Vehicle weighing method, device, equipment and storage medium based on dynamic track scale

Abstract

The present application discloses a vehicle weighing method, device, equipment and storage medium based on a dynamic track scale, and relates to the field of railway transportation detection technology. The vehicle weighing method based on the dynamic track scale includes: collecting the AD values ​​of two signals of the dynamic track scale; judging whether the vehicle is on the scale according to the jump of the AD values ​​of the two signals, and obtaining the vehicle weighing result; when the vehicle weighing result is that the vehicle has been weighed, analyzing and calculating the AD values ​​of the two signals during each two zero returns of the scale to obtain the vehicle weight. The present application can still accurately capture effective signals in the case of data fluctuations to ensure the accuracy of the weighing results. Through the precise signal acquisition and calculation process, the reliability of the weighing data is guaranteed, the entire process realizes automated operation, reduces human intervention, and improves the real-time performance and efficiency of the system.

Description

Technical Field

[0001] The present application relates to the field of railway transportation detection technology, and in particular to a vehicle weighing method, device, equipment and storage medium based on a dynamic track scale. Background Art

[0002] With the rapid development of railway transportation, dynamic track scales are increasingly used in weighing items. Dynamic track scales are a type of equipment that can measure in real time while the train is running, and can accurately obtain the weight of the vehicle without stopping.

[0003] The current dynamic track scale technology usually uses two sensor signals to determine the upper and lower scale states of the vehicle by analyzing the fluctuations of the signals. These methods generally use zero-point data during the empty scale period to determine and calculate the vehicle type, and use algorithms such as slope calculation and average value invariance to find the effective measurement section.

[0004] However, existing practices are prone to incorrect judgments and large measurement errors when data fluctuates greatly, vehicle models change frequently, or heavy and light vehicles are mixed. Existing dynamic track scale measurement methods have problems with insufficient accuracy and poor adaptability. When data fluctuates greatly, it is often difficult to accurately judge the upper and lower scale states of the vehicle, resulting in weighing errors. In addition, with the diversification of railway transportation, the existing methods are unable to respond flexibly to different vehicle models and car combinations, resulting in a decrease in accuracy and reliability. Therefore, how to accurately weigh vehicles when data fluctuates has become a problem that needs to be solved urgently.

[0005] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0006] The purpose of this application is to provide a vehicle weighing method, device, equipment and storage medium based on a dynamic track scale, aiming to solve the technical problem of how to accurately weigh a vehicle when data fluctuates.

[0007] To achieve the above objectives, the present application proposes a vehicle weighing method based on a dynamic track scale, the method comprising:

[0008] Collect the AD values ​​of two signals of dynamic track scale;

[0009] Determine whether the vehicle is on the scale according to the jump of the AD values ​​of the two signals, and obtain the vehicle on the scale result;

[0010] When the vehicle weighing result is that the vehicle has been weighed, the AD values ​​of the two signals during each two zeroing periods of the weighing instrument are analyzed and calculated to obtain the vehicle weight.

[0011] In one embodiment, when the vehicle weighing result is that the vehicle has been weighed, the step of analyzing and calculating the AD values ​​of the two signals during each two zeroing periods of the weighing instrument to obtain the vehicle weight includes:

[0012] When the vehicle weighing result is that the vehicle has been weighed, the target two-way signal AD value is determined according to the time when the scale returns to zero twice, and the target two-way signal AD value includes left-way data and right-way data;

[0013] Obtaining sum data according to the left-path data and the right-path data, and filtering the sum data to obtain filtered sum data;

[0014] Analyzing and processing the left-channel data, the right-channel data, the sum data, and the filtered sum data to obtain a target metering effective section;

[0015] Obtaining the target and data corresponding to the target measurement effective section according to the sum data;

[0016] The AD values ​​of the target and data are averaged and calibrated to obtain the vehicle weight.

[0017] In one embodiment, the step of analyzing and processing the left-channel data, the right-channel data, the sum data, and the filtered sum data to obtain a target metering effective segment includes:

[0018] Analyzing the filtered data from a first direction and a second direction respectively to obtain a first target valid segment, wherein the first direction is opposite to the second direction;

[0019] Within the first target valid segment, analyzing the left-path data, the right-path data and the sum data to obtain a second target valid segment;

[0020] performing a de-fluctuation process on the second target effective segment to obtain a reference measurement effective segment;

[0021] According to the waveform difference between the locomotive head and the carriage, the portion corresponding to the carriage in the reference metering effective section is selected as the target metering effective section.

[0022] In one embodiment, the step of analyzing the filtered and data from the first direction and the second direction to obtain the first target valid segment includes:

[0023] Analyzing the filtered and data from a first direction to obtain a first rising point;

[0024] Finding a point in the filtered data from the first direction whose AD value is less than a preset multiple of the AD value corresponding to the first rising point, to obtain a first falling point;

[0025] Obtaining a first initial valid segment according to the first ascending point and the first descending point;

[0026] Analyzing the filtered and data from a second direction to obtain a second rising point;

[0027] Find a point in the filtered data from the second direction whose AD value is less than the preset multiple of the AD value corresponding to the second rising point, to obtain a second falling point;

[0028] Obtaining a second initial valid segment according to the second rising point and the second falling point;

[0029] A first target valid segment is obtained according to the first initial valid segment and the second initial valid segment.

[0030] In one embodiment, the first target valid segment includes a first initial valid segment and a second initial valid segment, and the step of analyzing the left-path data, the right-path data, and the sum data within the first target valid segment to obtain the second target valid segment includes:

[0031] Within the first initial valid section, a third rising point is obtained according to the maximum value of the difference between the left-way data and the right-way data, and a third falling point is obtained according to the maximum value of the difference between the right-way data and the left-way data;

[0032] Obtain a third initial valid segment according to the third rising point, the third falling point and the sum data;

[0033] Within the second initial valid section, a fourth rising point is obtained according to the maximum value of the difference between the left-way data and the right-way data, and a fourth falling point is obtained according to the maximum value of the difference between the right-way data and the left-way data;

[0034] Obtaining a fourth initial valid segment according to the fourth rising point, the fourth falling point and the sum data;

[0035] A second target valid segment is obtained according to the third initial valid segment and the fourth initial valid segment.

[0036] In one embodiment, the second target effective segment includes a third initial effective segment and a fourth initial effective segment, and the step of performing a de-fluctuation process on the second target effective segment to obtain a reference measurement effective segment includes:

[0037] Divide the third initial valid segment into a first preset number of segments, and perform a de-fluctuation process on the first preset number of segments to obtain a first left segment and a first right segment;

[0038] Find the maximum AD value in the sum data corresponding to the first left segment, and the corresponding point is the fifth rising point;

[0039] Find the maximum AD value in the sum data corresponding to the first right segment, and the corresponding point is the fifth descending point;

[0040] Obtaining a first metering effective section according to the fifth ascending point and the fifth descending point;

[0041] Divide the fourth initial valid segment into a second preset number of segments, and perform a de-fluctuation process on the second preset number of segments to obtain a second left segment and a second right segment;

[0042] Find the maximum AD value in the sum data corresponding to the second left segment, and its corresponding point is the sixth ascending point;

[0043] Find the maximum AD value in the sum data corresponding to the second right segment, and its corresponding point is the sixth descending point;

[0044] Obtaining a second metering effective section according to the sixth ascending point and the sixth descending point;

[0045] A reference metering valid segment is obtained according to the first metering valid segment and the second metering valid segment.

[0046] In one embodiment, the two-way signal AD values ​​include a first target effective section, a second target effective section and a target measurement effective section. When the vehicle weighing result is that the vehicle has been weighed, the two-way signal AD values ​​during each two zeroing periods of the weighing instrument are analyzed and calculated to obtain the vehicle weight, and the following steps are further included:

[0047] Determine the vehicle weighing time according to the jump of the AD values ​​of the two signals;

[0048] When the AD values ​​of the two signals return to zero and the duration is greater than or equal to the preset time, the vehicle off-balance time is determined;

[0049] According to the AD values ​​of the two signals, the time when the vehicle is on the scale and the time when the vehicle is off the scale, the AD values ​​of the two signals on the scale are obtained;

[0050] Simulating and analyzing the waveform of the two AD values ​​of the scale signals to obtain the rising points and falling points of the data change waveform curve, and obtaining the offline measurement results according to the rising points and the falling points;

[0051] Perform fault analysis based on the offline measurement results.

[0052] In addition, to achieve the above purpose, the present application also proposes a vehicle weighing device based on a dynamic track scale, the device comprising:

[0053] Data acquisition module, used to collect the AD values ​​of two signals of dynamic track scale;

[0054] A weighing determination module is used to determine whether the vehicle is weighed according to the jump of the AD values ​​of the two signals, and obtain a vehicle weighing result;

[0055] The vehicle weighing module is used to analyze and calculate the AD values ​​of the two signals during each two zero returns of the scale to obtain the vehicle weight when the vehicle weighing result is that the vehicle has been weighed.

[0056] In addition, to achieve the above-mentioned objectives, the present application also proposes a vehicle weighing device based on a dynamic track scale, the device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the vehicle weighing method based on a dynamic track scale as described above.

[0057] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the vehicle weighing method based on the dynamic track scale as described above are implemented.

[0058] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the vehicle weighing method based on the dynamic track scale as described above.

[0059] One or more technical solutions proposed in this application have at least the following technical effects:

[0060] Collect the AD values ​​of the two-way signal of the dynamic track scale; judge whether the vehicle is on the scale according to the jump of the AD values ​​of the two-way signal, and obtain the vehicle on the scale result; when the vehicle on the scale result is that it has been on the scale, analyze and calculate the AD values ​​of the two-way signal during each two zero returns of the scale to obtain the vehicle weight. First, the system continuously collects the AD values ​​of the two-way signal of the dynamic track scale. These signals reflect the dynamic state of the vehicle before, during and after the scale is on the scale, ensuring that the data is fully collected while providing sufficient information for subsequent calculations, so that the movement process of the vehicle can be fully grasped. Then, the system accurately identifies the moment when the vehicle is on the scale by monitoring the jump of the signal AD value, thereby distinguishing the state of the vehicle entering the weighing area. This step helps to improve the accuracy of the on-scale detection and avoid missed detection and false detection. Finally, after the vehicle confirms that it is on the scale, the system analyzes and calculates the signal AD value during each two zero returns during the operation of the vehicle to obtain the accurate weight of the vehicle. Even in the case of data fluctuations, the system can still accurately capture effective signals to ensure the accuracy of the weighing results. Through precise signal acquisition and calculation process, the reliability of weighing data is guaranteed, the whole process is automated, human intervention is reduced, and the real-time performance and efficiency of the system are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0062] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0063] Figure 1 A flow chart of a first embodiment of a vehicle weighing method based on a dynamic track scale according to the present application;

[0064] Figure 2 A schematic diagram of an over-weighing waveform provided in Embodiment 1 of the vehicle weighing method based on a dynamic track scale of the present application;

[0065] Figure 3 A schematic diagram of a rough effective segment waveform provided in Embodiment 1 of the vehicle weighing method based on a dynamic track scale of the present application;

[0066] Figure 4 A waveform diagram of a complete effective segment and a metering effective segment provided in Embodiment 1 of the vehicle weighing method based on a dynamic track scale of the present application;

[0067] Figure 5A schematic diagram of a locomotive head waveform provided in Embodiment 1 of the vehicle weighing method based on a dynamic track scale of the present application;

[0068] Figure 6 A flow chart of the second embodiment of the vehicle weighing method based on the dynamic track scale of the present application;

[0069] Figure 7 A schematic diagram of the load on the weighing instrument when the train is moving provided in Embodiment 2 of the vehicle weighing method based on the dynamic track scale of the present application;

[0070] Figure 8 A schematic diagram of a brief process of a vehicle weighing method based on a dynamic track scale provided in Example 2 of the present application;

[0071] Fig. 9 This is a schematic diagram of the module structure of a vehicle weighing device based on a dynamic track scale according to an embodiment of the present application;

[0072] Fig.10 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the vehicle weighing method based on the dynamic track scale in the embodiment of the present application.

[0073] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0074] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0075] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0076] Dynamic track scales are widely used in railway transportation and can accurately weigh trains in real time while they are in motion. However, existing technologies are susceptible to data fluctuations and vehicle type changes, resulting in measurement errors, and have poor adaptability, making it difficult to cope with the diverse needs of railway transportation.

[0077] The main solution of the embodiment of the present application is to monitor the dynamic process of the vehicle by continuously collecting the AD value of the track scale signal to ensure data integrity, and then accurately identify the moment when the vehicle is weighed by detecting the jump of the AD value to improve the detection accuracy. After confirming that the vehicle is weighed, the system analyzes the signal data during the vehicle's driving process to calculate the vehicle's weight, ensuring the accuracy of the weighing result even under data fluctuations.

[0078] It should be noted that the execution subject of the embodiment of the present application may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a measuring system of a dynamic track scale, a dynamic track scale, etc. The following takes the measuring system of a dynamic track scale as an example to illustrate this embodiment and the following embodiments.

[0079] Based on this, the embodiment of the present application provides a vehicle weighing method based on a dynamic track scale, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the vehicle weighing method based on the dynamic track scale of the present application.

[0080] In this embodiment, the vehicle weighing method based on the dynamic track scale includes steps S10 to S30:

[0081] Step S10, collecting AD values ​​of two signals of the dynamic track scale;

[0082] It should be noted that in this embodiment, the system has four weighing sensors, two of which are connected in parallel in the direction perpendicular to the rails, and the other two are connected in parallel, and are recorded as the left path, and the AD values ​​of the two signals are collected in real time. The weighing sensor is installed under the scale body of the track scale, and its function is to convert the detected weight information into an analog electrical signal. When there is no vehicle on the scale, it is recorded as an empty scale state; when the vehicle is weighed, it is recorded as a measuring state. The dynamic track scale is a weighing system for railways or rail transit, which can measure the weight of each carriage in real time when the train passes. The sensor converts the weight information into an analog electrical signal, and then converts it into a digital signal AD value through an analog-to-digital converter (AD converter) for system analysis and processing. The two-way signal AD value refers to the two-way analog signal (Analog Signal) obtained from the dynamic track scale. These signals are converted into digital values ​​(AD values) after the analog-to-digital converter (AD converter). These signals may represent different measurement parameters, such as: Train weight signal: represents the real-time weight information of the train when it passes through the track scale. Other related signals: For example, the vibration, speed or other dynamic characteristics of the track can be measured.

[0083] It is understandable that first of all, it is necessary to ensure that the sensors of the dynamic track scale system are correctly installed under the scale body of the track scale. The weighing sensors of the track scale sense the weight changes when the train passes through the scale body. These sensors can only reflect weight information and convert it into analog electrical signals. Subsequently, these analog electrical signals are processed by analog-to-digital converters (AD converters) to generate digital signal AD values, forming two signals for the left and right channels. These two signals are mainly used to measure the actual weight of the train rather than reflect other dynamic information. Finally, the collected AD values ​​are transmitted to the data processing unit for further analysis and calculation to accurately obtain the dynamic weight data of the train to support real-time monitoring and management.

[0084] Step S20, judging whether the vehicle is on the scale according to the jump of the AD values ​​of the two signals, and obtaining the vehicle on the scale result;

[0085] It should be noted that a jump refers to a rapid change or obvious fluctuation in the signal AD value during the dynamic track scale monitoring process. This jump is usually caused by the sudden change in the weight and motion state of the vehicle when the train passes through the track scale, resulting in obvious fluctuations in the signal detected by the sensor. This jump is the key to determining whether the train is on the scale, because it can reflect the actual passing status and weight of the train. The vehicle on-scale result is based on the analysis results of the jump signal to determine whether the train has passed the track scale, including the vehicle on the scale (that is, the train has passed and the weight data has been effectively collected) and the vehicle not on the scale (that is, the train has not passed and the weight data has not been effectively collected). By judging these two states, the system can make an accurate assessment of the actual situation of the train to ensure the safety and compliance of railway transportation.

[0086] It can be understood that the AD values ​​of the two signals will be collected at the same time to determine the direction of the train on the track scale and determine the complete and effective weight measurement section. When the train is on the track scale, if the left signal jumps first, it means that the train is on the scale from left to right; if the right signal jumps first, it means that the train is on the scale from right to left. In the process of the train passing through the track scale, its weight change will cause a significant jump in the signal AD value, that is, the signal value will rise or fall rapidly in a short period of time. By analyzing these signal jumps, the system can determine whether the train has entered the track scale and the location of the effective measurement section. When the jump signal reaches the set threshold, the system determines that the vehicle is on the scale, indicating that the train weight data has been effectively collected; if the jump signal does not reach the threshold, it is determined that the vehicle is not on the scale, indicating that the weight information of the train has not been successfully collected. This process provides a basis for subsequent vehicle weight monitoring and data analysis, ensuring the safety and accuracy of railway transportation.

[0087] Step S30, when the vehicle weighing result is that the vehicle has been weighed, the AD values ​​of the two signals during each two zeroing periods of the weighing instrument are analyzed and calculated to obtain the vehicle weight.

[0088] It should be noted that "weighed" means that the system confirms that the vehicle has entered the track scale after analyzing the jump of the AD values ​​of the two signals collected, which means that the track scale can accurately measure the weight data of the vehicle. The scale refers to a dynamic track scale equipment that can measure the weight of the train in real time while the train is moving. The dynamic track scale collects the signal data when the vehicle passes and calculates it to obtain the weight of each car. The calculation process is carried out while moving. When the second car passes the scale, the system can analyze the weight of the first car. Whenever the front bogie and rear bogie of a car cross the scale, the system will detect this zero return opportunity and analyze and calculate the data since the last zero return. This calculation obtains the weight of the rear bogie of the previous car and the front bogie of the current car. Specifically, the weight of a car is calculated by adding the current calculated rear bogie data and the last calculated front bogie data. Bogies refer to an important component of railway vehicles used to support the vehicle body and guide the vehicle along the track. Specifically, bogies are a structural frame installed under railway vehicles (such as freight cars, passenger cars, etc.). It carries the weight of the vehicle and contacts the rails through the wheels on it, so that the vehicle can move on the track. In railway freight cars, each carriage usually has two bogies, located at both ends of the carriage, and each bogie is equipped with two wheels. In the measurement method of bogie measurement dynamic track scale, the two axles (one bogie) of each carriage are used as a measurement unit, and the weight of the entire carriage is calculated by measuring the weight of multiple bogies (the weight of one bogie is calculated each time). This measurement method allows the weight of the vehicle to be dynamically measured during the vehicle's travel without the need for the vehicle to stop, which is of great significance for improving the efficiency and safety of railway transportation. Zero return refers to the state when there is no object on the track scale, and the left-way AD value and the right-way AD value collected by the system are close to / less than the left-way zero point and the right-way zero point respectively. (In this embodiment, the most recent 1024 left-road AD and right-road AD data will be saved in a first-in-first-out manner in the empty balance state, and the average of the first 200 data will be used as the zero point of the left and right roads. When the vehicle is weighed and the result is that the vehicle has been weighed, the system will record the left and right road zero points as reference values ​​for judging the return to zero during the vehicle's movement.) The return to zero process occurs when the two bogies of each vehicle cross the scale. Vehicle weight refers to the actual weight of the train or vehicle measured by the track scale equipment. When the vehicle passes through the track scale, the change in the signal AD value reflects the pressure of the vehicle on the track. By analyzing and calculating these data, the system can derive the weight value of the vehicle.

[0089] The sensor data collection is ongoing. When the N+1 section crosses the scale, the weight of the N section is analyzed and calculated. The so-called cross-scale means that the front bogie (front two axles) and the rear bogie (rear two axles) of this section are distributed on both sides of the scale, and no axle is on the scale (equivalent to an empty scale in motion). This is because the distance between the front and rear bogies is greater than the length of the scale. When the cross-scale is an empty scale in motion, the system detects this opportunity and analyzes and calculates the data since the last cross-scale (the last return to zero). This data is the data of the rear bogie of the N section and the front bogie of the N+1 section passing through the scale. The weight of the rear bogie of the N section and the weight of the front bogie of the N+1 section are analyzed and calculated. The weight of the N section is the sum of the weight of its front bogie calculated last time and the weight of its rear bogie calculated this time; the weight of the rear bogie of the N+1 section will be calculated in the next analysis. The so-called bogie measurement is to measure a car section in two sections, and add the two to get the weight of the whole car section. In this way, the length of the scale is shorter, and only one bogie can be on the scale; while the whole car measurement is that the length of the scale is very long, and the whole car section can be placed on the scale. In this way, the weight of the whole car section can be measured at one time without twice.

[0090] It can be understood that, first, when the system detects that the vehicle has been weighed, that is, after confirming that the vehicle has driven onto the track scale by analyzing the jump of the AD values ​​of the two signals, the system will start to collect the AD value data of the two signals in real time during the vehicle's driving process. Secondly, every time the scale returns from a non-zero state to a zero state, that is, every time the bogie of the vehicle leaves the scale, the system will record this zero return point and use it as the starting point and end point of the data analysis, and analyze and judge the data sequence between the last zero return and the current zero return. Then, the system adds the AD values ​​of the left and right roads to obtain the sum data, and filters the sum data to reduce noise and fluctuations. Then, a rough effective segment is identified from the filtered sum data, and the complete effective segment is determined by analyzing the difference between the left and right road data, and finally the measurement effective segment is obtained by removing the fluctuation. In this measurement effective segment, the system will calculate the weight of the bogie. The specific method is to average the data in the measurement effective segment, multiply it by the calibration coefficient, and obtain the weight of a bogie. Then, the weight of the front bogie this time is added to the weight of the rear bogie calculated last time to obtain the weight of the previous car. In this way, data can be collected and calculated at the same time, achieving real-time and accurate measurement of the weight of each vehicle section, ensuring the continuity and accuracy of the weighing process. At the same time, through filtering and determining the effective segment, the measurement accuracy is improved, adapting to various vehicle differences and combinations, and reducing misjudgments and errors.

[0091] As an example, the AD values ​​of the two signals include a first target effective section, a second target effective section and a target measurement effective section. When the vehicle is weighed, the AD values ​​of the two signals during each two returns to zero of the scale are analyzed and calculated to obtain the vehicle weight. The step also includes: determining the vehicle weighing time according to the jump of the AD values ​​of the two signals; determining the vehicle unweighing time when the AD values ​​of the two signals return to zero and the duration is greater than or equal to a preset time; obtaining the AD values ​​of the two signals on the scale according to the AD values ​​of the two signals, the vehicle weighing time and the vehicle unweighing time; simulating and waveform analyzing the AD values ​​of the two signals on the scale to obtain each rising point and falling point of the data change waveform curve, and obtaining the offline measurement result according to the rising point and the falling point; and performing fault analysis based on the offline measurement result.

[0092] The first target effective section refers to a time period that is preliminarily determined after the vehicle is weighed by analyzing the AD values ​​of the two signals. The data in this time period contains valid information about the vehicle weight, but further refinement and confirmation are required. The second target effective section refers to the time period that is determined after narrowing the scope through further analysis and calculation on the basis of the first target effective section. This time period more accurately reflects the valid information about the vehicle weight. The target measurement effective section refers to the time period for calculating the vehicle weight that is finally determined after de-fluctuation processing and refined analysis on the basis of the second target effective section. The data in this time period is considered to be the most stable and accurate, and can be directly used to calculate the actual weight of the vehicle. The jump refers to the sudden change of the AD values ​​of the two signals, that is, the sudden change of the signal value. This change is usually caused by the vehicle being weighed or unweighed, and can be used to determine the time point when the vehicle is weighed or unweighed. The vehicle weighing time refers to the specific time point when the vehicle starts to be weighed by analyzing the jump of the AD values ​​of the two signals. The preset duration refers to a time length preset by the system to determine whether the vehicle has been completely unweighed. Only when the AD values ​​of the two signals return to zero and the duration reaches or exceeds this preset duration, the system will confirm that the vehicle has been completely unweighed. The vehicle unweighing time refers to the specific time point when the vehicle is completely unweighed by analyzing the situation that the AD values ​​of the two signals return to zero and the duration reaches the preset duration. The AD values ​​of the two signals on the scale refer to the collected data of the AD values ​​of the two signals during the period from the vehicle being weighed to the vehicle being unweighed. Simulation refers to the use of existing data and algorithms to simulate the entire process of vehicle weighing to verify the accuracy of the algorithm and optimize the algorithm. Waveform analysis refers to the graphical processing of the collected AD values ​​of the two signals to form a waveform curve, and the change trend and feature points of the data are identified by analyzing these waveform curves. The data change waveform curve refers to the graphical representation of the collected AD values ​​of the two signals. The waveform curve formed can intuitively show the change of the data. The so-called waveform records the AD values ​​of the two sensor signals (the sensor output is an analog millivolt signal, which is converted into a digital signal. The digital AD value is proportional to the force applied to the sensor). The computer collects and saves the two signals at high speed from the time the train enters the track scale (upper scale) until it leaves the track scale (lower scale). Calculating the weight of a car is the process of analyzing, searching, and determining the valid segment of the waveform. The weight calculation of each car is not a one-time calculation when the train is weighed down, but is calculated while collecting. When a train is measured, a data file (waveform file) is formed. This file is read and displayed through a curve (it can display the left data, the right data, and the sum of the two data). The force applied to the sensor during the entire measurement process can be viewed and analyzed. For example, data fluctuations. If the data fluctuations are large, it means that the mechanical structure may be unstable or the data transmission line is interfered.For example, when one axle of a vehicle drives onto the scale table, the data should have a steep rise. If it rises too slowly, it means that the scale table is in contact with the adjacent rail and the scale is squeezed. In short, all problems with the scale can be reflected in the waveform. Furthermore, this waveform file can be used to replace the sensor as the data source to simulate the passing of the train and verify the optimization effect of the algorithm (for example, the measurement of a train exposes a problem, and the algorithm is subsequently optimized. At this time, you can use the waveform file of that train as the data source without actually passing the train on site to simulate the passing process). The rising point refers to the point on the waveform curve that indicates the increase in signal value, which usually corresponds to the moment when a part of the vehicle begins to be weighed. The falling point refers to the point on the waveform curve that indicates the decrease in signal value, which usually corresponds to the moment when a part of the vehicle begins to be weighed. Offline measurement results refer to the offline analysis results of the waveform curve based on the AD value data at any time after the train weight is measured. This result can be used for fault analysis. For example, if the system fails and the measurement is completed, only 49 out of 50 cars are measured. Through this analysis result, the cause of the fault can be found and eliminated, and normal measurement can be carried out next time.

[0093] First, the collected two-way signal AD values ​​are divided into three stages: the first target effective section (rough effective section), the second target effective section (complete effective section) and the target measurement effective section (measurement effective section). After confirming that the vehicle has been put on the scale, the moment when the vehicle is put on the scale is determined by the jump of the signal AD value. When the signal AD value returns to zero and lasts for a period greater than or equal to the preset time, the time when the vehicle is unweighed is determined. After that, the AD values ​​of the two signals during the period of weighing can be extracted according to the time when the vehicle is weighed and unweighed, and these signals can be simulated and waveform analyzed to obtain signal characteristics and analysis results. According to the analysis results, a fault analysis is performed. If a fault is found, the cause of the fault can be eliminated so that normal measurement can be performed next time.

[0094] Please refer to Figure 2 , Figure 2The waveform diagram of overweighing provided in the first embodiment of the vehicle weighing method based on the dynamic track scale of the present application shows the waveform diagram of overweighing of a train when passing through the dynamic track scale of bogie measurement, and describes in detail the complete process of each bogie of the train passing through the track scale in turn. From left to right, the waveform diagram records the process of weighing and returning to zero of the two bogies of the first to fourth sections, as well as the return to zero and downweighing of the locomotive head. Each "return to zero" in the figure indicates that a bogie leaves the track scale and the scale returns to the unloaded state, while "weighing" indicates that the train begins to enter the track scale and is measured. "Downweighing" means that the last bogie of the train leaves the scale and the track scale returns to the unloaded state. "Downweighing" is the end point of the weighing process of the entire train, not the end point of the weighing process of each carriage, but data collection will not stop, and the collection is always ongoing. Only when it is always ongoing can the train be judged at any time. This process reflects the ability of the dynamic track scale to weigh the weight of each bogie in real time during the train, so that the weight of each carriage can be accurately calculated. Through this continuous weighing process, the system can collect the necessary data for vehicle model judgment and weight calculation, ensuring the continuity and accuracy of measurement.

[0095] Please refer to Figure 3 , Figure 3 A schematic diagram of a rough effective segment waveform is provided for the first embodiment of the vehicle weighing method based on a dynamic track scale of the present application, which shows a rough effective segment waveform obtained by analyzing and calculating the AD values ​​of the two collected signals. The figure shows the weight change between two returns to zero, where the "raw sum data" represents the sum of the unprocessed signal values ​​collected by the sensor, reflecting the real-time weight change when the vehicle passes the track scale. The "filtered" sum data is the result of filtering the raw data, which aims to reduce noise and fluctuations in the data and make the waveform smoother, so as to more accurately identify the upper and lower scale points of the vehicle.

[0096] In the figure, "a1" and "a2" represent the starting and ending points between two returns to zero, respectively, and they define the time period of analysis. The area between "b1" and "g1" represents the first roughly valid segment, and the area between "b2" and "g2" represents the second roughly valid segment. These roughly valid segments are determined by analyzing the filtering and data change trends, and they roughly identify the time period when the vehicle is weighed. "b1" is the first rising point found from left to right, that is, starting from "a1", the first significant weight increase point is found. Point "g1" is the point after point "b1" where the weight begins to drop and is less than the preset multiple of the AD value at the first rising point, that is, the first drop point. Similarly, point "b2" is the second rising point found from right to left, and point "g2" is the point where the corresponding weight drops and is less than the preset multiple of the AD value at the second rising point, which is the second drop point. The preset multiple is a pre-set multiple value. When looking for a falling point, the AD value should be close to the AD value at the rising point. For example, if the AD value at the rising point is 1000, then the AD value when looking for a falling point should be less than 1100. In this embodiment, the preset multiple is 1.1 times.

[0097] Please refer to Figure 4 , Figure 4 The waveform diagram of the complete effective segment and the metering effective segment provided in the first embodiment of the vehicle weighing method based on the dynamic track scale of this application shows the complete effective segment and the metering effective segment for analyzing and calculating the AD values ​​of the two collected signals. The figure depicts the waveform changes from left to right in detail, where the "left data" and "right data" respectively represent the signal values ​​collected by the two sets of sensors connected in parallel along the vertical direction of the rail, and the "sum data" is the sum of the two signal values.

[0098] In the figure, "b1" to "g1" identifies the first rough effective section, which indicates the process of the first bogie being weighed; "b2" to "g2" identifies the second rough effective section, which indicates the process of the second bogie being weighed. In the first rough effective section "b1" to "g1", by calculating the difference (LR) between the left road and the right road, the "c1" point corresponding to the maximum difference point is found; similarly, the difference (RL) between the right road and the left road is calculated in this section, and the "f1" point corresponding to the maximum difference point is found, thereby determining the first complete effective section "c1" to "f1", during which the two axles of the first bogie are completely on the scale. Similarly, the second complete effective section "c2" to "f2" represents the time period when the two axles of the second bogie are completely on the scale. In order to improve the measurement accuracy, it is necessary to remove the parts with large fluctuations at both ends from the complete effective section to determine the measurement effective section. In the first complete valid segment "c1" to "f1", it is divided into 6 segments, and the 1 / 6 segments at both ends are removed. Then, in the remaining middle 4 / 6 segments, the two maximum AD value points "d1" and "e1" of the data "X" sequence are found (d1 is the maximum point in the second 1 / 6 segment, and e1 is the maximum point in the fifth 1 / 6 segment). The area between these two points is the first effective measurement segment. Similarly, the second effective measurement segment "d2" to "e2" is also determined from the second complete effective segment "c2" to "f2" by the same method. The entire schematic diagram reflects how to accurately determine the effective measurement segment by analyzing and processing sensor data in the dynamic track scale measurement method, thereby improving the precision and accuracy of measurement. Through this method, the system can adapt to various vehicle differences and combinations, effectively avoid misjudgments and errors, and ensure the efficiency and accuracy of the measurement process.

[0099] Please refer to Figure 5 , Figure 5 The locomotive head waveform schematic diagram provided for the first embodiment of the vehicle weighing method based on the dynamic track scale of the present application shows the locomotive head waveform in the process of analyzing and calculating the AD values ​​of the collected two-way signals, reflecting the weight distribution characteristics of the locomotive head on the track scale. In the schematic diagram, the part between the "a1" and "a2" points represents the waveform of the rear bogie of a car and the front bogie of the locomotive head passing through the track scale. The "b1" and "b2" points represent the starting points of the first and second rough effective segments, respectively, and these two points are determined by analyzing the filtering and data change trends. The "g1" and "g2" points represent the end points of the first and second rough effective segments, respectively. The "c1" and "f1" points define the starting and ending points of the first complete effective segment, while the "c2" and "f2" points define the starting and ending points of the second complete effective segment. These points are determined by analyzing the difference changes in the original left and right road data, marking the time period when the rear bogie of a car and a front bogie of the head are completely on the scale.

[0100] For the carriage, the length of "c1~f1" is not much different from the length of "a1~c1", but for the locomotive head, the length of "c2~f2" is quite different from the length of "a2~c2". This length difference is due to the different structure of the locomotive head and the carriage, which makes the weight distribution characteristics generated on the track scale different. Through this analysis, the system can distinguish between the locomotive head and the ordinary carriage, because the waveform characteristics of the locomotive head are significantly different from those of the carriage. This distinction is crucial to ensure the accuracy of measurement because it allows the system to correctly select the carriage part to calculate the weight and avoid the interference of the locomotive head on the measurement of the carriage weight. The entire schematic diagram reflects how to accurately identify and measure the locomotive carriage by analyzing and processing sensor data in the dynamic track scale measurement method to ensure the efficiency and accuracy of the entire measurement process.

[0101] This embodiment provides a vehicle weighing method based on a dynamic track scale, which collects the AD values ​​of two signals of the dynamic track scale; determines whether the vehicle is on the scale according to the jump of the AD values ​​of the two signals, and obtains the vehicle on the scale result; when the vehicle on the scale result is that the vehicle has been on the scale, the AD values ​​of the two signals during the two zero returns of the scale are analyzed and calculated to obtain the vehicle weight. First, the system continuously collects the AD values ​​of the two signals of the dynamic track scale. These signals reflect the dynamic state of the vehicle before, during and after the scale is on the scale, ensuring that the data is fully collected while providing sufficient information for subsequent calculations, so that the movement process of the vehicle can be fully grasped. Then, the system accurately identifies the moment when the vehicle is on the scale by monitoring the jump of the signal AD value, thereby distinguishing the state of the vehicle entering the weighing area. This step helps to improve the accuracy of the on-scale detection and avoid missed detection and false detection. Finally, after the vehicle confirms that it is on the scale, the system analyzes and calculates the AD values ​​of the signals during the two zero returns during the operation of the vehicle to obtain the accurate weight of the vehicle. Even in the case of data fluctuations, the system can still accurately capture effective signals to ensure the accuracy of the weighing results. Through precise signal acquisition and calculation process, the reliability of weighing data is guaranteed, the whole process is automated, human intervention is reduced, and the real-time performance and efficiency of the system are improved.

[0102] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 6 , Figure 6 This is a flow chart of the second embodiment of the vehicle weighing method based on the dynamic track scale of the present application. Step S30 of the vehicle weighing method based on the dynamic track scale includes steps S31 to S35:

[0103] Step S31, when the vehicle weighing result is that the vehicle has been weighed, determining the target two-way signal AD value according to the time when the scale returns to zero twice, the target two-way signal AD value includes left-way data and right-way data;

[0104] It should be noted that the left-channel data and the right-channel data refer to the weighing signals collected from the left and right sides of the scale respectively through the dynamic track scale. The left-channel data and the right-channel data are the spatial sources of the signals, and the effective segment is the time period division of the signals.

[0105] It can be understood that when it is detected that the vehicle has been weighed, the AD values ​​of the two target signals collected are determined by observing the two zero return times of the scale. These signals come from the left and right sides of the vehicle when it passes through the track scale. Specifically, the zero return time refers to the moment when the collected data of the scale is close to / less than the zero point of the scale. Using these two zero return time points, the time period from each section of the vehicle (two bogies) entering the scale to leaving the scale can be accurately determined. During this period, the data of the left and right signals are collected and recorded separately to obtain the left and right data.

[0106] Step S32, obtaining sum data according to the left-channel data and the right-channel data, and filtering the sum data to obtain filtered sum data;

[0107] It should be noted that the sum data refers to the total weight signal obtained by adding the left-road data and the right-road data. The weight of the vehicle is distributed on the left and right sides of the track scale. Therefore, after collecting the AD signal data of the left and right roads respectively, the system adds these two parts of data to obtain the sum data reflecting the weight of the entire vehicle. The filtered sum data refers to the sum data continuously collected during the vehicle weighing, and the continuous data point set formed after filtering. The purpose of filtering is to eliminate noise and interference in the signal to ensure that the obtained sum data sequence is smoother and more accurate, thereby further improving the weighing accuracy.

[0108] It can be understood that after obtaining the AD signal data of the left and right tracks, the two data are first added together to form the total weight signal of the vehicle on the entire track scale, that is, the sum data. The left AD data sequence is recorded as L, the right AD data sequence is recorded as R, the AD value sequence of the left station + the right station is recorded as X, and the sum of the left and right data is calculated to obtain the X sequence: X i =L i +R i Then, the sum data is filtered to remove the noise and irregular fluctuations in the signal, thereby obtaining the smoothed filtered sum data Y. The filtering method is to make each value of X equal to the average value of X within a certain length l (for example, l = 20) afterwards:

[0109]

[0110] Among them, l represents the time window length used for moving average filtering, and i is used to represent the index of the current data point in the sequence, X n For each data point in the sequence X, Y i represents each data point in the sequence X.

[0111] This process ensures the accuracy and stability of the weight signal, effectively eliminates interference, and makes subsequent vehicle weight calculations more accurate. Through filtering, the system can cope with data fluctuations during vehicle weighing and achieve accurate weight measurement.

[0112] Step S33, analyzing and processing the left-channel data, the right-channel data, the sum data and the filtered sum data to obtain a target metering effective section;

[0113] It should be noted that the target measurement effective section refers to the data interval that best reflects the actual weight of the vehicle after analyzing the left-road data, right-road data, and data after filtering. This interval excludes interference factors such as noise and data fluctuations, and can accurately reflect the force applied to the vehicle on the scale, so it is used as the basis for the final calculation of the vehicle weight.

[0114] It can be understood that the left-side data, right-side data, and data, as well as the filtered and data sequences after filtering, are first analyzed and processed in detail. By comparing the change trends, fluctuations, and time series characteristics of these data, the effective parts related to vehicle weighing are identified, and irrelevant or noise sections are excluded. This process can accurately locate the data feature interval when the vehicle passes through the scale, and then determine the target measurement effective section that is accurately related to the vehicle weight. This method can effectively improve the weighing accuracy and ensure that the final weighing result is accurate and reliable.

[0115] As an example, the steps of analyzing and processing the left-channel data, the right-channel data, the sum data and the filtered sum data to obtain a target metering effective section include: analyzing the filtered sum data from a first direction and a second direction respectively to obtain a first target effective section, the first direction and the second direction being opposite; within the first target effective section, analyzing the left-channel data, the right-channel data and the sum data to obtain a second target effective section; performing de-fluctuation processing on the second target effective section to obtain a reference metering effective section; and selecting the part corresponding to the car body in the reference metering effective section as the target metering effective section according to the waveform difference between the locomotive head and the car body.

[0116] The first direction (from left to right in this embodiment) and the second direction (from right to left in this embodiment) are the directions for processing from different starting points of the time axis when analyzing the sum data sequence. The first direction is to analyze from the beginning (from left) to the end (to the right) of the data sequence, and the second direction is to analyze from the end (from right) to the beginning (to the left) of the data sequence. Through bidirectional analysis, the characteristic intervals in the data can be more comprehensively identified. The first target effective section (rough effective section) is a larger time period preliminarily identified based on the filtered sum data, which contains valid data, but also includes the time when the bogie is partially weighed and partially weighed. Therefore, it is a rough time period that has not been finely processed. The second target effective section (complete effective section) refers to a more accurate effective section obtained by further analyzing the left-road data, the right-road data and the sum data on the basis of the first target effective section and filtering out the transition data. This interval fully reflects the main force conditions when the vehicle passes through the scale, but may also contain some fluctuations or interference. De-fluctuation processing is a processing step for the data in the second target effective segment, which aims to remove slight fluctuations caused by factors such as vehicle bumps and natural vibrations of the scale to ensure that the data is more stable and accurate. The reference measurement effective segment refers to the data interval after de-fluctuation processing, which is called the reference measurement effective segment. This section of data has eliminated most of the fluctuations and interference, but may still contain the corresponding parts of the front and the car body. In data analysis, the front and the car body will show different waveform characteristics, because the front of the car is usually heavier and shorter, and the car body is relatively stable. Therefore, the data of the front part often shows greater fluctuations or irregularities. Selecting the waveform of the car body as the target measurement effective segment can obtain a more accurate overall vehicle weight. The effective segment that the system is looking for is the time period when one and only one bogie (two axles) is completely on the scale. The rough effective segment is just a little wider, including the time when the bogie is partially on the scale and partially off the scale. The complete effective segment is the time period when one and only one bogie (two axles) is completely on the scale. Although the data is complete, there are large fluctuations when the bogie is just completely on the scale and is about to be partially off the scale, so it is necessary to further shrink the data and remove the two ends to get the final measurement effective segment.

[0117] First, the filtered and data are analyzed from the first direction (from left to right) and the second direction (from right to left) to capture all possible valid data and preliminarily identify the first target valid segment (rough valid segment), which may contain the time when the bogie is partially weighed and partially weighed. Then, within the first target valid segment, the left-way data, the right-way data and the data are further analyzed to extract the second target valid segment (complete valid segment), at which the data is more accurate and comprehensive. Subsequently, the second target valid segment is subjected to de-fluctuation processing, the purpose of which is to eliminate data fluctuations caused by vehicle movement, vibration, etc., and obtain a more stable reference measurement valid segment. Finally, based on the difference in waveform between the head and the carriage, the part of the reference measurement valid segment related to the carriage is selected as the target measurement valid segment to ensure that the data obtained is more accurate and reliable. This segment of data reflects the actual weight and state of the vehicle when it passes through the scale.

[0118] As an example, the steps of analyzing the filtered data from both a first direction and a second direction to obtain a first target valid segment include: analyzing the filtered data from the first direction to obtain a first rising point; finding a point in the filtered data from the first direction whose AD value is less than a preset multiple of the AD value corresponding to the first rising point to obtain a first falling point; obtaining a first initial valid segment based on the first rising point and the first falling point; analyzing the filtered data from the second direction to obtain a second rising point; finding a point in the filtered data from the second direction whose AD value is less than the preset multiple of the AD value corresponding to the second rising point to obtain a second falling point; obtaining a second initial valid segment based on the second rising point and the second falling point; obtaining a first target valid segment based on the first initial valid segment and the second initial valid segment.

[0119] The first rising point refers to the point where the front bogie of the vehicle in the section of the car between each two returns to zero begins to be weighed when analyzing the filtered and data from the first direction (from left to right), that is, the specific position corresponding to the change in AD value when the front bogie of the vehicle in the section of the car between each two returns to zero begins to exert pressure on the track scale. The first falling point refers to the point where the AD value continues to drop from the first direction after the first rising point, and is less than a preset multiple of the AD value at the first rising point, indicating the moment when the front bogie of the car between each two returns to zero begins to leave the scale. The first initial valid segment (first rough valid segment) is a time period determined based on the first rising point and the first falling point, indicating the range of influence of the front bogie of the vehicle on the track scale. This segment may contain noise or inaccurate data and is a preliminarily determined valid data segment. The second rising point is the point where the rear bogie of the vehicle in the section of the car between every two returns to zero begins to be weighed when analyzing the filtered and data from the second direction (from right to left). It is similar to the first rising point, but in the opposite direction, indicating the position of the change in AD value when the rear bogie of the vehicle in the section of the car between every two returns to zero is weighed when observed from another direction. The second falling point is after the second rising point, looking for a point where the AD value drops from the second direction and is less than a preset multiple of the AD value at the second rising point, indicating the moment when the rear bogie of the car between every two returns to zero begins to leave the scale. The second initial valid segment (second rough valid segment) is a time period determined based on the second rising point and the second falling point, similar to the first initial valid segment, but obtained from the opposite direction. It also indicates the range of influence of the vehicle axle on the track scale and provides further verification of the valid segment.

[0120] First, analyze the filtered data from the first direction (from left to right) to find the point where the AD value jumps on the front bogie of the vehicle in the section between every two returns to zero. This point is called the first rising point (b1). Next, continue to look for a point where the AD value drops and is less than the preset multiple of the AD value at the first rising point in the same direction, and obtain the point where the front bogie of the vehicle in the section between every two returns to zero begins to leave the scale, that is, the first falling point (g1). According to the range defined by these two points (b1 and g1), determine the time period when the front bogie of the vehicle in the section between every two returns to zero passes through the scale, which is called the first initial valid section (first rough valid section). Then, repeat the same analysis process, but from the opposite direction (from right to left), find the second rising point (b2) and the second falling point (g2) of the rear bogie of the vehicle in the section between every two returns to zero, and determine the second initial valid section (second rough valid section). Finally, the initial valid segments in the two directions are combined to obtain a more accurate first target valid segment, which reflects the valid data range when the vehicle passes through the scale.

[0121] As an example, the first target valid segment includes a first initial valid segment and a second initial valid segment, and within the first target valid segment, the left-path data, the right-path data and the sum data are analyzed to obtain the second target valid segment. The step includes: within the first initial valid segment, a third rising point is obtained according to the maximum value of the difference between the left-path data and the right-path data, and a third falling point is obtained according to the maximum value of the difference between the right-path data and the left-path data; a third initial valid segment is obtained according to the third rising point, the third falling point and the sum data; within the second initial valid segment, a fourth rising point is obtained according to the maximum value of the difference between the left-path data and the right-path data, and a fourth falling point is obtained according to the maximum value of the difference between the right-path data and the left-path data; a fourth initial valid segment is obtained according to the fourth rising point, the fourth falling point and the sum data; and a second target valid segment is obtained according to the third initial valid segment and the fourth initial valid segment.

[0122] The difference between the left-channel data and the right-channel data refers to the difference between the data from the two signals. Because the values ​​measured by the left and right-channel sensors may differ when the vehicle is on the scale, the trajectory of the vehicle during weighing can be determined more accurately by analyzing these differences. For example, if the left-channel signal is higher than the right-channel signal, it means that the weight of the vehicle is more distributed on the left side of the scale. (It is not an absolute difference, so [the difference between the left-channel data and the right-channel data] is not the same as [the difference between the right-channel data and the left-channel data]) In this embodiment, the point corresponding to the maximum value in the difference between the left and right-channel data is the upper scale point or the lower scale point. The third rising point refers to the point in the first initial valid segment (corresponding to Figure 4 b1-g1 in the figure), by analyzing the difference between the left-road data and the right-road data, the time point when the front bogie of the vehicle in the section between each two returns to zero is just completely on the scale is found. This point is usually the time point corresponding to when the difference suddenly increases. The difference between the right-road data and the left-road data is the opposite of the difference between the left-road data and the right-road data, that is, the analysis is based on the right road to find the point with the maximum difference, which is used to further determine the vehicle's lowering point. The third descending point refers to the time point when the front bogie of the vehicle in the section between each two returns to zero is about to begin to descend, which is found by analyzing the difference between the right-road data and the left-road data, indicating that the vehicle axle has left the scale. After obtaining the third rising point and the third descending point, the third initial valid section corresponding to the third rising point and the third descending point can be determined based on the data. The third initial valid section refers to the interval between the third rising point and the third descending point. The data in this interval reflects the time period when the front bogie of the vehicle in the section between each two returns to zero is on the scale, that is, the first complete valid section (corresponding to Figure 4 The fourth rising point is in the second initial effective segment (corresponding to the c1-f1 segment in the Figure 4In the b2-g2 section in the figure, by analyzing the difference between the left and right road data, the time point when the rear bogie of the vehicle in the carriage between each two returns to zero is just completely on the scale is found. The fourth descending point is the time point when the rear bogie of the vehicle in the carriage between each two returns to zero is about to start to descend from the scale, obtained by analyzing the difference between the right road data and the left road data. After obtaining the fourth rising point and the fourth descending point, the fourth initial valid section corresponding to the fourth rising point and the fourth descending point can be determined based on the data. The fourth initial valid section is a time period determined by the fourth rising point and the fourth descending point, marking the time period when the rear bogie of the vehicle in the carriage between each two returns to zero is on the scale, that is, the second complete valid section (corresponding to Figure 4 c2-f2 in the figure).

[0123] Please refer to Figure 7 , Figure 7 The schematic diagram of the scale load when the train is moving is provided in Example 2 of the vehicle weighing method based on the dynamic track scale of the present application. The blue bars in the figure represent the various carriages of the train, and the red bars represent the track scale, that is, the dynamic track scale equipment. The purple circles represent the wheels, which pass through the track scale in turn. When the wheels press on the track scale, the sensors on the track scale will collect the AD values ​​of the two signals in real time. These AD values ​​reflect the pressure of the wheels on the track scale, which is proportional to the weight of the wheels.

[0124] During the train's travel, the track scale's measurement system will calculate the train's weight based on the AD value data. The system first determines the time when the vehicle is on the scale by analyzing the sudden change in the AD values ​​of the two signals, that is, the moment when the wheels begin to contact the track scale. Subsequently, the system will continue to monitor the AD value until the wheel completely leaves the track scale and the AD values ​​of the two signals return to zero and last for a period of time (preset duration), at which time the system will determine the time when the vehicle is off the scale.

[0125] Between the upper and lower scales of the vehicle, the measurement system of the track scale will analyze the AD value data collected during this period. The system adds the AD values ​​of the left and right roads to obtain the sum data, and then filters the sum data to reduce noise and fluctuations. Next, the system analyzes the trend of data changes to find the rough effective section, and then determines the complete effective section by calculating the point with the maximum value of the difference between the left and right road data. Finally, the system removes fluctuations from the complete effective section to obtain the measurement effective section, and calculates the weight of a bogie by multiplying the average value of the data in this effective section by the calibration coefficient. In this way, the system can continuously measure the real-time weight of each vehicle, ensuring the continuity and accuracy of the weighing process.

[0126] First, it is clear that the first target effective section consists of the first initial effective section and the second initial effective section, so as to further analyze the data in this section. Then, in the first initial effective section, firstly, by analyzing the difference between the left-way data and the right-way data, the point with the largest difference in the difference is identified, which is the third rising point (c1), indicating that the front bogie of the vehicle in the section between every two zero returns is just completely on the scale; then, the right-way data and the left-way data are analyzed in the same way, and the point with the largest difference in the difference is found to obtain the third falling point (f1) (the left-right maximum value in b1g1 determines the c1 point, and the right-left maximum value determines the f1 point), which indicates that the front bogie of the vehicle in the section between every two zero returns will start to be weighed down. Therefore, the time period determined by combining these two points forms the third initial effective section, that is, the first complete effective section, which marks the time when the front bogie of the vehicle in the section between every two zero returns is on the scale. Next, in the second initial valid section, a similar process is repeated. By analyzing the difference between the left and right data, the point with the largest difference in the difference is determined to be the fourth rising point (c2), and then the fourth falling point (f2) is found based on the difference between the right and left data. The fourth initial valid section, that is, the second complete valid section, is obtained by combining these two points, which represents the weighing time period of the rear bogie of the vehicle in the carriage between every two returns to zero. Finally, the third initial valid section and the fourth initial valid section are combined to form the second target valid section, ensuring a more comprehensive and accurate analysis of vehicle weighing. This process ensures accurate identification of the upper and lower weighing moments of each axle by analyzing different directions and differences, thereby improving the reliability of the weighing data.

[0127] As an example, the second target effective segment includes a third initial effective segment and a fourth initial effective segment, and the step of performing a de-fluctuation process on the second target effective segment to obtain a reference metering effective segment includes: dividing the third initial effective segment into a first preset number of segments, and performing a de-fluctuation process on the first preset number of segments to obtain a first left segment and a first right segment; searching for a maximum AD value in the sum data corresponding to the first left segment, and the corresponding point is the fifth rising point; searching for a maximum AD value in the sum data corresponding to the first right segment, and the corresponding point is the fifth falling point; obtaining the first metering effective segment according to the fifth rising point and the fifth falling point; dividing the fourth initial effective segment into a second preset number of segments, and performing a de-fluctuation process on the second preset number of segments to obtain a second left segment and a second right segment; searching for a maximum AD value in the sum data corresponding to the second left segment, and the corresponding point is the sixth rising point; searching for a maximum AD value in the sum data corresponding to the second right segment, and the corresponding point is the sixth falling point; obtaining the second metering effective segment according to the sixth rising point and the sixth falling point; obtaining the reference metering effective segment according to the first metering effective segment and the second metering effective segment.

[0128] The first preset number refers to the number of segments into which the third initial valid segment (c1 to f1) is equally divided, for example, it is divided into 6 segments, that is, in this example, it contains 6 1 / 6 segments. De-fluctuation processing refers to removing the two segments with larger fluctuations, the leftmost (the first 1 / 6 segment, the bogie is just completely on the scale) and the rightmost (the sixth 1 / 6 segment, the bogie is about to start to descend from the scale) segments among these segments, so as to reduce the impact of noise on data analysis and obtain more stable data results. The first left segment and the first right segment refer to two segments retained after processing, of which the first left segment refers to the second 1 / 6 segment, and the first right segment refers to the fifth 1 / 6 segment. The fifth rising point (d1) refers to the point with the largest AD value found in the sum data corresponding to the first left segment; the fifth falling point (e1) refers to the point with the largest AD value found in the sum data corresponding to the first right segment. Based on these two points, the first measurement valid segment (corresponding to Figure 4 d1-e1 segment in the figure), which represents the effective weighing time period of the front bogie of the vehicle in the carriage between every two returns to zero on the scale. The second preset number refers to the number of segments into which the fourth initial valid segment (c2 to f2) is divided, for example, it can be set to 8 segments. The second left segment and the second right segment refer to the two ends of the segment retained after processing, where the second left segment refers to the second 1 / 8 segment, and the second right segment refers to the seventh 1 / 8 segment. The sixth rising point (d2) refers to the point with the largest AD value found in the sum data corresponding to the second left segment; the sixth falling point (e2) refers to the point with the largest AD value found in the sum data corresponding to the second right segment. Based on these two points, the second measurement effective segment (corresponding to Figure 4 The d2-e2 section in the figure represents the effective weighing time period of the rear bogie of the vehicle in the carriage between each two zero returns. Finally, the first effective measurement section and the second effective measurement section are combined to obtain the reference effective measurement section to provide more accurate weighing data.

[0129] When processing the second target valid segment, the third initial valid segment is first divided into several segments (for example, 6 segments) in order to effectively reduce the impact of noise on the results when performing the de-fluctuation process. In this process, the two segments on the far left (the first 1 / 6 segment) and the far right (the sixth 1 / 6 segment) are removed. These two segments usually contain large fluctuation data. Removing them can better reflect the stability of the middle segment. In the remaining parts, the first left segment refers to the second 1 / 6 segment, and the first right segment refers to the fifth 1 / 6 segment. The maximum AD value is searched in the sum data corresponding to the first left segment to obtain the fifth rising point (d1), and the same search is performed in the first right segment to obtain the fifth falling point (e1). This is done to accurately capture the valid data when the vehicle passes through these segments. Through the positioning of these two balance points, the first metering valid segment can be calculated to provide a reliable measurement basis. Then, the fourth initial valid segment is also divided into the second preset number of segments, and the same de-fluctuation process is performed to obtain the second left segment and the second right segment to ensure the same data quality. In the second left segment and the second right segment, the maximum AD value is found respectively to obtain the sixth rising point (d2) and the sixth falling point (e2), thereby obtaining the second effective measurement segment. Finally, the first effective measurement segment and the second effective measurement segment are integrated to obtain the reference effective measurement segment to ensure accurate and stable measurement results in different situations and improve the overall accuracy and reliability of the system.

[0130] Step S34, obtaining the target and data corresponding to the target measurement effective period according to the sum data;

[0131] It should be noted that the target sum data refers to the part of the sum data corresponding to the target measurement effective period. Specifically, the target sum data refers to the data part of the entire sum data that can represent the effective weighing period of the vehicle after analysis and processing. This target sum data includes the sum data within the target measurement effective period, which helps to more accurately reflect the weight of the vehicle during this period, thereby supporting subsequent weighing and analysis work.

[0132] It can be understood that the part corresponding to the target measurement effective section is first identified by analyzing the sum data. This process includes determining the starting and ending positions of the target measurement effective section to ensure that only data within this range is extracted. Then, these specific data points are filtered out from the complete sum data to form the target sum data. This target sum data specifically represents the weighing of the vehicle within the target measurement effective section, ensuring that the data contained is accurate and relevant. In this way, the accuracy of subsequent calculations can be improved, ensuring that the data used is more reliable when performing weight measurement and analysis, thereby optimizing the effectiveness and efficiency of the overall measurement process.

[0133] Step S35, average calculation and calibration are performed on the AD values ​​of the target and data to obtain the vehicle weight.

[0134] It should be noted that the AD value refers to the actual measurement data extracted from the target and data, which represents the signal strength or change of the vehicle within the effective section of the target measurement. These AD values ​​are obtained through the dynamic track scale and reflect the weight information of the vehicle. Mean calculation refers to the statistical analysis of the AD value, which is obtained by summing these data points and dividing them by the number of data points to obtain a representative average value. This mean can reflect the overall weight characteristics of the vehicle when passing through the track scale. Calibration is to multiply the calculated mean by a coefficient that has been calibrated in advance with a standard vehicle, that is, to obtain the weight of a car.

[0135] It can be understood that the AD values ​​are first extracted from the target and data, and then the average of these AD values ​​is calculated, specifically, all AD values ​​are added and divided by the total number of data points to obtain the average signal value of the vehicle during the period. Then, the average is multiplied by the calibration coefficient to obtain the weight of a bogie, ensuring the reliability of the weighing result.

[0136] In this embodiment, when the vehicle is weighed, the target two-way signal AD value is determined according to the time when the scale returns to zero twice, and the target two-way signal AD value includes left-way data and right-way data; the sum data is obtained according to the left-way data and the right-way data, and the sum data is filtered to obtain the filtered sum data; the left-way data, the right-way data, the sum data and the filtered sum data are analyzed and processed to obtain the target measurement effective section; the target sum data corresponding to the target measurement effective section is obtained according to the sum data; the AD value of the target sum data is averaged and calibrated to obtain the vehicle weight. When the vehicle is detected to be weighed, the two-way signal AD value, i.e., the left-way data and the right-way data, is first determined by the time when the scale returns to zero twice, which can accurately reflect the weighing situation of the wheel on the track. Then, the sum data is obtained by adding the left-way data and the right-way data, and the sum data is filtered to eliminate noise or fluctuation interference to obtain stable filtered sum data. Then, the left-side, right-side, and data and the filtered and data are further analyzed and processed to identify the key part of vehicle weighing, namely the target measurement effective section, which helps to accurately capture the effective weighing period of the vehicle. Subsequently, based on the and data, the target and data corresponding to the target measurement effective section are extracted to lay the foundation for the final weight calculation. Finally, the AD values ​​in the target and data are averaged and calibrated to eliminate possible system errors or external interference to ensure the accuracy and reliability of the weighing results. Through this set of steps, the vehicle weight can be accurately calculated in the case of data fluctuations, achieving an efficient and accurate weighing process.

[0137] For example, in order to help understand the implementation process of the vehicle weighing method based on the dynamic track scale obtained by combining this embodiment with the above-mentioned embodiment 1, please refer to Figure 8 , Figure 8 A brief flow chart of a vehicle weighing method based on a dynamic track scale is provided, specifically:

[0138] The figure shows the process of the vehicle weighing method based on the dynamic track scale, including real-time data storage, empty scale and vehicle weighing, waveform display, vehicle weighing, vehicle model analysis and calculation, finding complete valid segments, finding rough valid segments, data filtering, and determining the effective measurement segment and calculating weight. In the empty scale state, the system collects the AD values ​​of the two signals in real time and stores the AD values ​​of the most recent time in a first-in-first-out manner. When the vehicle is weighed, the vehicle weighing and weighing direction are determined by the jump of the AD data. Subsequently, from the beginning of the vehicle weighing to the weighing, the AD values ​​of the two signals are saved in real time and formed into files for long-term storage. After the vehicle is weighed, the system will run the vehicle model judgment and calculation tasks, which involves adding and filtering the data of the left and right roads to analyze the data change trend and find the rough effective segment. In the rough effective segment, the complete effective segment is determined by calculating the maximum point of the difference between the left and right road data. Then, the complete effective segment is de-fluctuated to obtain the effective measurement segment. In addition, the system will also use the significant difference between the locomotive head and the train car waveform to select the car waveform part. Finally, the weight of a bogie is calculated by averaging the data in the effective measurement section and multiplying it by the calibration coefficient. During the whole process, the system can also display the complete passing waveform in the form of a curve by reading the saved passing data, and perform offline simulation of the vehicle judgment algorithm to vividly display the rough effective section, complete effective section and measurement effective section to ensure the accuracy and adaptability of the measurement.

[0139] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the vehicle weighing method based on the dynamic track scale of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0140] This application also provides a vehicle weighing device based on a dynamic track scale, please refer to Fig. 9 , the vehicle weighing device based on dynamic track scale comprises:

[0141] The data acquisition module 10 is used to collect the AD values ​​of the two-way signals of the dynamic track scale;

[0142] The weighing determination module 20 is used to determine whether the vehicle is weighed according to the jump of the AD values ​​of the two signals, and obtain the vehicle weighing result;

[0143] The vehicle weighing module 30 is used to analyze and calculate the AD values ​​of the two signals during each two zeroing periods of the scale to obtain the vehicle weight when the vehicle weighing result is that the vehicle has been weighed.

[0144] In one embodiment, the vehicle weighing module 30 is also used to determine the target two-way signal AD value according to the time when the scale returns to zero twice when the vehicle is weighed, and the target two-way signal AD value includes left-way data and right-way data; obtain sum data according to the left-way data and the right-way data, and filter the sum data to obtain filtered sum data; analyze and process the left-way data, the right-way data, the sum data and the filtered sum data to obtain a target measurement effective section; obtain the target sum data corresponding to the target measurement effective section according to the sum data; average and calibrate the AD values ​​of the target sum data to obtain the vehicle weight.

[0145] In one embodiment, the vehicle weighing module 30 is further used to analyze the filtered sum data from a first direction and a second direction respectively to obtain a first target valid segment, the first direction and the second direction being opposite; within the first target valid segment, the left-road data, the right-road data and the sum data are analyzed to obtain a second target valid segment; the second target valid segment is de-fluctuated to obtain a reference measurement valid segment; based on the waveform difference between the vehicle head and the vehicle body, the portion of the reference measurement valid segment corresponding to the vehicle body is selected as the target measurement valid segment.

[0146] In one embodiment, the vehicle weighing module 30 is also used to analyze the filtered data from a first direction to obtain a first rising point; find a point in the filtered data from the first direction whose AD value is less than a preset multiple of the AD value corresponding to the first rising point to obtain a first falling point; obtain a first initial valid segment based on the first rising point and the first falling point; analyze the filtered data from a second direction to obtain a second rising point; find a point in the filtered data from the second direction whose AD value is less than the preset multiple of the AD value corresponding to the second rising point to obtain a second falling point; obtain a second initial valid segment based on the second rising point and the second falling point; obtain a first target valid segment based on the first initial valid segment and the second initial valid segment.

[0147] In one embodiment, the vehicle weighing module 30 is also used to obtain, within the first initial valid section, a third rising point according to the maximum value of the difference between the left-road data and the right-road data, and a third falling point according to the maximum value of the difference between the right-road data and the left-road data; obtain a third initial valid section according to the third rising point, the third falling point and the sum data; within the second initial valid section, a fourth rising point according to the maximum value of the difference between the left-road data and the right-road data, and a fourth falling point according to the maximum value of the difference between the right-road data and the left-road data; obtain a fourth initial valid section according to the fourth rising point, the fourth falling point and the sum data; obtain a second target valid section according to the third initial valid section and the fourth initial valid section.

[0148] In one embodiment, the vehicle weighing module 30 is also used to divide the third initial valid segment into a first preset number of segments, and perform a de-fluctuation process on the first preset number of segments to obtain a first left segment and a first right segment; search for the maximum AD value in the sum data corresponding to the first left segment, and the corresponding point is the fifth rising point; search for the maximum AD value in the sum data corresponding to the first right segment, and the corresponding point is the fifth falling point; obtain the first measurement effective segment based on the fifth rising point and the fifth falling point; divide the fourth initial valid segment into a second preset number of segments, and perform a de-fluctuation process on the second preset number of segments to obtain a second left segment and a second right segment; search for the maximum AD value in the sum data corresponding to the second left segment, and the corresponding point is the sixth rising point; search for the maximum AD value in the sum data corresponding to the second right segment, and the corresponding point is the sixth falling point; obtain the second measurement effective segment based on the sixth rising point and the sixth falling point; obtain the reference measurement effective segment based on the first measurement effective segment and the second measurement effective segment.

[0149] In one embodiment, the vehicle weighing module 30 is also used to determine the time when the vehicle is weighed based on the jump of the AD values ​​of the two signals; determine the time when the vehicle is weighed off the scale when the AD values ​​of the two signals return to zero and the duration is greater than or equal to a preset time; obtain the AD values ​​of the two signals on the scale based on the AD values ​​of the two signals, the time when the vehicle is weighed, and the time when the vehicle is weighed off the scale; simulate and analyze the AD values ​​of the two signals on the scale to obtain each rising point and falling point of the data change waveform curve, and obtain offline measurement results based on the rising points and the falling points; and perform fault analysis based on the offline measurement results.

[0150] The vehicle weighing device based on a dynamic track scale provided by the present application adopts the vehicle weighing method based on a dynamic track scale in the above-mentioned embodiment, and can solve the technical problem of how to accurately weigh a vehicle when the data fluctuates. Compared with the prior art, the beneficial effects of the vehicle weighing device based on a dynamic track scale provided by the present application are the same as the beneficial effects of the vehicle weighing method based on a dynamic track scale provided by the above-mentioned embodiment, and the other technical features of the vehicle weighing device based on a dynamic track scale are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0151] The present application provides a vehicle weighing device based on a dynamic track scale, and the vehicle weighing device based on the dynamic track scale includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle weighing method based on the dynamic track scale in the above-mentioned embodiment one.

[0152] Reference below Fig.10 , which shows a schematic diagram of the structure of a vehicle weighing device based on a dynamic track scale suitable for implementing the embodiment of the present application. The vehicle weighing device based on a dynamic track scale in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig.10 The vehicle weighing equipment based on the dynamic track scale shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0153] like Fig.10As shown, the vehicle weighing equipment based on the dynamic track scale may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the vehicle weighing equipment based on the dynamic track scale are also stored. The processing device 1001, the ROM 1002 and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the vehicle weighing device based on the dynamic track scale to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a vehicle weighing device based on the dynamic track scale with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0154] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0155] The vehicle weighing equipment based on a dynamic track scale provided by the present application adopts the vehicle weighing method based on a dynamic track scale in the above-mentioned embodiment, which can solve the technical problem of how to accurately weigh a vehicle when the data fluctuates. Compared with the prior art, the beneficial effects of the vehicle weighing equipment based on a dynamic track scale provided by the present application are the same as the beneficial effects of the vehicle weighing method based on a dynamic track scale provided by the above-mentioned embodiment, and the other technical features of the vehicle weighing equipment based on a dynamic track scale are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0156] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0157] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0158] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the vehicle weighing method based on the dynamic track scale in the above-mentioned embodiment.

[0159] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0160] The above-mentioned computer-readable storage medium may be included in the vehicle weighing device based on the dynamic track scale; or it may exist independently without being assembled into the vehicle weighing device based on the dynamic track scale.

[0161] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle weighing equipment based on the dynamic track scale, the vehicle weighing equipment based on the dynamic track scale: collects the AD values ​​of the two-way signal of the dynamic track scale; judges whether the vehicle is on the scale according to the jump of the AD values ​​of the two-way signal, and obtains the vehicle weighing result; when the vehicle weighing result is that the vehicle has been weighed, analyzes and calculates the AD values ​​of the two-way signal during each two times the scale returns to zero, and obtains the vehicle weight.

[0162] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0163] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0164] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0165] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle weighing method based on a dynamic track scale, and can solve the technical problem of how to accurately weigh a vehicle when data fluctuates. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the vehicle weighing method based on a dynamic track scale provided in the above-mentioned embodiment, and will not be elaborated here.

[0166] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the vehicle weighing method based on a dynamic track scale as described above.

[0167] The computer program product provided by the present application can solve the technical problem of how to accurately weigh a vehicle when data fluctuates. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the vehicle weighing method based on the dynamic track scale provided by the above embodiment, which will not be described in detail here.

[0168] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A vehicle weighing method based on a dynamic track scale, characterized in that: The method comprises: Collect the AD values ​​of two signals of dynamic track scale; Determine whether the vehicle is on the scale according to the jump of the AD values ​​of the two signals, and obtain the vehicle on the scale result; When the vehicle weighing result is that the vehicle has been weighed, the AD values ​​of the two signals during each two zeroing periods of the weighing instrument are analyzed and calculated to obtain the vehicle weight.

2. The method according to claim 1, characterized in that When the vehicle weighing result is that the vehicle has been weighed, the step of analyzing and calculating the AD values ​​of the two signals during each two zeroing periods of the weighing instrument to obtain the vehicle weight includes: When the vehicle weighing result is that the vehicle has been weighed, the target two-way signal AD value is determined according to the time when the scale returns to zero twice, and the target two-way signal AD value includes left-way data and right-way data; Obtaining sum data according to the left-path data and the right-path data, and filtering the sum data to obtain filtered sum data; Analyzing and processing the left-channel data, the right-channel data, the sum data, and the filtered sum data to obtain a target metering effective section; Obtaining the target and data corresponding to the target measurement effective section according to the sum data; The AD values ​​of the target and data are averaged and calibrated to obtain the vehicle weight.

3. The method according to claim 2, characterized in that The step of analyzing and processing the left-channel data, the right-channel data, the sum data and the filtered sum data to obtain a target metering effective section comprises: Analyzing the filtered data from a first direction and a second direction respectively to obtain a first target valid segment, wherein the first direction is opposite to the second direction; Within the first target valid segment, analyzing the left-path data, the right-path data and the sum data to obtain a second target valid segment; performing a de-fluctuation process on the second target effective segment to obtain a reference measurement effective segment; According to the waveform difference between the locomotive head and the carriage, the portion corresponding to the carriage in the reference metering effective section is selected as the target metering effective section.

4. The method according to claim 3, characterized in that The step of analyzing the filtered data from the first direction and the second direction to obtain the first target valid segment includes: Analyzing the filtered and data from a first direction to obtain a first rising point; Finding a point in the filtered data from the first direction whose AD value is less than a preset multiple of the AD value corresponding to the first rising point, to obtain a first falling point; Obtaining a first initial valid segment according to the first ascending point and the first descending point; Analyzing the filtered and data from a second direction to obtain a second rising point; Find a point in the filtered data from the second direction whose AD value is less than the preset multiple of the AD value corresponding to the second rising point, to obtain a second falling point; Obtaining a second initial valid segment according to the second rising point and the second falling point; A first target valid segment is obtained according to the first initial valid segment and the second initial valid segment.

5. The method according to claim 3, characterized in that The first target valid segment includes a first initial valid segment and a second initial valid segment, and the step of analyzing the left-path data, the right-path data, and the sum data within the first target valid segment to obtain the second target valid segment includes: Within the first initial valid section, a third rising point is obtained according to the maximum value of the difference between the left-way data and the right-way data, and a third falling point is obtained according to the maximum value of the difference between the right-way data and the left-way data; Obtain a third initial valid segment according to the third rising point, the third falling point and the sum data; Within the second initial valid section, a fourth rising point is obtained according to the maximum value of the difference between the left-way data and the right-way data, and a fourth falling point is obtained according to the maximum value of the difference between the right-way data and the left-way data; Obtaining a fourth initial valid segment according to the fourth rising point, the fourth falling point and the sum data; A second target valid segment is obtained according to the third initial valid segment and the fourth initial valid segment.

6. The method according to claim 3, characterized in that The second target effective segment includes a third initial effective segment and a fourth initial effective segment, and the step of performing a de-fluctuation process on the second target effective segment to obtain a reference measurement effective segment includes: Divide the third initial valid segment into a first preset number of segments, and perform a de-fluctuation process on the first preset number of segments to obtain a first left segment and a first right segment; Find the maximum AD value in the sum data corresponding to the first left segment, and the corresponding point is the fifth rising point; Find the maximum AD value in the sum data corresponding to the first right segment, and the corresponding point is the fifth descending point; Obtaining a first metering effective section according to the fifth ascending point and the fifth descending point; Divide the fourth initial valid segment into a second preset number of segments, and perform a de-fluctuation process on the second preset number of segments to obtain a second left segment and a second right segment; Find the maximum AD value in the sum data corresponding to the second left segment, and its corresponding point is the sixth ascending point; Find the maximum AD value in the sum data corresponding to the second right segment, and its corresponding point is the sixth descending point; Obtaining a second metering effective section according to the sixth ascending point and the sixth descending point; A reference metering valid segment is obtained according to the first metering valid segment and the second metering valid segment.

7. The method according to any one of claims 1 to 6, characterized in that The two-way signal AD value includes a first target effective section, a second target effective section and a target measurement effective section. When the vehicle weighing result is that the vehicle has been weighed, the two-way signal AD value during each two zeroing periods of the weighing instrument is analyzed and calculated to obtain the vehicle weight, and the step further includes: Determine the vehicle weighing time according to the jump of the AD values ​​of the two signals; When the AD values ​​of the two signals return to zero and the duration is greater than or equal to the preset time, the vehicle off-balance time is determined; According to the AD values ​​of the two signals, the time when the vehicle is on the scale and the time when the vehicle is off the scale, the AD values ​​of the two signals on the scale are obtained; Simulating and analyzing the waveform of the two AD values ​​of the scale signals to obtain the rising points and falling points of the data change waveform curve, and obtaining the offline measurement results according to the rising points and the falling points; Perform fault analysis based on the offline measurement results.

8. A vehicle weighing device based on a dynamic track scale, characterized in that: The device comprises: Data acquisition module, used to collect the AD values ​​of two signals of dynamic track scale; A weighing determination module is used to determine whether the vehicle is weighed according to the jump of the AD values ​​of the two signals, and obtain a vehicle weighing result; The vehicle weighing module is used to analyze and calculate the AD values ​​of the two signals during each two zero returns of the scale to obtain the vehicle weight when the vehicle weighing result is that the vehicle has been weighed.

9. A vehicle weighing device based on a dynamic track scale, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the vehicle weighing method based on a dynamic track scale as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle weighing method based on a dynamic track scale as described in any one of claims 1 to 7 are implemented.

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