invention provides an optimization device for an empty railway freight car weighing system, comprising: The stiffness enhancement module is used to enhance the stiffness of the load-bearing structure of the tippler track scale and add lateral limiting support foundations to optimize the force transmission path. The sensor configuration module is used to configure potentiometer-less sensor junction boxes and smart meters, and to realize analog-to-digital conversion, automatic addressing and parameter correction of weighing sensors through smart meters; The control weighing instrument setting module is used to set the digital indicating rail scale as the control weighing instrument and to use the temporary benchmark setting function of freight cars to perform traceability comparison between the tipper rail scale and the digital indicating rail scale. The error compensation execution module is used to execute a progressive error compensation algorithm, which dynamically compensates the empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift.

[0017] In one embodiment of the present invention, it further includes: The limit switch linkage module is used to link the limit switch with the automatic vehicle number recognition system and the rebalancing machine control system to control the rebalancing machine to pull the heavy-duty freight car to the effective weighing area of ​​the rail scale. The data synchronization module is used to interface the weighing management software with the fuel management system to achieve remote synchronous transmission of weighing data, vehicle number information and video monitoring data.

[0018] This invention discloses an optimization method and apparatus for an empty railway freight car weighing system. By strengthening the rigidity of the load-bearing structure and optimizing the mechanical transmission path, a precise data acquisition network based on potentiometer-less intelligent sensors is constructed. A traceable metrological benchmark based on the control weighing instrument is established, and a progressive dynamic error compensation algorithm is executed. This effectively solves the problems of low weighing accuracy and poor long-term stability caused by insufficient structural rigidity, data drift, and inaccurate measurement values. Through the synergy of structural enhancement, intelligent sensing, standard traceability, and algorithm compensation, this method and apparatus achieve integrated optimization across the entire chain, from mechanical load-bearing, signal acquisition, metrological comparison to data compensation, significantly improving the accuracy, repeatability, and robustness of empty car weighing.

[0019] To achieve the above objectives, a third aspect of this application provides a computer device, including a processor and a memory; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, for implementing a railway freight car empty car weighing system optimization method as described in the first aspect embodiment.

[0020] To achieve the above objectives, a fourth aspect of this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an optimization method for an empty railway freight car weighing system as described in the first aspect embodiment.

[0021] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of an optimization method for an empty railway freight car weighing system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of an optimization device for an empty railway freight car weighing system according to an embodiment of the present invention; Figure 3 It is a computer device according to an embodiment of the present invention. Detailed Implementation

[0023] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] The following description, with reference to the accompanying drawings, describes an optimization method, apparatus, equipment, and storage medium for an empty railway freight car weighing system according to an embodiment of the present invention.

[0026] The core idea of ​​this invention is to construct a high-precision, high-stability empty car weighing system through systematic and coordinated optimization of the load-bearing structure, sensor network, metrological benchmark, and data processing algorithm. First, the load-bearing structure of the tippler's track scale is reinforced by adding key components such as lateral limit supports to fundamentally optimize the mechanical transmission path and suppress inherent errors caused by structural deflection. Based on this, a potentiometer-less sensor junction box and an intelligent instrument integrating analog-to-digital conversion, automatic addressing, and parameter correction functions are configured to construct a precise, reliable, and self-calibrating intelligent sensor network. Furthermore, a digital indicating track scale is set up as the control weighing instrument, and the temporary benchmarking function for freight cars is used for periodic value traceability comparison to establish a traceable on-site metrological benchmark, ensuring the long-term accuracy and legal compliance of the system's values. Finally, a progressive error compensation algorithm is executed, relying on the automatic correction function of the intelligent instrument to dynamically and accurately compensate the sensor output, continuously eliminating data drift caused by component aging and environmental factors. This integrated solution transforms the traditional model that relies on improvements in a single link into a collaborative optimization system that integrates mechanical structure enhancement, intelligent sensing, standard traceability, and dynamic algorithm compensation, thereby significantly improving the accuracy, repeatability, and long-term operational stability of empty vehicle weighing.

[0027] Example 1 To achieve the above invention, embodiments of the present invention provide an optimization method for a railway freight car empty car weighing system, such as... Figure 1 As shown, it includes: S1, the load-bearing structure of the tippler track scale is reinforced with increased stiffness, and a lateral limiting support foundation is added to optimize the force transmission path.

[0028] Specifically, this step mainly involves optimizing the mechanical properties and force transmission path of the load-bearing structure to reduce weighing errors caused by structural deformation, thereby meeting the technical requirements for ordinary accuracy class (Level IV) in the JJG781-2019 "Digital Indicating Rail Scale" verification procedure.

[0029] Furthermore, the load-bearing structure of a tippler weighbridge typically consists of the tippler's own load-bearing platform, which is approximately 16 meters long. Because the original structure only installed column-type load cells at the four corners, the load-bearing platform is prone to significant deflection under load, leading to horizontal force decomposition and affecting the linearity of the sensor output. To address this issue, this step employs a combination of structural reinforcement and the addition of lateral limiting supports. Specifically, by adding limiting support foundations at key lateral nodes of the load-bearing structure, the lateral stiffness of the structure is enhanced, limiting the lateral displacement of the truck during weighing. This optimizes the force transmission path, allowing the load to be distributed more evenly among the sensors and reducing errors caused by structural deformation.

[0030] Furthermore, according to national standards for railway weighbridge metrology, the deflection of a railway weighbridge under a 40t weight trolley at mid-span should not exceed 1‰. In this project, the goal of modifying the tippler railway weighbridge is to ensure it meets the general accuracy class (Level IV) requirements when weighing empty vehicles, i.e., a maximum permissible error of ±0.5%. By adding lateral limiting support foundations, the lateral deformation of the load-bearing structure can be effectively controlled, ensuring that the load distribution on the sensors conforms to linear requirements during empty vehicle weighing, thereby improving the stability and reliability of the weighing data.

[0031] Specifically, this step is mainly applied to the empty car weighing process after the tippler has unloaded the vehicle. Because the tippler's track scale is under unloading conditions for extended periods, its load-bearing structure is prone to fatigue and aging, leading to a decrease in rigidity. This modification can extend the equipment's service life, reduce the accumulation of weighing errors caused by structural problems, and thus prevent the national track scale metrology station from refusing calibration due to excessive errors.

[0032] Specifically, this step significantly improves the structural stability and weighing accuracy of the rail scale, providing a reliable foundation for subsequent empty car weighing data acquisition and automatic matching with loaded car weighing data. Simultaneously, by reducing structural deflection, it lowers the risk of nonlinear sensor output, improves the overall metrological confidence of the system, and provides solid data support for power plant fuel management and economic benefit analysis.

[0033] Furthermore, S1 includes: S11, anti-climb foundations are added to both ends of the original top vehicle platform foundation to prevent track displacement.

[0034] Specifically, the technical principle of this step is based on the stiffness control requirements of the track scale bearing structure. That is, anti-creep foundations are set at both ends of the track scale installation area to enhance the lateral constraint between the track and the foundation, and prevent the track from lateral displacement or creep caused by train operation or environmental factors (such as temperature changes, foundation settlement, etc.). This ensures that the weighing sensor maintains linear output during the stress process, improves weighing accuracy and long-term system stability.

[0035] Specifically, firstly, based on the structural dimensions and bearing capacity of the original track platform foundation, the geometry and depth of the anti-climb foundation are designed. The anti-climb foundation typically uses reinforced concrete, with its width matching the original foundation, while its length is determined according to the lateral displacement control requirements of the track scale installation area, generally ranging from 1.5m to 2.5m. The foundation depth should meet the stability requirements of the railway track structure, typically not less than 1.2m, to ensure it is below the frost line and avoid the impact of seasonal foundation deformation on the track.

[0036] Furthermore, the spacing of the anti-creep foundations should be controlled within 1.0m to 1.5m at each end of the effective weighing area of ​​the rail scale to ensure that their restraining effect on the track covers the entire weighing area. Simultaneously, the connection between the foundation and the track is achieved by welding pre-embedded steel plates to the track anchors, ensuring that the connection strength is not lower than the transverse shear strength required by the design of the rail scale's load-bearing structure, typically ≥150kN. In addition, the construction of the anti-creep foundations must comply with the relevant standards for the stiffness and displacement control of rail scale foundations in the "Railway Track Design Code" (TB 10082) and the JJG781-2019 "Digital Indicating Rail Scale" verification procedure.

[0037] Specifically, due to the long-term idleness of the original top car platform, its foundation structure may have undergone a certain degree of settlement or deformation. Adding an anti-climb foundation can effectively prevent track displacement during the weighing process, thereby reducing the horizontal decomposition of forces caused by structural deformation and improving the output linearity of the weighing sensor. Simultaneously, this measure provides a stable foundation for the subsequent installation of digital indicating rail scales, helping to meet the technical requirements of medium accuracy level (Level III), ensuring the accuracy and reliability of loaded vehicle weighing data, and providing solid data support for coal transportation settlement and safety management.

[0038] S12, sensor bearing foundation and lateral limiting support foundation are set in the foundation pit, and the force transmission path is evenly distributed by optimizing the spacing of the lateral limiting supports.

[0039] Specifically, this step optimizes the spacing of the lateral limit supports to ensure that the force transmission path is evenly distributed on the load-bearing structure when a truck passes by, thereby effectively improving the stability and measurement accuracy of the weighing system.

[0040] Specifically, the sensor support foundation is used to install the load cells, and its arrangement must strictly comply with the requirements for the stiffness and deflection of the load-bearing structure in the JJG781-2019 "Digital Indicating Rail Scale" verification procedure. Specifically, the sensor foundation should be located at the critical stress points of the rail scale's load-bearing structure, typically at both ends of the track and in the mid-span area, to ensure a reasonable distribution of load among the sensors. The lateral limit support foundation is used to install lateral limit devices, which restrict the lateral displacement of the freight car and prevent uneven stress on the sensors due to lateral vibration or off-center loading. The spacing of the lateral limit supports needs to be optimized based on parameters such as track length, freight car wheelbase, and load-bearing structure stiffness. Generally, a pair of limit supports is installed within 1 / 4 to 1 / 3 of the track length to achieve uniform force transmission.

[0041] Furthermore, the spacing of the lateral limit supports should meet the following requirements: In a tippler weighbridge with a track length of 16m, the spacing of the lateral limit supports is typically controlled between 4m and 6m to ensure that the lateral displacement of the freight car does not exceed ±5mm when passing through, conforming to the technical standard that the deflection of the weighbridge's load-bearing structure should not exceed 1‰. The installation position of the sensor foundation should ensure the linear output of the sensor within its maximum weighing range (e.g., 50t), and its installation error should be controlled within ±1mm to avoid weighing errors caused by installation deviations.

[0042] Specifically, this step is mainly applied to the renovation of track scale systems on dedicated railway lines, especially in scenarios where loaded and empty cars are weighed before and after unloading by the tippler. By rationally arranging sensors and lateral limit supports within the pit, the problem of insufficient rigidity of the load-bearing structure can be effectively addressed, improving the stability of the track scale during long-term use and meeting the verification requirements for medium accuracy class (Level III) and ordinary accuracy class (Level IV).

[0043] Specifically, this step, through structural optimization, significantly improves the uniformity of force transmission during the weighing process of freight cars on the rail scale, reduces weighing errors caused by deformation of the load-bearing structure, and improves the long-term stability and data reliability of the system, providing a solid foundation for subsequent automatic matching and remote monitoring of loaded and empty car data.

[0044] S2 is equipped with a potentiometer-less sensor junction box and an intelligent instrument, which enables analog-to-digital conversion, automatic addressing, and parameter correction of the weighing sensor.

[0045] Specifically, this step involves replacing the traditional potentiometer-type junction box with a potentiometer-less junction box and upgrading the original weighing instrument to an intelligent instrument with analog-to-digital conversion, automatic addressing, and parameter correction functions, thereby achieving efficient processing and dynamic compensation of the weighing sensor signal.

[0046] Furthermore, the potentiometer-less sensor junction box adopts an integrated design, eliminating the traditional manual potentiometer adjustment step. Instead, it directly transmits the analog signals from each sensor to the smart instrument via built-in signal conditioning circuitry and a digital interface. The smart instrument incorporates a high-precision analog-to-digital converter (ADC) module with a sampling accuracy typically no less than 16 bits and a sampling frequency that can be set to over 1000Hz to ensure real-time response and high-resolution acquisition of sensor output signals. For automatic addressing, the smart instrument interacts with each sensor via CAN bus or RS485 communication protocol, enabling it to identify and locate the installation position of each sensor and achieve independent acquisition and processing of multi-channel sensor data.

[0047] Furthermore, the smart instrument possesses an adaptive compensation algorithm that can automatically calibrate based on the sensor's output characteristics. For example, when the sensor experiences zero-point drift due to changes in ambient temperature or long-term use, the instrument can adjust its calibration based on a preset correction formula. By combining actual weighing data with theoretical values ​​for dynamic compensation, systematic errors are eliminated. In addition, the intelligent instrument also supports functions such as automatic angle difference calibration, automatic fault alarm, and sensor status detection, which meet the technical requirements of centering accuracy class (III) and ordinary accuracy class (IV) in the verification procedure of JJG781-2019 "Digital Indicating Rail Scale".

[0048] Specifically, this step mainly involves modifying the tippler's track scale to enable stable and reliable weighing of empty wagons after unloading. The automatic correction function of the intelligent instrument effectively avoids weighing data drift caused by changes in the deflection of the load-bearing structure, improving the overall measurement accuracy and long-term stability of the system. This technical solution is not only applicable to the railway freight car weighing system in this project but can also be replicated and applied to other similar scenarios, such as the automated weighing management of bulk commodities like coal and cement.

[0049] S3, set up a digital indicating track scale as the control scale, and use the temporary benchmarking function of freight cars to perform a traceability comparison between the tipper track scale and the digital indicating track scale.

[0050] Specifically, the technical implementation of this step is based on the JJG781-2019 "Verification Procedure for Digital Indicating Rail Scales", which combines the structural characteristics and data acquisition mechanism of the rail scale system to ensure the consistency of the measurement values ​​of the two rail scales under different working conditions.

[0051] Furthermore, the digital indicating rail scale, as a control weighing instrument, is structurally designed to meet the requirements of medium accuracy class (Level III), with a maximum permissible error of ±0.5e (where e is the verification scale division). In this project, its verification scale division is set as follows: That is, in Under the specified graduation unit, its maximum permissible error is ±50kg. This rail scale features automatic angular error calibration, automatic sensor status detection, and automatic fault alarm functions; its weighing data can be used as a standard reference value. In actual operation, several railway freight cars with known loads (such as coal freight cars loaded with standard weights or of known weight) are selected as temporary benchmark cars, and weighed on both the digital indicating rail scale and the tippler rail scale. The output data are collected and compared for analysis.

[0052] Furthermore, the tippler track scale, after modification, is used for weighing empty cars, with a maximum weighing capacity of [missing information]. The verification scale value is It meets the requirements of ordinary accuracy class (Level IV), with a maximum permissible error of ±1e. The relative error can be calculated by comparing the weighing results of the two rail scales on the same freight car, using the following formula: ; in, This is the weighing value of the tippler track scale. The weighing value of the rail scale is indicated digitally. If the relative error is within the allowable range, it indicates that the weighing performance of the tippler rail scale is stable and can continue to be used; if it exceeds the error range, calibration or structural optimization is required.

[0053] Specifically, this step is mainly used for the periodic calibration and anomaly data investigation of the rail scale system. During coal transportation and unloading, loaded and empty cars are weighed on digital indicating rail scales and tipper rail scales, respectively. The weighing management software identifies the car number and automatically matches the data to calculate the net load weight. By establishing temporary benchmarks for comparison, it can be verified whether there is any gradual drift in the tipper rail scale during long-term use, ensuring its accuracy in weighing empty cars.

[0054] Specifically, by comparing and tracing the measurement values, the overall measurement accuracy and data reliability of the rail scale system have been effectively improved, providing a solid foundation for data integration with the fuel management system. At the same time, the risk of errors caused by manual intervention has been reduced, and the efficiency of coal unloading and the level of intelligent measurement management have been improved.

[0055] Furthermore, S3 includes: S31 is periodically compared and verified using M-level standard weights.

[0056] Specifically, this step is mainly applied to the traceability comparison of the measurement values ​​between the digital indicating rail scale and the tippler rail scale, in order to verify their measurement consistency in different service cycles, thereby meeting the technical requirements of the centering accuracy class (Class III) and ordinary accuracy class (Class IV) in the verification procedure of JJG781-2019 "Digital Indicating Rail Scale".

[0057] Furthermore, the comparative verification process employs a static weighing method, where standard weights are sequentially placed within the effective weighing area of ​​the rail scale, and the weighing data of each weight is collected and recorded using a weighing instrument. The M-class standard weights are standards specified in national metrological standards, with a maximum permissible error of ±0.5e (e being the verification scale division). In this project, the weight specifications are 1.0t or 0.5t, suitable for medium-range calibration of the rail scale. In actual operation, the weights are evenly distributed in the weighing area according to the load-bearing structural distribution characteristics of the rail scale to simulate the actual stress state of the freight car on the rail scale, ensuring the representativeness of the calibration results.

[0058] Furthermore, according to the JJG781-2019 standard, the maximum permissible error for the medium accuracy class (Level III) of digital indicating rail scales is ±0.5e, while the permissible error for the ordinary accuracy class (Level IV) of tippler rail scales is ±1.0e. During the comparison process, if the difference in output error between the two rail scales under the same weight loading exceeds the permissible range, the system needs to be adjusted or repaired. In addition, the placement of the weights, the loading sequence, and the number of repetitions must all comply with the operating procedures in the "Verification Standard for Digital Indicating Rail Scales" to ensure the comparability and repeatability of the data.

[0059] Specifically, this comparative verification is typically performed for the first time after the rail scale is installed or overhauled, and is subsequently performed periodically throughout its lifecycle, such as quarterly or semi-annually. This step effectively identifies systematic errors in the rail scale caused by factors such as deformation of the load-bearing structure, sensor aging, and instrument drift, providing a reliable verification basis for subsequent automatic matching weighing management software.

[0060] Specifically, by periodically comparing standard weights, the measurement value traceability of the rail scale system can be realized, ensuring that it maintains measurement accuracy and stability during long-term operation. This will improve the data credibility of Huaneng Huaiyin No. 2 Power Generation Co., Ltd. in coal transportation settlement, reduce economic losses caused by weighing errors, and provide technical support for railway transportation safety.

[0061] S32 uses a T8 type weight weighing vehicle to perform on-site testing and generate traceability comparison records of measurement values.

[0062] Specifically, this step is mainly used to compare the values ​​of digital indicating rail scales and tippler rail scales to verify whether their metrological performance meets the requirements of relevant national verification regulations.

[0063] Furthermore, the T8 type weight verification cart is a standardized dynamic weighing and calibration device, designed to meet the technical requirements for control weighing instruments in the JJG781-2019 "Digital Indicating Rail Scale" verification procedure. This verification cart collects weighing data by simulating a standard load distribution as it travels at a constant speed on the track, sequentially passing through the effective weighing area of ​​the rail scale under test. In this project, the T8 type verification cart was used to verify a digital indicating rail scale (maximum weighing capacity 50t, calibration scale division value...). ) and tippler track scale (maximum weighing capacity 50t, verification scale value) On-site comparative testing is conducted. During the testing process, the weighing vehicle passes through the track scale at a specified speed (usually 5~25km / h). The system automatically records the weighing response values ​​at different speeds and compares them with the standard load values ​​to generate error curves and comparison reports.

[0064] Furthermore, the load configuration of the T8 type weight weighing vehicle must meet the usage requirements for control weighing instruments in JJG781-2019, and its standard load error range should be controlled within the allowable error range. Specifically, digital indicating rail scales must meet the technical requirements of medium accuracy class (Level III), with a maximum allowable error of ±0.3%; while tippler rail scales must meet the technical requirements of ordinary accuracy class (Level IV), with a maximum allowable error of ±0.5%. Through comparative testing with the T8 type weighing vehicle, the linearity, repeatability, and stability of the rail scales under actual operating conditions can be verified, ensuring that errors will not accumulate due to deformation of the load-bearing structure or aging of sensors during long-term use.

[0065] Specifically, this step is mainly performed after the installation and commissioning of the rail scale equipment, as well as during periodic verification. Through on-site testing using the T8-type weighted weighing vehicle, the measurement values ​​of the rail scale system can be traced, ensuring that its measurement data has legal validity and traceability in key areas such as fuel management and trade settlement. Furthermore, this step can also be used for cross-comparison between rail scales to verify system consistency, providing a reliable foundation for subsequent automatic data matching and remote monitoring.

[0066] Specifically, the use of a T8-type weight-based weighing vehicle for on-site testing not only improved the measurement accuracy and stability of the rail scale system but also effectively avoided weighing errors caused by insufficient rigidity of the load-bearing structure. By generating traceability and comparison records, detailed technical evidence can be provided for project acceptance, metrological certification, and subsequent maintenance, ensuring that the system complies with national metrological regulations and enhancing the authority and credibility of Huaneng Huaiyin Power Plant in coal transportation measurement.

[0067] S4 executes a progressive error compensation algorithm, which dynamically compensates for empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift.

[0068] Specifically, the algorithm is based on the automatic correction function of the smart instrument. By collecting and analyzing empty vehicle weighing data in real time and combining it with historical data trend models, it dynamically compensates for the current weighing results, thereby improving the accuracy and stability of empty vehicle weighing.

[0069] Furthermore, the algorithm first collects empty vehicle weighing data using an intelligent weighing instrument. The instrument's built-in analog-to-digital converter digitizes the analog signals output by each sensor and identifies the working status of each sensor through an automatic addressing function. After each empty vehicle weighing, the system compares the current weighing value with historical weighing data and calculates the deviation. The formula for calculating the deviation is: ; in, This indicates the deviation between the current weighing value and the reference value. This is the current empty vehicle weighing value. This is the baseline empty vehicle weight value set for the system. If the deviation exceeds a set threshold (e.g., the maximum permissible error of 0.5%), an error compensation mechanism is triggered. An adaptive filtering algorithm corrects the sensor output, and the compensation formula is: ; in, This is the compensation coefficient, set according to the sensor type and system calibration results, and typically ranges from [value range missing]. This is to avoid overcompensation leading to system instability.

[0070] Furthermore, the maximum weighing capacity of the tippler track scale used in this system is... The verification scale value is Its empty vehicle weighing error must meet the requirements of the ordinary accuracy class (Level IV) in the verification procedure of JJG781-2019 "Digital Indicating Rail Scale", that is, the maximum permissible error is The compensation frequency of the error compensation algorithm can be set according to the system operating status to be every [number] times. Once every minute, the compensation response time shall not exceed [time limit]. This ensures real-time performance and system stability.

[0071] Specifically, this algorithm is mainly used for weighing empty wagons after unloading from the tippler. Because the tippler's load-bearing structure lacks rigidity, it is prone to structural deformation after long-term use, leading to sensor output drift. Through progressive error compensation, the system can continuously correct the empty wagon weighing data without stopping the machine or manual intervention, ensuring its matching accuracy with the loaded wagon weighing data, thereby accurately calculating the net load weight of each wagon.

[0072] Specifically, the technical effect of this step is to significantly improve the long-term stability of empty car weighing, reduce the frequency of manual calibration, reduce measurement errors caused by data drift, provide reliable assurance for the data accuracy of the power plant fuel management system, and meet national metrological standards and railway transportation safety supervision requirements.

[0073] Furthermore, S4 includes: S41, calculate the compensation coefficient based on the linear change trend of the sensor output.

[0074] Specifically, this step mainly addresses the problem of nonlinear drift in the output of tippler track scales caused by factors such as insufficient rigidity of the load-bearing structure, sensor aging, or changes in environmental temperature and humidity during use. By analyzing the linear change trend of the sensor output signal, a compensation model is established to dynamically correct the weighing data and improve the measurement reliability of the system.

[0075] Specifically, this step first collects multiple sets of sensor output signals under standard loads, forming load-output data pairs. In some implementations, calibration can be performed using a T8-type weight weighing vehicle or M-level standard weights provided by the National Rail Weighing Station to ensure the authority and traceability of the data. Subsequently, the collected data is fitted using the least squares method or other linear fitting algorithms to establish a linear relationship model between the sensor output and the actual load. If there is a nonlinear deviation in the sensor output, its linear trend is further extracted, and the compensation coefficient is calculated. It is used to correct the output signal during the actual weighing process.

[0076] Furthermore, according to the verification procedure JJG781-2019 "Digital Indicating Rail Scales", the maximum permissible error for rail scales at medium accuracy class (Level III) is ±0.3%, while it is ±0.5% at ordinary accuracy class (Level IV). The calculation of the compensation coefficient must ensure that the system error after error correction is controlled within the above standard range. In addition, the output linearity of the sensor should be controlled within 0.5% to ensure the accuracy of the fitted model.

[0077] Specifically, this step is mainly used in the empty car weighing system of the tippler track scale. Because the load-bearing structure of the tippler has low rigidity, the sensors are prone to gradual drift during long-term use. By periodically collecting standard load data and calculating compensation coefficients, the system errors caused by structural deformation or sensor aging can be effectively corrected, ensuring the accuracy of empty car weighing data and thus improving the reliability of automatic matching of loaded and empty car data.

[0078] Specifically, the dynamic compensation mechanism significantly reduces the accumulation of errors in the rail scale over its service life, improving the long-term stability of the weighing system. Simultaneously, the introduction of the compensation coefficient provides a mathematical basis for subsequent data processing in the weighing management software, enhancing the system's adaptability to different vehicle types and operating conditions, and serving as a crucial technical support for achieving automated and intelligent weighing management.

[0079] S42 uses the distributed analog-to-digital conversion module of the smart instrument to independently compensate and correct the output of each sensor.

[0080] Specifically, this step is based on a distributed architecture for sensor signal acquisition and processing, combined with the adaptive compensation algorithm of the smart instrument, to achieve independent correction of the output signals of each sensor, thereby effectively eliminating system errors caused by factors such as sensor aging, installation deviation, and temperature drift.

[0081] Furthermore, a distributed analog-to-digital conversion module is deployed at the output of each weighing sensor, connecting to the smart instrument via a digital communication bus (such as RS485, CAN, or Modbus) to form a point-to-point data acquisition and processing structure. The raw analog signal from each sensor undergoes local analog-to-digital conversion (ADC) and is uploaded to the smart instrument for processing in real time. The smart instrument's built-in compensation and correction algorithms can perform independent linearization, temperature compensation, and zero-point drift correction on the output of each sensor. For example, for nonlinear errors in the sensor output, polynomial fitting or lookup table methods can be used for correction; the correction model can be expressed as: ; in, For the first Only the sensor's raw output voltage, The corrected output voltage, These are the correction coefficients obtained by fitting calibration data. This correction process is implemented in the smart instrument, eliminating the need for a central controller and improving the system's real-time performance and reliability.

[0082] Furthermore, the weighbridge for the tippler in this project is equipped with four column-type load cells, with a maximum weighing capacity of 50t and a calibration scale value of [value missing]. It meets the technical requirements of ordinary accuracy class (Level IV) in the verification procedure of JJG781-2019 "Digital Indicating Rail Scale". The intelligent instrument supports automatic addressing function, can identify and connect the communication addresses of each sensor, and ensure the integrity and accuracy of data acquisition.

[0083] Specifically, this step is mainly used in the empty car weighing stage. The unloaded trucks are weighed using the tippler's track scale, and the net weight value is automatically matched by combining the weighing data of the loaded trucks. Since the load-bearing structure of the tippler has limited rigidity, the sensor output is easily affected by structural deformation. Therefore, independent compensation correction can significantly improve the stability and repeatability of the system under dynamic weighing conditions.

[0084] Specifically, this step effectively avoids the problem of system error accumulation caused by sensor output drift in traditional rail scales, improves the long-term consistency and reliability of weighing data, and provides a solid data foundation for realizing automated weighing management.

[0085] S5, through limit switches, is linked with the automatic vehicle number recognition system and the rebalancing machine control system to control the rebalancing machine to pull the heavy-duty freight car to the effective weighing area of ​​the rail scale.

[0086] Specifically, this step is technically implemented by integrating mechanical position feedback with an automated control system, combined with vehicle number recognition technology, to ensure the positioning accuracy of the truck and the real-time response of the system during the weighing process.

[0087] Furthermore, limit switches are installed at specific locations at the entrance and exit of the weighbridge to detect whether the truck wheels have entered or left the effective weighing area. When the load cell towing a heavy-duty truck approaches the weighbridge, the automatic vehicle identification system obtains the truck's license plate number via RFID or video recognition technology and transmits this information to the weighing management system in real time. The system determines whether the truck is a vehicle to be weighed based on the license plate number and sends a traction command to the load cell control system. Upon receiving the command, the load cell controls the start / stop and speed adjustment of the traction motor via a PLC or industrial control computer, ensuring the truck enters the effective weighing area of ​​the weighbridge at a constant speed (typically controlled within the range of 0.5–1.5 m / s). When the truck wheels press against the limit switches, the system confirms that it has entered the weighing area and triggers the weighing sensors to begin collecting data.

[0088] Furthermore, the installation position of the limit switches needs to be precisely designed according to the load-bearing structure and sensor distribution of the rail scale. They are typically placed 1-2 meters before and after the effective weighing area to ensure that the freight truck is fully inside the weighing area before weighing begins. The vehicle number recognition system should have a recognition distance of no less than 5 meters and a recognition accuracy rate of over 99.5% to meet the requirements for automated weighing systems in the JJG781-2019 "Digital Indicating Rail Scale" verification procedure. The rebalancing machine control system should have a speed closed-loop control function, and the traction speed error should be controlled within ±0.2 m / s to reduce impact errors during dynamic weighing.

[0089] Specifically, this step is widely used in coal unloading operations on dedicated railway lines, especially in tippler systems, to achieve automatic weighing and data matching between heavily loaded freight cars and empty cars after unloading. This linkage mechanism effectively avoids errors caused by manual intervention, improving the reliability of weighing data and the efficiency of system operation.

[0090] Specifically, this step automates and enhances the precision of the truck weighing process, ensuring the integrity and accuracy of the weighing data collection. This provides a reliable data foundation for subsequent net weight calculations and integration with the fuel management system, while also improving the overall intelligence level and operational stability of the system.

[0091] The S6 integrates the weighing management software with the fuel management system, enabling remote synchronous transmission of weighing data, vehicle number information, and video monitoring data.

[0092] Specifically, this step integrates multi-source heterogeneous data from digital indicator rail scales for weighing loaded vehicles, tipper rail scales for weighing empty vehicles, vehicle number recognition systems, and video monitoring systems by building a unified data interface and communication protocol, and transmits the data to the fuel management system platform via the network to achieve centralized data processing and remote monitoring.

[0093] Furthermore, this step relies on the development and system integration of weighing management software. The weighing management software links with a vehicle identification system (such as OCR recognition or RFID reading) to acquire truck license plate information in real time and match it with the weighing data collected by the rail scale. Simultaneously, the video monitoring system transmits image information of the trucks during the weighing process to the weighing management software via RTSP or similar streaming media protocols for subsequent weighing data verification and anomaly analysis. The data matching algorithm uses the vehicle license plate as a unique identifier and employs a dual verification mechanism of timestamp and vehicle license plate number to ensure accurate correspondence between loaded and empty truck data, thereby calculating the net weight of each truck.

[0094] Furthermore, the transmission of weighing data must meet the accuracy requirements for Class III and Class IV rail scales in the JJG781-2019 "Digital Indicating Rail Scales" verification procedure, namely, the error range of the medium accuracy class for digital indicating rail scales is ±0.3%, and the error range of the ordinary accuracy class for tipper rail scales is ±1.0%. The vehicle number recognition system should have an accuracy rate of no less than 99.5%, and the video monitoring system must support real-time video streaming at least 1080P resolution and 30 frames per second, and have storage and playback functions. Data transmission latency should be controlled within 500ms to ensure the real-time response of the system.

[0095] Specifically, this step is widely used in the measurement and management of coal transportation, especially in the process of unloading coal on dedicated railway lines. Through remote synchronous transmission, it can realize functions such as automatic archiving of freight car weighing data, abnormal alarms, and data traceability, which meets the requirements of China Railway Shanghai Bureau Group Co., Ltd. for providing weighbridge slips and video images for returning empty cars, thereby ensuring transportation safety and measurement impartiality.

[0096] Specifically, this step effectively improves the accuracy and completeness of weighing data, reduces matching errors caused by human intervention, increases unloading efficiency, and provides a reliable basis for data-driven decision-making in the fuel management system, demonstrating significant engineering practical value and economic benefits.

[0097] This invention provides an optimization method for an empty freight car weighing system. By strengthening the rigidity of the load-bearing structure to optimize the force transmission path, configuring an intelligent sensor network to achieve high-precision signal acquisition and self-correction, establishing a traceable measurement benchmark based on a control scale, and executing a progressive dynamic error compensation algorithm, this method effectively solves the inherent system error and data drift problems caused by insufficient rigidity of the tippler track scale structure. Furthermore, this method achieves automatic and accurate positioning through the linkage of limit switches and a car number recognition system, and interfaces the weighing management software with the fuel management system. This realizes integrated collaborative optimization of the entire process from vehicle guidance, data acquisition, error correction to remote transmission, significantly improving the measurement accuracy, long-term stability, and system automation level of empty car weighing.

[0098] Example 2 To achieve the above invention, embodiments of the present invention also provide an application scenario for optimizing a railway freight car empty car weighing system, including: Specifically, based on the site conditions, the top platforms currently installed on each heavy-duty vehicle line have been idle. After exploration, it was found that the location is suitable for installing a digital indicating rail scale with a graduation value of 20kg and a platform length of 13m. The existing foundation can be utilized. Only two anti-climb foundations (4.7m×2.8m×0.9m) need to be added at each section (which meets the technical requirements stipulated by the national standard for rail scales). Then, eight sensor support foundations need to be added in the foundation pit to install the digital indicating electronic rail scale. This can reduce the investment cost of building a new rail scale foundation. The rail scale is a trade settlement rail scale, which has been calibrated by the Shanghai branch of the National Rail Scale Metrology Station and issued a calibration certificate.

[0099] Furthermore, since the load-bearing structure of the tippler track scale is borrowed from the tippler's load-bearing frame, the deformation and aging of the current load-bearing frame are no longer sufficient to guarantee the weighing accuracy when carrying a loaded car. However, the deformation of the load-bearing frame when carrying an empty car will have a relatively smaller impact on the weighing accuracy. Therefore, the original tippler track scale can be designated as a process scale for empty car inspection (not subject to mandatory verification). Although the Shanghai branch of the National Track Scale Metrology Station will no longer verify the process scale and issue verification certificates, the process scale can use a verified digital indicating track scale to trace the value through the value ratio method. Its error can be kept to less than 100 kg when weighing an empty car.

[0100] Furthermore, minor repairs were carried out on the existing tippler track scale, including replacing the adjustable potentiometer, replacing the weighing instrument, and adjusting the limit device, to ensure that empty cars can be detected.

[0101] Furthermore, two sets of management software were developed to automatically match the weighing data of loaded and empty cars. This allows each set of loaded and empty car weighing systems to automatically match the weighing data of loaded cars with the weighing data of empty cars according to the vehicle serial number, thereby obtaining the net weight of coal in each freight car.

[0102] Specifically, the on-site operation procedure for this solution is as follows: Using video monitoring, the operator operates the readjustment machine to pull the loaded wagons to the weighing area of ​​the digital indicator scale on the loaded wagon line for weighing. Then, the loaded wagons are pulled to the tippler for unloading. After unloading, the tippler scale is used to weigh the empty wagons, and the dispatching platform is used to move the empty wagons to the empty wagon line. This process is repeated until all loaded wagons are unloaded. Finally, the automatic matching button is clicked to automatically generate the actual net weight of the entire freight train.

[0103] The application scenario of the railway freight car empty car weighing system optimization method provided by this invention, in which a dual-weighing architecture of a "high-precision trade settlement scale" and a "modified process scale" working in tandem is constructed, effectively solving the problems of measurement inaccuracy and inability to meet mandatory verification requirements caused by the structural deformation of a single tippler track scale. A traceable measurement benchmark is established using existing on-site facilities, and the original equipment is specifically modified and upgraded with intelligence. Finally, through dedicated management software, fully automated and accurate matching of loaded and empty car weighing data and net weight calculation are achieved. This significantly improves the automation level, data reliability, and operational efficiency of the entire coal unloading and metering process, while ensuring the legality and accuracy of trade settlement.

[0104] Example 3 To achieve the above invention, such as Figure 2 As shown, this embodiment also provides a railway freight car empty car weighing system optimization device 10, which includes: The stiffness enhancement module 100 is used to enhance the stiffness of the load-bearing structure of the tippler track scale and add a lateral limiting support foundation to optimize the force transmission path.

[0105] The sensor configuration module 200 is used to configure potentiometer-less sensor junction boxes and smart meters, and to realize analog-to-digital conversion, automatic addressing and parameter correction of weighing sensors through smart meters.

[0106] The control weighing instrument setting module 300 is used to set the digital indicating rail scale as the control weighing instrument and to use the temporary benchmark setting function of freight cars to perform traceability comparison between the tipper rail scale and the digital indicating rail scale.

[0107] The error compensation execution module 400 is used to execute a progressive error compensation algorithm, which dynamically compensates the empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift.

[0108] In one embodiment of the present invention, it further includes: a limit switch linkage module, used to link with the vehicle number automatic identification system and the rebalancing machine control system through the limit switch, and control the rebalancing machine to pull the heavy-duty freight car to the effective weighing area of ​​the rail scale; and a data synchronization module, used to interface the weighing management software with the fuel management system to realize the remote synchronous transmission of weighing data, vehicle number information and video monitoring data.

[0109] This invention provides an optimization device for an empty freight car weighing system. It enhances the rigidity of the load-bearing structure through a stiffness strengthening module to optimize the mechanical transmission path; a sensor configuration module constructs an intelligent sensing network to achieve high-precision signal acquisition and self-correction; a weighing instrument setting module establishes a traceable metrological benchmark to ensure consistent measurement values; and an error compensation execution module implements a dynamic algorithm to suppress data drift. This effectively solves the problems of low weighing accuracy and poor long-term stability caused by structural deformation, signal interference, and missing benchmarks in existing technologies. Combined with a limit switch linkage and data synchronization module, this device achieves fully automated and collaborative control from vehicle guidance, accurate weighing, error compensation to remote data integration, significantly improving the accuracy of empty car weighing, system robustness, and the level of intelligent management.

[0110] To implement the methods of the above embodiments, the present invention also provides a computer device, such as... Figure 3 As shown, the computer device 600 includes a memory 601 and a processor 602; wherein, the processor 602 reads the executable program code stored in the memory 601 to run a program corresponding to the executable program code, so as to implement the various steps of the railway freight car empty car weighing system optimization method described above.

[0111] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements an optimization method for an empty railway freight car weighing system as described in the foregoing embodiments.

[0112] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0113] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. An optimization method for an empty railway freight car weighing system, characterized in that, include: S1, the load-bearing structure of the tippler track scale is reinforced and modified to improve its rigidity, and a lateral limiting support foundation is added to optimize the force transmission path. S2 is equipped with a potentiometer-less sensor junction box and an intelligent meter, which enables analog-to-digital conversion, automatic addressing, and parameter correction of the weighing sensor. S3, set up a digital indicator rail scale as a control weighing instrument, and use the temporary standard setting function of freight cars to conduct a traceability comparison of the value of the tipper rail scale and the digital indicator rail scale; S4 executes a progressive error compensation algorithm, which dynamically compensates for empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift.

2. The method as described in claim 1, characterized in that, The aforementioned modification to strengthen the load-bearing structure of the tippler track scale, including the addition of lateral limiting support foundations to optimize the force transmission path, includes: S11, anti-climb foundations are added to both ends of the original top vehicle platform foundation to prevent track displacement; S12, sensor bearing foundation and lateral limiting support foundation are set in the foundation pit, and the force transmission path is evenly distributed by optimizing the spacing of the lateral limiting supports.

3. The method as described in claim 1, characterized in that, The setting of a digital indicating rail scale as a control weighing instrument, and the use of the temporary benchmarking function for freight cars to perform a traceability comparison between the tipper rail scale and the digital indicating rail scale, includes: S31 is verified through periodic comparison using M-level standard weights; S32 uses a T8 type weight weighing vehicle to perform on-site testing and generate traceability comparison records of measurement values.

4. The method as described in claim 1, characterized in that, The progressive error compensation algorithm, based on the automatic correction function of the smart instrument, dynamically compensates the empty vehicle weighing data to eliminate data drift, including: S41, calculate the compensation coefficient based on the linear change trend of the sensor output; S42 uses the distributed analog-to-digital conversion module of the smart instrument to independently compensate and correct the output of each sensor.

5. The method as described in claim 1, characterized in that, Also includes: S5, through the limit switch, is linked with the automatic vehicle number recognition system and the rebalancing machine control system to control the rebalancing machine to pull the heavy-duty freight car to the effective weighing area of ​​the rail scale; The S6 integrates the weighing management software with the fuel management system, enabling remote synchronous transmission of weighing data, vehicle number information, and video monitoring data.

6. An optimization device for an empty railway freight car weighing system, characterized in that, include: The stiffness enhancement module is used to enhance the stiffness of the load-bearing structure of the tippler track scale and add lateral limiting support foundations to optimize the force transmission path. The sensor configuration module is used to configure potentiometer-less sensor junction boxes and smart meters, and to realize analog-to-digital conversion, automatic addressing and parameter correction of weighing sensors through smart meters; The control weighing instrument setting module is used to set the digital indicating rail scale as the control weighing instrument and to use the temporary benchmark setting function of freight cars to perform traceability comparison between the tipper rail scale and the digital indicating rail scale. The error compensation execution module is used to execute a progressive error compensation algorithm, which dynamically compensates the empty vehicle weighing data based on the automatic correction function of the smart instrument to eliminate data drift.

7. The apparatus as claimed in claim 6, characterized in that, Also includes: The limit switch linkage module is used to link the limit switch with the automatic vehicle number recognition system and the rebalancing machine control system to control the rebalancing machine to pull the heavy-duty freight car to the effective weighing area of ​​the rail scale. The data synchronization module is used to interface the weighing management software with the fuel management system to achieve remote synchronous transmission of weighing data, vehicle number information and video monitoring data.

8. An electronic device, comprising: processor; The memory stores executable instructions; when the processor executes the instructions, it implements the optimization method for an empty railway freight car weighing system as described in any one of claims 1-5.

9. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements an optimization method for an empty railway freight car weighing system as claimed in any one of claims 1-5.

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