A Compensation Method, Device and Electronic Equipment for Axle Weight Error of Dynamic Weighbridge

Abstract

The present application discloses a method, device and electronic device for compensating the axle weight error of a dynamic weighbridge. After dividing the obtained effective axle weight data corresponding to the weighed axle into N segments, the method calculates the equivalent average slope corresponding to each segment of data, and then compensates the axle weight error corresponding to the weighed axle according to the relationship between these equivalent data average slopes and the axle weight data error compensation coefficient corresponding to the weighed axle. Since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, therefore, the above method for compensating the axle weight error based on each equivalent average slope corresponding to the equivalent axle weight data of the weighed axle takes into account the main cause of axle weight error, which is vehicle vibration, and improves the accuracy of axle weight error compensation.

Description

Technical Field

[0001] The present application relates to the technical field of dynamic vehicle weighbridges, and particularly to a method, device, and electronic device for compensating the axle weight error of a dynamic vehicle weighbridge. Background Art

[0002] Large vehicles such as trucks and buses will cause damage to traffic facilities such as highway pavements and bridges when overloaded, thus affecting the service life of traffic facilities such as highways and bridges. At the same time, it will also affect the driving safety of passing vehicles. Therefore, it is necessary to manage overloaded vehicles. At present, the management of overloaded vehicles usually adopts the non-site overloading control method. This management method uses a non-stop detection system to monitor vehicles, which has the advantages of unattended operation, accuracy, and high passing speed. However, when the measured vehicle vibrates due to its own reasons or due to factors such as road unevenness, it is very difficult to accurately calculate the axle weights of each axle of the vehicle, resulting in inaccurate weighing results and affecting the judgment of overloading control law enforcement.

[0003] To solve the above problems, the prior art usually installs a newly added vibration sensor near the entrance of the vehicle to the weighing platform to sense the vibration of the weighing platform itself caused by the vehicle axle entering the weighing platform, and compensates the axle weight error based on the data collected by the vibration sensor.

[0004] The above method for compensating the axle error mainly considers the axle weight error caused by the vibration of the weighing platform itself. However, in fact, the vibration of the weighing platform itself is caused by the vibration of the vehicle entering the weighing platform, and the vehicle vibration is the main factor causing the axle weight error. Therefore, the accuracy of compensating the axle weight error by this compensation method is not high, affecting the final weighing result. Summary of the Invention

[0005] The present application provides a method for compensating the axle weight error of a dynamic vehicle weighbridge, which is a method for compensating the axle weight error based on the respective equivalent average slopes corresponding to the effective axle weight data of the axles passing through the scale, considering the main cause of the axle weight error, i.e., vehicle vibration, and improving the accuracy of compensating the axle weight error.

[0006] In a first aspect, the present application provides a method for compensating the axle weight error of a dynamic vehicle weighbridge, the method comprising:

[0007] Dividing the effective axle weight data of the axles passing through the scale into N segments at equal time intervals, and calculating the equivalent average slope for each segment of the effective axle weight data to obtain K equivalent average slopes, where N and K are both positive integers greater than or equal to 2;

[0008] Calculating a first slope based on the N equivalent average slopes, the first slope being able to reflect the influence of vehicle vibration on the axle weight data of the axles passing through the scale;

[0009] Determine the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient;

[0010] Compensate the axle weight error corresponding to the weighed axle according to the axle weight error compensation coefficient corresponding to the weighed axle.

[0011] By compensating the axle weight error corresponding to the weighed axle through the above method, since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, therefore, the above method for compensating the axle weight error based on each equivalent average slope corresponding to the weighed axle equivalent axle weight data takes into account the main cause of axle weight error, which is vehicle vibration, and improves the accuracy of axle weight error compensation.

[0012] In a possible design, before equally dividing the effective axle weight data of the weighed axle into N segments at the same time interval, it further includes:

[0013] After detecting that the current axle leaves the weighing platform, obtain M peaks corresponding to M axle weight data sequences of the weighed axle detected by M sensors, where M is an even number greater than or equal to 4;

[0014] Determine the first moment and the second moment corresponding to two peaks during the weighing time period, where the weighing time period is the time period corresponding to after the axle enters the weighing platform and before it leaves the weighing platform;

[0015] Sum the axle weight data within the time period corresponding to the first moment and the second moment in the M axle weight data sequences to obtain the effective axle weight data of the weighed axle.

[0016] Through the above method, confirm the effective axle weight data according to the peaks corresponding to the axle weight data detected by each sensor, making the finally obtained effective axle weight data more stable and containing more effective data volume.

[0017] In a possible design, before detecting that the current axle leaves the weighing platform, it further includes:

[0018] Superimpose the M axle weight data sequences according to the corresponding time to obtain the total axle weight data;

[0019] When the waveform corresponding to the total axle weight data crosses the first threshold from low to high, record the third moment corresponding to the first threshold;

[0020] When the waveform corresponding to the total axle weight data crosses the second threshold from high to low, record the fourth moment corresponding to the second threshold;

[0021] When the difference between the third moment and the fourth moment is greater than a third threshold, the time period corresponding to the third moment and the fourth moment is taken as the weighing time period.

[0022] Through the above method, the interference data corresponding to the time period when the axle enters the weighing platform and the time period when it leaves the weighing platform can be filtered.

[0023] In a possible design, determining the axle weight error compensation coefficient corresponding to the axle passing the scale according to the relationship between the first slope and the axle weight error compensation coefficient includes:

[0024] Comparing the first slope with a preset database to obtain the axle weight error compensation coefficient corresponding to the first slope, where the first slope in the preset database and the axle weight error compensation coefficient are in one-to-one correspondence;

[0025] Taking the axle weight error compensation coefficient as the axle weight error compensation coefficient corresponding to the axle passing the scale.

[0026] Through the above method, the axle weight error compensation coefficient corresponding to the current first slope is determined based on the preset database. This compensation method can continuously update the preset database and improve the accuracy of axle weight error compensation.

[0027] In a possible design, determining the axle weight error compensation coefficient corresponding to the axle passing the scale according to the relationship between the first slope and the axle weight error compensation coefficient includes:

[0028] Inputting the first slope into a preset model for calculation to obtain a calculation result, where the preset model is a calculation model reflecting the mapping relationship between the first slope and the axle weight error compensation coefficient;

[0029] Taking the calculation result as the axle weight error compensation coefficient corresponding to the axle passing the scale.

[0030] Through the above method, the axle weight error compensation coefficient corresponding to the current first slope is calculated based on the preset model. This compensation method has a short analysis time and can also improve the preset model to enhance the accuracy of axle weight compensation.

[0031] In a second aspect, the present application provides a device for compensating the axle weight error of a dynamic weighbridge, and the device includes:

[0032] A calculation module, configured to evenly divide the effective axle weight data of the axle passing the scale into N segments at the same time interval, and calculate the equivalent average slope for each segment of effective axle weight data to obtain K equivalent average slopes, where both N and K are positive integers greater than or equal to 2; according to the N equivalent average slopes, calculate a first slope, and the first slope can reflect the influence of vehicle vibration on the axle weight data of the axle passing the scale;

[0033] A first determination module, configured to determine an axle weight error compensation coefficient corresponding to the axle passing over the scale according to the relationship between the first slope and the axle weight error compensation coefficient;

[0034] Compensate for the axle weight error corresponding to the axle passing over the scale according to the axle weight error compensation coefficient corresponding to the axle passing over the scale.

[0035] In a possible design, the device further includes:

[0036] An acquisition module, configured to, after detecting that the current axle leaves the scale platform, acquire M peaks corresponding to M axle weight data sequences of the axle passing over the scale detected by M sensors, where M is an even number greater than or equal to 4;

[0037] A second determination module, configured to determine a first moment and a second moment respectively corresponding to two peaks within a weighing time period, where the weighing time period is the time period corresponding to after the axle enters the scale platform and before it leaves the scale platform;

[0038] A summation module, configured to sum the axle weight data within the time period corresponding to the first moment and the second moment in the M axle weight data sequences to obtain the effective axle weight data of the axle passing over the scale.

[0039] In a possible design, the device further includes:

[0040] An acquisition module, configured to stack the M axle weight data sequences according to the corresponding time to obtain total axle weight data;

[0041] A first recording module, configured to record a third moment corresponding to the first threshold when the waveform corresponding to the total axle weight data crosses the first threshold from low to high;

[0042] A second recording module, configured to record a fourth moment corresponding to the second threshold when the waveform corresponding to the total axle weight data crosses the second threshold from high to low;

[0043] A third determination module, configured to, when the difference between the third moment and the fourth moment is greater than a third threshold, use the time period corresponding to the third moment and the fourth moment as the weighing time period.

[0044] In a possible design, the first determination module is specifically configured to:

[0045] Compare the first slope with a preset database to obtain the axle weight error compensation coefficient corresponding to the first slope, where the first slope in the preset database and the axle weight error compensation coefficient are in one-to-one correspondence;

[0046] Take the axle weight error compensation coefficient as the axle weight error compensation coefficient corresponding to the axle passing over the scale.

[0047] In a possible design, the first determination module is further configured to:

[0048] Input the first slope into a preset model for calculation to obtain a calculation result, where the preset model is a calculation model reflecting the mapping relationship between the first slope and the axle weight error compensation coefficient;

[0049] Take the calculation result as the axle weight error compensation coefficient corresponding to the axle passing over the scale.

[0050] In a third aspect, the present application provides an electronic device, including:

[0051] A memory for storing a computer program;

[0052] A processor for implementing the steps of the above-mentioned method for compensating the axle weight error of a dynamic weighbridge when executing the computer program stored in the memory.

[0053] In a fourth aspect, the present application provides a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned method for compensating the axle weight error of a dynamic weighbridge are implemented.

[0054] Based on the above-mentioned method for compensating the axle weight error of a dynamic weighbridge, after dividing the obtained effective axle weight data corresponding to the axle passing over the scale into N segments, calculate the equivalent average slope corresponding to each segment of data, and then, according to the relationship between these equivalent data average slopes and the axle weight data error compensation coefficient corresponding to the axle passing over the scale, compensate for the axle weight error corresponding to the axle passing over the scale. Since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, therefore, the above-mentioned method for compensating the axle weight error based on each equivalent average slope corresponding to the equivalent axle weight data of the axle passing over the scale takes into account the main cause of axle weight error, which is vehicle vibration, and improves the accuracy of compensating for the axle weight error.

[0055] For the various aspects in the above-mentioned second aspect to fourth aspect and the possible technical effects that each aspect may achieve, reference may be made to the technical effects that can be achieved by the above-mentioned first aspect or various possible solutions in the first aspect, and details will not be repeated here. Description of the Drawings

[0056] Figure 1 Is a flowchart of a method for compensating the axle weight error of a dynamic weighbridge provided by the present application;

[0057] Figure 2 Is a schematic diagram of the installation position of a sensor provided by the present application;

[0058] Figure 3 Schematic diagram of multiple axle weight data sequences corresponding to the weighing axle of this application;

[0059] Figure 4 Schematic diagram of the total axle weight data sequence corresponding to the weighing axle of this application;

[0060] Figure 5 Schematic diagram of the peak values of axle weight data corresponding to multiple sensors of this application;

[0061] Figure 6 Schematic diagram of the segmentation of equivalent axle weight data of this application;

[0062] Figure 7 Schematic diagram of the relationship between the first slope and vehicle vibration of this application;

[0063] Figure 8 Schematic diagram of the structure of a compensation device for the axle weight error of a dynamic weighbridge of this application;

[0064] Figure 9 Schematic diagram of the structure of an electronic device of this application. Specific embodiments

[0065] In order to make the objectives, technical solutions, and advantages of this application clearer, the following will further describe this application in detail with reference to the accompanying drawings. The specific operation methods in the method embodiments can also be applied to the device embodiments or system embodiments. It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The connection between A and B can represent: A is directly connected to B and A is connected to B through C. In addition, in the description of this application, words such as "first" and "second" are only used for the purpose of distinguishing descriptions, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0066] The following will describe the embodiments of this application in detail with reference to the accompanying drawings.

[0067] When detecting the load of a weighing vehicle, due to the vibration of the vehicle being measured, it is very difficult to accurately obtain the axle weights of the weighing vehicle, which results in inaccurate weighing results. To solve this problem, the prior art usually installs a newly added vibration sensor near the entrance of the vehicle to the weighing platform to sense the vibration of the weighing platform itself caused by the vehicle axle leaving the weighing platform, and compensates for the axle weight error based on the data collected by the vibration sensor.

[0068] The above method for compensating axle errors mainly considers the axle weight errors caused by the vibration of the weighing platform itself. In fact, the vibration of the weighing platform itself is caused by the vibration of the vehicle entering the weighing platform, and the vehicle vibration is the main factor causing the axle weight errors. Therefore, the accuracy of the compensation method for axle weight errors is not high, which affects the final weighing result.

[0069] To solve the above problems, the present application provides a method for compensating axle weight errors of a dynamic weighbridge. After dividing the obtained effective axle weight data corresponding to the weighed axle into N segments, the equivalent average slope corresponding to each segment of data is calculated, and then, according to the relationship between these equivalent data average slopes and the axle weight error compensation coefficient corresponding to the weighed axle, the axle weight error corresponding to the weighed axle is compensated. Since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, the above method for compensating axle weight errors based on each equivalent average slope corresponding to the equivalent axle weight data of the weighed axle takes into account the main cause of axle weight errors, i.e., vehicle vibration, and improves the accuracy of compensating axle weight errors. Among them, the methods and devices described in the embodiments of the present application are based on the same technical concept. Since the principles of the problems solved by the methods and devices are similar, the embodiments of the device and the method can be referred to each other, and the repeated parts will not be described again.

[0070] As Figure 1 shown, it is a flowchart of the method for compensating axle weight errors of a dynamic weighbridge provided by the present application, which specifically includes the following steps:

[0071] S11, evenly divide the effective axle weight data of the weighed axle into N segments at the same time interval, and calculate the equivalent average slope for each segment of effective axle weight data to obtain N equivalent average slopes;

[0072] S12, calculate the first slope according to the N equivalent average slopes;

[0073] S13, determine the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient;

[0074] S14, compensate the axle weight error corresponding to the weighed axle according to the axle weight error compensation coefficient corresponding to the weighed axle.

[0075] In the embodiments of the application, when a vehicle passes the weighbridge, M axle weight data sequences corresponding to the currently weighed axle are detected by M sensors, and the total axle weight data obtained by superimposing the M axle weight data sequences according to the corresponding time.

[0076] For example, referring to Figure 2 、 Figure 3 and Figure 4 , where Figure 2 is a sensor installation position diagram, Figure 2A1, A2, A3, and A4 therein are respectively four sensors for detecting the axle weight data corresponding to the weighed axle. Figure 3 The waveforms corresponding to A1, A2, A3, and A4 therein are respectively the axle weight data sequences output by the four sensors. When the axle approaches a certain sensor, the reading of this sensor will increase. Therefore, sensors A2 and A4 reach the maximum reading first, and sensors A1 and A3 reach the maximum later. Also, because the left and right wheels of the vehicle often do not get on the scale at the same time, there is a certain time difference between the waveforms of A2 and A4, or between A1 and A3. Figure 4 (A1 + A2 + A3 + A4) therein is the total axle weight data obtained by superimposing the axle weight data sequences corresponding to A1, A2, A3, and A4 respectively according to the corresponding time.

[0077] Next, effective axle weight data for axle weight error compensation analysis is extracted from the total axle weight data. The specific method includes:

[0078] First, determine the weighing time period when the axle passes the scale. Among them, the weighing time period is the time period corresponding to after the axle enters the scale platform and before it leaves the scale platform;

[0079] Specifically, when the waveform corresponding to the total axle weight data crosses the first threshold from low to high, record the third moment corresponding to crossing the first threshold; when the waveform corresponding to the total axle weight data crosses the second threshold from high to low, record the fourth moment corresponding to crossing the second threshold; when the time difference between the third moment and the fourth moment is greater than the third threshold, take the time period between the third moment and the fourth moment as the weighing time period.

[0080] For example, referring to Figure 3 , when the waveform corresponding to the total axle weight data crosses the first preset threshold V1 from low to high, record the moment t1 corresponding to V1. When the waveform corresponding to the total axle weight data crosses the second preset threshold V2 from high to low, record the moment t2 corresponding to V2. At this time, the time difference between t1 and t2 is Δt = t2 - t1. If Δt is greater than the set time T, the time period before t1 is the time period of entering the scale platform, the time period after t2 is the time period of leaving the scale platform, and the time period between t1 and t2 is the weighing time period.

[0081] Further, after determining the weighing time period when the axle passes the scale, determine the effective axle weight data corresponding to the weighed axle from the total axle weight data corresponding to the weighed axle. Among them, the time corresponding to the effective axle weight data is within the weighing time period. The specific method for determining the effective axle weight data corresponding to the weighed axle includes:

[0082] After detecting that the current axle leaves the scale platform, obtain M peaks corresponding to the M axle weight data sequences of the weighed axle detected by M sensors, where M is an even number greater than or equal to 4;

[0083] Determine the first moment and the second moment corresponding to the two peaks within the weighing time period respectively;

[0084] Sum up the axle weight data within the time period corresponding to the first moment and the second moment in the M axle weight data sequences to obtain the effective axle weight data of the vehicle passing the scale.

[0085] For example, referring to Figure 5 , where the time period between t1 and t2 is the weighing time period, V A1 , V A2 , V A3 and V A4 are respectively the 4 peaks corresponding to the 4 axle weight data sequences of the vehicle passing the scale detected by four sensors A1, A2, A3, and A4. The time points corresponding to the 4 peaks are T A1 , T A2 , T A3 and T A4 . Through the analysis of the 4 axle weight data sequences, it can be known that within the time period between T A4 and T A2 , the data changes in the 4 axle weight data sequences are relatively gentle. Therefore, sum up the axle weight data within the time period between T A4 and T A2 in the 4 axle weight data sequences to obtain the effective axle weight data of the vehicle passing the scale.

[0086] Through the above method, confirm the effective axle weight data according to the peaks corresponding to the axle weight data detected by each sensor, so that the finally obtained effective axle weight data is more stable and contains more valid data volume.

[0087] Furthermore, after determining the effective axle weight data corresponding to the vehicle passing the scale, divide the effective axle weight data into N segments at equal time intervals, and calculate the equivalent average slope for each segment of the effective axle weight data to obtain K equivalent average slopes, where both N and K are integers greater than or equal to 2.

[0088] For example, referring to Figure 6 , divide the effective axle weight data into 4 segments, and the time interval between every two adjacent segments of data is t_step. Now calculate the equivalent average slope k_value_0 corresponding to the first two segments of data and the equivalent average slope k_value_1 corresponding to the last two segments of data respectively. The specific calculation formula of k_value_0 is:

[0089] k_value_0 = (A - B) / t_step 2 (1)

[0090] In formula (1),

[0091] A = sum(A_total(t A4 + t_step:t A4 + 2t_step)) (2)

[0092] B = sum(A_total(t A4 :t A4 + t_step)) (3)

[0093] In formulas (2) and (3), sum represents the summation function, and A_total(a:b) represents all data points in the data sequence A_total from time a to time b.

[0094] Similarly, the specific calculation formula for k_value_1 is:

[0095] k_value_0 = (C - D) / t_step 2 (4)

[0096] In formula (4),

[0097] C = sum(A_total(t A4 + 3t_step:t A1 )) (5)

[0098] D = sum(A_total(t A4 + 2t_step:t A4 + 3t_step)) (6)

[0099] Furthermore, after calculating the K equivalent average slopes, the K equivalent average slopes are calculated to obtain the first slope, where the first slope can reflect the influence of vehicle vibration on the axle weight data of the weighed axle.

[0100] In this application, the method for calculating the K equivalent average slopes can be:

[0101] Assign coefficients to each of the K equivalent average slopes to obtain K optimized average slopes;

[0102] Add the K optimized average slopes to obtain the first slope.

[0103] For example, after assigning coefficients 1 and -1 to k_value_0 and k_value_1 respectively, k_value_0 and -k_value_1 are obtained, and adding k_value_0 and -k_value_1, the obtained first slope is: k_value_0 - k_value_1.

[0104] When k_value_0 - k_value_1 = 0, it indicates that the vehicle vibration does not cause axle weight error to the weighed axle; when k_value_0 - k_value_1 > 0, it indicates that the vehicle vibration makes the axle weight data corresponding to the weighed axle greater than the true axle weight; when k_value_0 - k_value_1 < 0, it indicates that the vehicle vibration makes the axle weight data corresponding to the weighed axle less than the true axle weight.

[0105] To describe the relationship between the first slope and vehicle vibration in more detail, the following combines with reference Figure 7 To further explain the above conclusion, vehicle vibration is usually formed by the superposition of sine waves in different frequency bands and partial impulse responses. The sine waves in the low-frequency band have a greater impact on the effective axle weight data. If there are no low-frequency sine waves in the effective axle weight data, then the effective axle weight data is a horizontal line; if the effective axle weight data contains low-frequency sine waves such as Figure 7 shown in the first figure of Figure 7 , the low-frequency sine waves make the effective axle weight data greater than the true axle weight, and at this time the first slope is less than zero; if the effective axle weight data contains low-frequency sine waves such as Figure 7 shown in the second figure of

[0106] , the low-frequency sine waves do not cause axle weight error to the effective axle weight data, and at this time the first slope is equal to zero; if the effective axle weight data contains low-frequency sine waves such as

[0107] shown in the third figure of

[0108] , the low-frequency sine waves make the effective axle weight data less than the true axle weight data, and at this time the first slope is greater than zero.

[0109] In the embodiments of the present application, the preset model is a calculation model that reflects the mapping relationship between the first slope and the axle weight error compensation coefficient. The specific method for obtaining the preset model may be as follows: When multiple test vehicles with different weights pass over the weighing platform at different speeds, the axle weight data of each test is statistically recorded, and the axle weight data of each test is compared with the actual axle weight of the vehicle passing over the scale to calculate the axle weight error. Further, based on the axle weight error, the axle weight error compensation coefficient can be obtained. The specific calculation method is:

[0110] Axle weight error compensation coefficient = -Axle weight error / Actual axle weight;

[0111] While calculating the axle weight error compensation coefficient, record the first slope corresponding to the axle weight error. After multiple tests and obtaining a large amount of test data, a large number of axle weight error compensation coefficients and the first slope corresponding to each axle weight error compensation coefficient can be obtained. Next, according to the method of linear fitting, the functional relationship between the axle weight error compensation coefficient and the first slope can be obtained, and the model corresponding to this functional relationship is used as the above-mentioned preset model.

[0112] Based on the above preset model, the axle weight error compensation coefficient corresponding to the current first slope can be calculated. This compensation method has a short analysis time and can also improve the preset model to enhance the accuracy of axle weight compensation.

[0113] Further, after obtaining the axle weight error compensation coefficient, compensate the axle weight error of the axle of the vehicle passing over the scale. The compensated axle weight is:

[0114] Actual axle weight = Initial axle weight × (1 + Axle weight error compensation coefficient × 100%)

[0115] Among them, the initial axle weight corresponding to the axle of the vehicle passing over the scale can be calculated based on the effective axle weight data corresponding to the axle of the vehicle passing over the scale. The specific calculation method may be the integration method or the average method, which will not be described in detail here.

[0116] Based on the above compensation method for the axle weight error of the dynamic truck scale, after dividing the obtained effective axle weight data corresponding to the axle of the vehicle passing over the scale into N segments, calculate the equivalent average slope corresponding to each segment of data, and then compensate the axle weight error corresponding to the axle of the vehicle passing over the scale according to the relationship between these equivalent data average slopes and the axle weight data error compensation coefficient corresponding to the axle of the vehicle passing over the scale. Since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, the above method for compensating the axle weight error based on each equivalent average slope corresponding to the equivalent axle weight data of the axle of the vehicle passing over the scale considers the main cause of axle weight error, which is vehicle vibration, and has a high accuracy in compensating the axle weight error.

[0117] Based on the same inventive concept, an apparatus for compensating the axle weight error of a dynamic truck scale is also provided in the embodiments of the present application, asFigure 8 As shown in the figure, it is a schematic structural diagram of a dynamic axle weight error compensation device in this application. The device includes:

[0118] A calculation module 81, configured to evenly divide the effective axle weight data of the weighed axle into N segments at the same time interval, and calculate the equivalent average slope for each segment of the effective axle weight data to obtain K equivalent average slopes, where both N and K are positive integers greater than or equal to 2; according to the N equivalent average slopes, calculate a first slope, and the first slope can reflect the influence of vehicle vibration on the axle weight data of the weighed axle;

[0119] A first determination module 82, configured to determine the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient; compensate the axle weight error corresponding to the weighed axle according to the axle weight error compensation coefficient corresponding to the weighed axle.

[0120] In a possible design, the device further includes:

[0121] An acquisition module, configured to, after detecting that the current axle leaves the weighing platform, acquire M peaks corresponding to M axle weight data sequences of the weighed axle detected by M sensors, where M is an even number greater than or equal to 4;

[0122] A second determination module, configured to determine a first moment and a second moment corresponding to two peaks during the weighing time period, where the weighing time period is the time period corresponding to after the axle enters the weighing platform and before it leaves the weighing platform;

[0123] A summation module, configured to sum the axle weight data within the time period corresponding to the first moment and the second moment in the M axle weight data sequences to obtain the effective axle weight data of the weighed axle.

[0124] In a possible design, the device further includes:

[0125] An acquisition module, configured to stack the M axle weight data sequences according to the corresponding time to obtain the total axle weight data;

[0126] A first recording module, configured to record a third moment corresponding to the first threshold when the waveform corresponding to the total axle weight data crosses the first threshold from low to high;

[0127] A second recording module, configured to record a fourth moment corresponding to the second threshold when the waveform corresponding to the total axle weight data crosses the second threshold from high to low;

[0128] A third determination module, configured to use the time period corresponding to the third moment and the fourth moment as the weighing time period when the difference between the third moment and the fourth moment is greater than a third threshold.

[0129] In a possible design, the first determination module 82 is specifically configured to:

[0130] Compare the first slope with a preset database to obtain an axle weight error compensation coefficient corresponding to the first slope, where there is a one-to-one correspondence between the first slopes in the preset database and the axle weight error compensation coefficients;

[0131] Use the axle weight error compensation coefficient as the axle weight error compensation coefficient corresponding to the axle passing the scale.

[0132] In a possible design, the first determination module 82 is further configured to:

[0133] Input the first slope into a preset model for calculation to obtain a calculation result, where the preset model is a calculation model reflecting the mapping relationship between the first slope and the axle weight error compensation coefficient;

[0134] Use the calculation result as the axle weight error compensation coefficient corresponding to the axle passing the scale.

[0135] Based on the above dynamic weighbridge axle weight error compensation device, after dividing the obtained effective axle weight data corresponding to the axle passing the scale into N segments, calculate the equivalent average slope corresponding to each segment of data, and then compensate the axle weight error corresponding to the axle passing the scale according to the relationship between these equivalent data average slopes and the axle weight data error compensation coefficient corresponding to the axle passing the scale. Since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, therefore, the above method for compensating the axle weight error based on each equivalent average slope corresponding to the equivalent axle weight data of the axle passing the scale takes into account the main cause of axle weight error, which is vehicle vibration, and has a high accuracy in compensating the axle weight error.

[0136] Based on the same inventive concept, an electronic device is further provided in an embodiment of the present application. The electronic device can implement the functions of the foregoing dynamic weighbridge axle weight error compensation device. Refer to Figure 9 , the electronic device includes:

[0137] At least one processor 91, and a memory 92 connected to at least one processor 91. In the embodiment of the present application, the specific connection medium between the processor 91 and the memory 92 is not limited. Figure 5 It is taken as an example that the processor 91 and the memory 92 are connected through a bus 50. The bus 50 is in Figure 5The connection in the figure is represented by a thick line, and the connection methods between other components are only for illustrative purposes and are not limited thereto. The bus 50 can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 9 it is only represented by a thick line in the figure, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 91 can also be referred to as a controller, and no limitation is imposed on the name.

[0138] In the embodiment of the present application, the memory 92 stores instructions executable by at least one processor 91. By executing the instructions stored in the memory 92, at least one processor 91 can execute the dynamic weighbridge axle weight error compensation method described above. The processor 91 can implement Figure 8 the functions of each module in the device shown.

[0139] Among them, the processor 91 is the control center of the device. It can connect various parts of the entire control device through various interfaces and lines. By running or executing the instructions stored in the memory 92 and calling the data stored in the memory 92, various functions of the device and process data, so as to monitor the device as a whole.

[0140] In a possible design, the processor 91 may include one or more processing units. The processor 91 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the processor 91. In some embodiments, the processor 91 and the memory 92 can be implemented on the same chip. In some embodiments, they can also be implemented separately on independent chips.

[0141] The processor 91 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor, etc. The steps of the dynamic weighbridge axle weight error compensation method disclosed in combination with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0142] The memory 92, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The memory 92 can include at least one type of storage medium. For example, it can include flash memory, hard disks, multimedia cards, card-type memories, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memories, magnetic disks, optical discs, etc. The memory 92 is any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 92 in the embodiments of the present application can also be a circuit or any other device capable of implementing a storage function, for storing program instructions and / or data.

[0143] By designing and programming the processor 91, the code corresponding to the dynamic weighbridge axle weight error compensation method introduced in the foregoing embodiments can be solidified into the chip, so that the chip can execute Figure 1 the steps of the dynamic weighbridge axle weight error compensation method of the illustrated embodiment. How to design and program the processor 91 is a well-known technology to those skilled in the art and will not be elaborated here.

[0144] Based on the same inventive concept, the embodiments of the present application also provide a storage medium storing computer instructions, which, when run on a computer, cause the computer to execute the dynamic weighbridge axle weight error compensation method discussed above.

[0145] In some possible implementation manners, each aspect of the dynamic weighbridge axle weight error compensation method provided in the present application can also be implemented in the form of a program product, which includes program code. When the program product runs on a device, the program code is used to cause the control device to execute the steps in the dynamic weighbridge axle weight error compensation method according to various exemplary embodiments of the present application described above in this specification.

[0146] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0147] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0148] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0149] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0150] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A compensation method for the axle weight error of a dynamic weighbridge, characterized in that The method includes: After detecting that the current axle leaves the weighing platform, obtaining M peak values corresponding to M axle weight data sequences of the weighed axle detected by M sensors, where M is an even number greater than or equal to 4; Determining a first moment and a second moment corresponding to two peak values within the weighing time period, where the weighing time period is the time period corresponding to after the axle enters the weighing platform and before it leaves the weighing platform; Summing the axle weight data within the time period corresponding to the first moment and the second moment in the M axle weight data sequences to obtain the effective axle weight data of the weighed axle; Dividing the effective axle weight data of the weighed axle into N segments at equal time intervals, and calculating the equivalent average slope for each segment of effective axle weight data to obtain N equivalent average slopes, where N is a positive integer greater than or equal to 2; the equivalent average slope is obtained based on the ratio between the difference between a first value and a second value and the square of the time interval, and the first value and the second value are effective axle weight data in different time periods; Assigning coefficients to each of the N equivalent average slopes to obtain N optimized average slopes; adding the N optimized average slopes to obtain a first slope, and the first slope can reflect the influence of vehicle vibration on the axle weight data of the weighed axle; Determining the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient; Compensating the axle weight error corresponding to the weighed axle according to the axle weight error compensation coefficient corresponding to the weighed axle.

2. The method according to claim 1, wherein Before detecting that the current axle leaves the weighing platform, it further includes: Superposing the M axle weight data sequences according to the corresponding time to obtain the total axle weight data; When the waveform corresponding to the total axle weight data crosses a first threshold from low to high, recording the third moment corresponding to the first threshold; When the waveform corresponding to the total axle weight data crosses a second threshold from high to low, recording the fourth moment corresponding to the second threshold; When the difference between the third moment and the fourth moment is greater than a third threshold, taking the time period corresponding to the third moment and the fourth moment as the weighing time period.

3. The method according to claim 1, wherein Determining the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient, including: Comparing the first slope with a preset database to obtain the axle weight error compensation coefficient corresponding to the first slope, where the first slope in the preset database and the axle weight error compensation coefficient are in one-to-one correspondence; Taking the axle weight error compensation coefficient as the axle weight error compensation coefficient corresponding to the weighed axle.

4. The method according to claim 1, wherein Determining the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient, including: Inputting the first slope into a preset model for calculation to obtain a calculation result, where the preset model is a calculation model reflecting the mapping relationship between the first slope and the axle weight error compensation coefficient; Taking the calculation result as the axle weight error compensation coefficient corresponding to the weighed axle.

5. A compensation device for the axle weight error of a dynamic weighbridge, characterized in that, The device includes: An acquisition module, configured to, after detecting that the current axle leaves the weighing platform, acquire M peak values corresponding to M axle weight data sequences of the weighed axle detected by M sensors, where M is an even number greater than or equal to 4; A second determination module, configured to determine a first moment and a second moment corresponding to two peak values within a weighing time period, where the weighing time period is the time period corresponding to after the axle enters the weighing platform and before it leaves the weighing platform; A summation module, configured to sum the axle weight data within the time period corresponding to the first moment and the second moment in the M axle weight data sequences to obtain the effective axle weight data of the weighed axle; A calculation module, configured to evenly divide the effective axle weight data of the weighed axle into N segments at the same time interval, and calculate the equivalent average slope for each segment of effective axle weight data to obtain N equivalent average slopes, assign coefficients to each of the N equivalent average slopes to obtain N optimized average slopes; sum the N optimized average slopes to obtain a first slope, where N is a positive integer greater than or equal to 2; the equivalent average slope is obtained based on the ratio between the difference between a first value and a second value and the square of the time interval, and the first value and the second value are effective axle weight data in different time periods; the first slope can reflect the influence of vehicle vibration on the axle weight data of the weighed axle; A first determination module, configured to determine the axle weight error compensation coefficient corresponding to the weighed axle according to the relationship between the first slope and the axle weight error compensation coefficient; A compensation module, configured to compensate the axle weight error corresponding to the weighed axle according to the axle weight error compensation coefficient corresponding to the weighed axle.

6. The device according to claim 5, characterized in that, The first determination module is specifically configured to: Compare the first slope with a preset database to obtain the axle weight error compensation coefficient corresponding to the first slope, where there is a one-to-one correspondence between the first slope and the axle weight error compensation coefficient in the preset database; Use the axle weight error compensation coefficient as the axle weight error compensation coefficient corresponding to the weighed axle.

7. The device according to claim 5, characterized in that The first determination module is further configured to: Input the first slope into a preset model for calculation to obtain a calculation result, where the preset model is a calculation model reflecting the mapping relationship between the first slope and the axle weight error compensation coefficient; Use the calculation result as the axle weight error compensation coefficient corresponding to the weighed axle.

8. An electronic device, characterized in that, It includes: A memory, configured to store a computer program; A processor, configured to, when executing the computer program stored on the memory, implement the method steps described in any one of claims 1-4.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements the method steps described in any one of claims 1-4.

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