CN115371790A - Sensor calibration and weighing method of vehicle dynamic weighing system - Google Patents
Sensor calibration and weighing method of vehicle dynamic weighing system Download PDFInfo
- Publication number
- CN115371790A CN115371790A CN202211087900.5A CN202211087900A CN115371790A CN 115371790 A CN115371790 A CN 115371790A CN 202211087900 A CN202211087900 A CN 202211087900A CN 115371790 A CN115371790 A CN 115371790A
- Authority
- CN
- China
- Prior art keywords
- sensor
- vehicle
- weighing
- speed
- sensors
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000005303 weighing Methods 0.000 title claims abstract description 93
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000005316 response function Methods 0.000 claims abstract description 27
- 238000004364 calculation method Methods 0.000 claims description 12
- 230000002902 bimodal effect Effects 0.000 claims description 2
- 238000005259 measurement Methods 0.000 abstract description 9
- 238000012360 testing method Methods 0.000 abstract description 4
- 238000005070 sampling Methods 0.000 description 6
- 230000003068 static effect Effects 0.000 description 5
- 238000002474 experimental method Methods 0.000 description 4
- 238000009434 installation Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000005096 rolling process Methods 0.000 description 2
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G23/00—Auxiliary devices for weighing apparatus
- G01G23/01—Testing or calibrating of weighing apparatus
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
- G01G19/03—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Algebra (AREA)
- Measuring Fluid Pressure (AREA)
Abstract
The invention relates to a sensor calibration and weighing method of a vehicle dynamic weighing system, which comprises the following steps: step 1, constructing a vehicle dynamic weighing system; the weighing system comprises sensors for weighing m groups of vehicles which are sequentially arranged on a road surface in a front-back order; step 2, calibrating the weighing system in the step 1 to obtain a calibrated weighing system; step 3, when any multi-shaft vehicle to be weighed passes through the calibrated weighing system in the step 2, acquiring the speed v of the vehicle to be weighed s And the pressure signal collected by each sensor; calculating to obtain an ideal pressure model of each tire of the vehicle to be weighed according to the pressure signal acquired by each sensor and the dynamic response function of each sensor; and obtaining the dynamic weighing weight of the vehicle to be weighed. Compared with the traditional method, the method is nearly tenThe calibration test of the rest times greatly reduces the calibration times; and the measurement precision of the calibrated sensor is doubled compared with that of the traditional method.
Description
Technical Field
The invention relates to the technical field of weighing, in particular to a sensor calibration and weighing method of a vehicle dynamic weighing system.
Background
In recent years, the total road mileage and the road density of China rise year by year, and the road traffic mileage is the first in the world at the bottom of 2020. While the highway network is constructed in a large scale, overload and over-limit transportation become bottlenecks which restrict the development of the transportation industry. The overload transportation means that the freight vehicle exceeds the total vehicle and cargo mass and axle load mass limit standard specified by laws, regulations and regulations or exceeds the load limit standard marked by road traffic prohibition signs and runs on roads, road bridges and road tunnels with the limit standard. The harm is mainly that the highway and bridge facilities are seriously damaged, road traffic accidents are frequent, the transportation market order is disturbed, huge loss is caused to the country, the life and property safety of people is harmed, and the social hazard is obvious. According to the calculation, if the vehicles running on the road are overloaded by about 50%, the normal service life of the road is shortened by about 80%. Weighing a suspected overweight cargo vehicle is the main basis for carrying out overload penalty. Therefore, accurate measurement of the actual load of the transportation vehicle is particularly important for the regulatory authorities to monitor and enforce law legally and effectively.
At present, the method for gross weight (load) of large freight vehicles mainly comprises a static wagon balance method and a dynamic weighing method. The wagon balance method is a mature vehicle load detection technology, a vehicle must enter a special over-limit transportation detection station to be weighed according to the requirements of related workers, the method requires that the vehicle is weighed on a wagon balance (a flat sensor) in a static state or a low-speed state (less than or equal to 40 km/h), the measurement precision is high, but the detection efficiency is low, the working strength of law enforcement personnel is high, the coverage area is small, and the illegal over-limit overload is difficult to be fundamentally controlled. The dynamic weighing method consists of a group of sensors (mostly resistance strain type narrow sensors) and corresponding hardware measuring equipment, and can calculate the information of the weight, the number of axles, the speed and the like of the passing vehicle according to the pressure of the running vehicle tire to the ground sensor, thereby realizing the off-site high-efficiency law enforcement. However, the existing dynamic weighing system and related products mainly adopt a peak signal of a sensor to calculate the load of a vehicle during passing, and the error of a measurement result of the system is large when the system is at low speed and high speed. In addition, when the system is installed and debugged to calibrate the sensor, a large number of measurement experiments are carried out by using the weight vehicle with the load calibrated and adopting various different vehicle speeds, and the sensor calibration is realized by adopting a fitting method. The method has large calibration experiment amount and long calibration time, can be realized in the system installation stage of road closure, and is difficult to realize long-time road closure for system calibration verification once the road closure passes delivery and use, particularly on a large-flow road section. The large loading error of the vehicle easily causes law enforcement disputes, and the long calibration time brings difficulty to later system maintenance. Therefore, how to realize the calibration of the dynamic weighing system of the vehicle quickly and realize the weighing of the dynamic vehicle with high precision is urgent.
Disclosure of Invention
The invention aims to solve the technical problem of providing a sensor calibration and weighing method of a vehicle dynamic weighing system, which has simpler calibration and higher weighing accuracy.
The technical scheme adopted by the invention for solving the technical problems is as follows: a sensor calibration and weighing method of a vehicle dynamic weighing system is characterized by comprising the following steps:
the weighing system comprises m groups of sensors for weighing the vehicles, wherein the m groups of sensors are sequentially arranged on the road surface in a front-back order, and m is a natural number more than or equal to 2;
the sensors for weighing each group of vehicles comprise a first sensor and a second sensor which are arranged side by side at intervals; the first sensor and the second sensor are respectively used for collecting the pressure of tires on two sides of the vehicle to the road surface;
step 2, calibrating the weighing system in the step 1 to obtain a calibrated weighing system;
the specific calibration method comprises the following steps:
step 2-1, a vehicle with known weight H is used as a vehicle for sensor calibration, and the vehicle for sensor calibration is an N-axis vehicle; wherein N is a natural number greater than or equal to 2; the N-axis vehicle is correspondingly provided with N pairs of tires;
step 2-2, enabling the vehicle for calibrating the sensor to pass through the sensor mounting area in the step 1 at M different vehicle speeds respectively, and obtaining pressure signals collected by each sensor at different vehicle speeds; wherein a pair of tires respectively pass through a first sensor and a second sensor in a group of sensors; m is a natural number greater than or equal to 2;
step 2-3, acquiring the corresponding vehicle speeds of the sensor calibration vehicles under M different vehicle speeds;
step 2-4, selecting the minimum value of the vehicle speeds from the M different vehicle speeds in the step 2-3, and calculating the dynamic response function of each sensor under the minimum vehicle speed;
the calculation method of the dynamic response function of each sensor comprises the following steps:
step 2-4 (1), setting the dynamic response function g (x) of each sensor as a standard Gaussian function, and calculating the formula as follows:
wherein x is time; σ is the standard deviation;
step 2-4 (2), a grounding ideal pressure model f (x) when the tire is pressed and rolled is set as a bimodal Gaussian function, and the calculation formula is as follows:
wherein a, b and c are all coefficients and are all constants;
step 2-4 (3), when the tire passes through the sensor for weighing the vehicle, the pressure signal f' (x) acquired by the sensor is as follows:
wherein,
calculating for convolution;
and 2-4 (4) substituting the pressure signals of the N tires acquired by each sensor at the minimum vehicle speed into the step 2-4 (3), and iteratively solving a best fit solution to obtain the tire pressure sensor, wherein the pressure signals of the N tires are acquired by each sensor at the minimum vehicle speed: the sigma value in the dynamic response function of each sensor and the a, b and c values in the ideal pressure model function of each tire at the minimum vehicle speed;
step 2-5, according to the pressure signals collected by each sensor under M-1 different vehicle speeds except the minimum vehicle speed and the dynamic response function of each sensor in the step 2-4, carrying out iteration on the formula in the step 2-4 (3) to obtain an optimal fitting solution, and calculating to obtain an ideal pressure model of each tire under different vehicle speeds;
step 2-6, integrating the ideal pressure model of each tire at the same speed to obtain the pressure characteristic value of each tire passing through different sensors at the same speed, and dividing the sum of the pressure characteristic values of all the sensors at the same speed by m to obtain the finished automobile weight characteristic value at the same speed;
step 2-7, substituting M different speeds v and the finished automobile weight characteristic values f (v) corresponding to the different speeds v into a formula:
f(v)＝h·exp(q*v)+k
performing exponential function fitting to obtain optimal fitting parameters h, q and k;
step 3, when any multi-shaft vehicle to be weighed passes through the calibrated weighing system in the step 2, acquiring the speed vs of the vehicle to be weighed and pressure signals acquired by each sensor;
according to the pressure signals collected by each sensor and the dynamic response function of each sensor in the step 2-4, carrying out iteration on the formula in the step 2-4 (3) to obtain an optimal fitting solution, and calculating to obtain an ideal pressure model of each tire of the vehicle to be weighed; then according to the same method in the step 2-6, calculating to obtain the current speed v of the vehicle to be weighed s Lower whole vehicle weight characteristic value w s ；
Will speed v s Obtaining a whole vehicle weight characteristic value f (v) corresponding to the vehicle for calibrating the sensor in a formula obtained by fitting in the step 2-7 s )，f(v s ) Corresponds to h.exp (q.v.) s ) + k; the dynamic weighing weight W of the vehicle to be weighed s Is composed of
In order to realize the weighing of the freight vehicle, the sensor for weighing the vehicle in the step 1 is preferably a narrow-band sensor.
Preferably, the separation distance d between the sensors for weighing any two adjacent groups of vehicles in the step 1 is the same.
As an improvement, the vehicle speed obtaining method of the vehicle for sensor calibration in the step 2-3 comprises the following steps:
calculating the vehicle speed according to the pressure signals acquired by each sensor in the step 2-2; the specific calculation method comprises the following steps:
acquiring peak positions in pressure signals acquired by m first sensors or second sensors on the same side, calculating time difference corresponding to the two adjacent peak positions, wherein the time difference corresponds to the time difference when the same tire passes through the two adjacent first sensors or second sensors, and obtaining the speed of the same tire passing through the two adjacent first sensors or second sensors through the condition that the separation distance d of the sensors for vehicle weighing is in the time difference;
and according to the same method, calculating the vehicle speed according to the peak position of each tire passing through each sensor, and taking the average value of all the speeds as the final vehicle speed.
Further, the speed v of the vehicle to be weighed in the step 3 s The obtaining method of (2) is the same as that in step (2-3).
Compared with the prior art, the invention has the advantages that: the method comprises the steps of firstly calculating a dynamic response function of each sensor, reversely calculating a grounding ideal pressure model when each tire rolls under pressure on the basis of the dynamic response function, and reducing the influence of noise and tire deformation on weight measurement results to the maximum extent by reversely calculating the model and integrating. Therefore, the method can finish the calibration work by the weight vehicles at different speeds passing through the vehicle for sensor calibration, and compared with the traditional calibration test run for more than ten times, the calibration times are greatly reduced; and the measurement precision of the calibrated sensor is doubled compared with that of the traditional method.
Drawings
FIG. 1 is a schematic view of a vehicle passing weighing system in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a sensor arrangement according to an embodiment of the present invention;
FIG. 3 is a graph of the pressure signal collected by sensor 1 of FIG. 2;
FIG. 4 is a graph of pressure signals collected by sensor 2 of FIG. 2;
FIG. 5 is a graph of pressure signals collected by sensor 3 of FIG. 2;
FIG. 6 is a graph of pressure signals collected by sensor 4 of FIG. 2;
FIG. 7 is a graph of the peak signals of sensor 1 and sensor 3 of FIGS. 3 and 5;
FIG. 8 is a graph of pressure signals collected by sensor 1 of FIG. 3 for the 1 st tire;
FIG. 9 is a graph of the dynamic response function of sensor 1 of FIG. 2;
fig. 10 is a graph showing an ideal contact pressure model in the case of pressure rolling of the 1 st tire in fig. 8.
Detailed Description
The invention is described in further detail below with reference to the accompanying examples.
The sensor calibration and weighing method of the vehicle dynamic weighing system in the embodiment comprises the following steps:
the weighing system comprises m groups of sensors for weighing the vehicles, wherein the m groups of sensors are sequentially arranged on the road surface in a front-back order, and m is a natural number more than or equal to 2; the sensors for weighing each group of vehicles comprise a first sensor and a second sensor which are arranged side by side at intervals; the first sensor and the second sensor are respectively used for collecting the pressure of tires on two sides of the vehicle to the road surface;
in the embodiment, the sensor for weighing the vehicle is a narrow-band sensor; the vehicle dynamic weighing system is mainly applied to weighing freight vehicles;
generally, in engineering installation, the spacing distance d between sensors for weighing any two adjacent groups of vehicles is the same; the sequential installation intervals of the narrow strip sensors on the left side and the right side are also the same; as shown in fig. 1; the sensor is represented by a horizontal line, and wheels on two sides are respectively correspondingly pressed in the centers of the first sensor and the second sensor in the running process of the vehicle;
the narrow strip sensor is subjected to static pressure test when leaving a factory, but the test mode method is not in accordance with the actual use, and dynamic calibration is required after field installation;
step 2, calibrating the weighing system in the step 1 to obtain a calibrated weighing system;
the specific calibration method comprises the following steps:
step 2-1, a vehicle with a known weight H is used as a sensor calibration vehicle, and the sensor calibration vehicle is an N-axis vehicle; wherein N is a natural number greater than or equal to 2; the N-axis vehicle is correspondingly provided with N pairs of tires;
in the embodiment, the vehicle for calibrating the sensor is a weight vehicle with known weight, and the total weight of the weight vehicle is obtained by weighing by a static wagon balance method;
step 2-2, enabling the vehicle for calibrating the sensor to pass through the sensor mounting area in the step 1 at M different vehicle speeds respectively, and obtaining pressure signals collected by each sensor at different vehicle speeds; wherein a pair of tires respectively pass through a first sensor and a second sensor in a group of sensors; m is a natural number greater than or equal to 2; in this embodiment, M =3; at least comprises a high speed, a medium speed and a low speed;
step 2-3, acquiring the corresponding vehicle speeds of the sensor calibration vehicles under M different vehicle speeds;
in this embodiment, the vehicle speed obtaining method for the vehicle for sensor calibration includes:
calculating the vehicle speed according to the pressure signals acquired by each sensor in the step 2-2; the specific calculation method comprises the following steps:
acquiring peak positions in pressure signals acquired by m first sensors or second sensors on the same side, calculating time difference corresponding to the two adjacent peak positions, wherein the time difference corresponds to the time difference when the same tire passes through the two adjacent first sensors or second sensors, and obtaining the speed of the same tire passing through the two adjacent first sensors or second sensors through the condition that the separation distance d of the sensors for vehicle weighing is in the time difference;
according to the same method, the vehicle speed is calculated according to the peak position of each tire passing through each sensor, and the average value of all the speeds is taken as the final vehicle speed;
step 2-4, selecting the minimum value of the vehicle speeds from the M different vehicle speeds in the step 2-3, and calculating the dynamic response function of each sensor under the minimum vehicle speed;
the calculation method of the dynamic response function of each sensor comprises the following steps:
step 2-4 (1), setting the dynamic response function g (x) of each sensor as a standard Gaussian function, and calculating the formula as follows:
wherein x is time; σ is the standard deviation;
step 2-4 (2), a grounding ideal pressure model f (x) when the tire rolls under pressure is set as a double-peak Gaussian function, and the calculation formula is as follows:
wherein a, b and c are all coefficients and are all constants;
the ideal ground contact pressure model when the tire rolls under pressure is as follows: an ideal pressure model of the tire contacting with the ground when the tire is pressed and rolling;
step 2-4 (3), when the tire passes through the sensor for weighing the vehicle, the pressure signal f' (x) acquired by the sensor is as follows:
wherein,
calculating for convolution;
and 2-4 (4) substituting the pressure signals of the N tires acquired by each sensor at the minimum vehicle speed into the step 2-4 (3), and iteratively solving a best fit solution to obtain the tire pressure sensor, wherein the pressure signals of the N tires are acquired by each sensor at the minimum vehicle speed: the sigma value in the dynamic response function of each sensor and the a, b and c values in the ideal pressure model function of each tire at the minimum vehicle speed;
step 2-5, according to the pressure signals collected by each sensor under M-1 different vehicle speeds except the minimum vehicle speed and the dynamic response function of each sensor in the step 2-4, carrying out iteration on the formula in the step 2-4 (3) to obtain an optimal fitting solution, and calculating to obtain an ideal pressure model of each tire under different vehicle speeds;
step 2-6, integrating the ideal pressure model of each tire at the same speed to obtain the pressure characteristic value of each tire passing through different sensors at the same speed, and dividing the sum of the pressure characteristic values of all the sensors at the same speed by m to obtain the finished automobile weight characteristic value at the same speed;
step 2-7, substituting M different speeds v and the finished automobile weight characteristic values f (v) corresponding to the different speeds v into a formula:
f(v)＝h·exp(q*v)+k
performing exponential function fitting to obtain optimal fitting parameters h, q and k;
step 3, when any multi-shaft vehicle to be weighed passes through the calibrated weighing system in the step 2, acquiring the speed v of the vehicle to be weighed s And the pressure signal collected by each sensor; in this embodiment, the speed v of the vehicle to be weighed s The obtaining method of (2) is the same as that in the step (2-3);
according to the pressure signal acquired by each sensor and the dynamic response function of each sensor in the step 2-4, carrying out iteration on the formula in the step 2-4 (3) to obtain an optimal fitting solution, and calculating to obtain an ideal pressure model of each tire of the vehicle to be weighed; then according to the same method in the step 2-6, calculating to obtain the current speed v of the vehicle to be weighed s Lower whole vehicle weight characteristic value w s ；
Will speed v s Obtaining a whole vehicle weight characteristic value f (v) corresponding to the vehicle for calibrating the sensor in a formula obtained by fitting in the step 2-7 s )，f(v s ) Corresponds to h.exp (q.v.) s ) + k; the dynamic weighing weight W of the vehicle to be weighed s Is composed of
In order to facilitate understanding of the method in the present invention, the method is described by taking the following experiments as examples, in this embodiment, sensors for weighing vehicles are strip sensors, and are installed on a road surface, the value of m is 2, as shown in fig. 2, a sensor 3 and a sensor 4 are one group, a sensor 1 and a sensor 2 are another group, the adjacent distance between the front group of sensors and the rear group of sensors is 2.5 meters, the strip sensors are divided into left and right sides, the left side is used for collecting the pressure of a left wheel of a truck against the ground, the right side is used for collecting the pressure of a right wheel of the truck against the ground, and the sampling interval fs of a sensor collecting system is 7812.5Hz.
During a sensor calibration experiment, a 3-shaft weight vehicle (namely, the left side and the right side of a vehicle are respectively provided with 3 tires) is adopted, the total weight of the weight vehicle is weighed by adopting a static wagon balance to obtain H =23440kg, and a worker drives the weight vehicle to normally run on a road and pass through a sensor mounting area at a constant speed. The weighing system obtains pressure change data for each wheel as it passes the sensor, the pressure data obtained by each sensor being shown in figures 3 to 6.
The peak signals of the sensor 1 and the sensor 3 are compared (the peak signals of the sensor 2 and the sensor 4 are compared), and the peak signals of the sensor 1 and the sensor 3 are taken as an example, as shown in fig. 7. In fig. 7, the solid line represents the real-time pressure signal of the sensor 1, and the broken line represents the real-time pressure signal of the sensor 3.
The peak positions (abscissa values) of the peak signals of the sensor 1 and the sensor 3 in fig. 7 are taken, the peak positions of the sensor 1 are 3182, 8588 and 10209 respectively, and the peak positions of the sensor 3 are 6282, 11728 and 13349 respectively. Therefore, the time difference (unit: s) of the same tire pressure sensor 1 and sensor 3 is:
(6282-3182)/7812.5＝0.397；(11728-8588)/7812.5＝0.402；(13349-10209)/7812.5＝0.402
the speed of the weight vehicle is the time difference divided by the adjacent distance between the front sensor and the rear sensor by 2.5m, and the speed is respectively as follows: 2.5m/0.397s ≈ 6.297m/s ≈ 22.67km/h, 2.5m/0.402s ≈ 6.219m/s ≈ 22.39km/h, 2.5m/0.402s ≈ 6.219m/s ≈ 22.39km/h. And finally, the average value of the vehicle speed is 22.49km/h.
The weight vehicle is driven to pass through the weighing system at 3 different vehicle speeds (about 40km/h, 35km/h and 14 km/h) to obtain a pressure signal when the weight vehicle passes through the weighing system.
Because the dynamic response function of each sensor is related to the sampling frequency of the sensor, and the sampling frequency of the sensor is a fixed value, if the speed of the vehicle is high and the sampling frequency cannot be kept up with the sampling frequency, the calculated dynamic response function is inaccurate in calculation due to insufficient data in the change process. If the sampling frequency is sufficient when the vehicle speed is slow, the dynamic response function of the sensor is measured, so that the dynamic response function of each sensor is calculated by using the real-time pressure signal of the sensor with the speed per hour of about 14km/h in the embodiment. The number of the axles of the weight vehicle is 3, taking the weight vehicle as an example of the sensor 1 when passing through the dynamic weighing system, the weight vehicle can acquire grounding pressure signals (namely pressure signals contacting with the ground) when 3 groups of tires roll, as shown in fig. 3. And substituting 3 groups of pressure signals into a formula (3) to repeatedly and circularly iterate to solve the optimal fitting solution. The left first tire pressure signal collected by sensor 1 in fig. 3 is shown enlarged as shown in fig. 8.
Fitting an optimal solution to
That is, the standard deviation σ =20, and the corresponding curve is shown in fig. 9, and the ideal contact pressure model when the 1 st tire on the left side of the vehicle rolls under pressure is
I.e. standard deviation a =0.4, b =90, c =120, the corresponding curve is shown in fig. 10.
To pair
The curves are integrated to obtain: 170.155, which is the weight characteristic for the 1 st tire at the current speed.
And calculating the weight characteristic values of all tires passing through the sensors at the current speed, wherein the weight characteristic values are shown in table 1, adding all the weight characteristic values in table 1, and dividing by the number of the sensors (groups) 2 to obtain the finished vehicle weight characteristic value 1372.16 of the weight vehicle at the current speed.
TABLE 1 weight characteristic of weight vehicle passing sensor at 14km/h speed for each tire
| |
Sensor 2 | Sensor 3 | Sensor 4 | |
| |
170.155 | 178.95 | 167.46 | 182.518 |
| Tyre 2 | 237.964 | 275.434 | 250.13 | 255.034 |
| Tyre 3 | 270.722 | 256.036 | 266.545 | 233.375 |
The characteristic values of the weight of the whole weight of the weight vehicle at 3 different vehicle speeds and the corresponding speed are calculated according to the patent method, and the results are shown in table 2.
TABLE 2 complete vehicle weight characteristic values at different speeds
| Speed (km/h) | Characteristic value of weight of whole vehicle |
| 40.91 | 1553.148 |
| 34.68 | 1502.206 |
| 14.3 | 11372.159 |
Substituting the speed as an independent variable x1 and the whole vehicle weight characteristic value as a dependent variable f (x 1) into a formula: f (x 1) = h · exp (q × x 1) + k, and the best fit parameter is obtained, the calculation results are: h =40375.1, q = -0.0887k =0.1, and the dynamic calibration work is completed.
When any freight vehicle passes through the calibrated weighing system, firstly, the vehicle passing speed v is calculated s Then obtaining the pressure signal when each tire passes through each sensor, obtaining the optimal fitting parameter solution of the ideal pressure model through repeated cycle iteration by using the dynamic response function of each sensor, integrating the optimal fitting parameter solution, and obtaining the finished weight characteristic value w of the weight vehicle at the vehicle speed by dividing the optimal fitting parameter solution by the number (m) of the strip sensor groups s ；
The current vehicle speed v s Substituting into formula f (v) s )＝40375.1·exp(-0.0887v s ) +0.1, obtaining a weight characteristic value f (v) corresponding to the weight H s ) Then the dynamic weighing weight W of the freight vehicle s Is composed of
Comparing the method of the invention with the traditional method of taking wave crest as weight characteristic value, the weighing results under 3 speeds are adopted for calibration, and then the dynamic weighing errors under other speeds are measured. The results of the conventional measurement method are shown in table 3; the measurement results of the method of the patent are shown in Table 4. The comparison of the two results shows that the average error value of the traditional method is 1.45%, the maximum weighing error is 875.72kg, the average error value of the method is 0.74%, and the maximum weighing error is 356.9kg, so that the measurement precision is effectively improved.
TABLE 3 weighing results of the conventional wave crest method
Table 4 weighing results of the weighing method of the present invention
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the technical principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (5)
1. A sensor calibration and weighing method of a vehicle dynamic weighing system is characterized by comprising the following steps:
step 1, constructing a vehicle dynamic weighing system;
the weighing system comprises m groups of sensors for weighing the vehicles, wherein the m groups of sensors are sequentially arranged on a road surface in a front-back order, and m is a natural number greater than or equal to 2;
the sensors for weighing each group of vehicles comprise a first sensor and a second sensor which are arranged side by side at intervals; the first sensor and the second sensor are respectively used for collecting the pressure of tires on two sides of the vehicle to the road surface;
step 2, calibrating the weighing system in the step 1 to obtain a calibrated weighing system;
the specific calibration method comprises the following steps:
step 2-1, a vehicle with known weight H is used as a vehicle for sensor calibration, and the vehicle for sensor calibration is an N-axis vehicle; wherein N is a natural number greater than or equal to 2; the N axles are correspondingly N pairs of tires;
step 2-2, enabling the vehicle for calibrating the sensor to pass through the sensor mounting area in the step 1 at M different vehicle speeds respectively, and obtaining pressure signals collected by each sensor at different vehicle speeds; one pair of tires respectively and correspondingly passes through a first sensor and a second sensor in a group of sensors; m is a natural number greater than or equal to 3;
step 2-3, acquiring corresponding vehicle speeds of the sensor calibration vehicles under M different vehicle speeds;
step 2-4, selecting the minimum value of the vehicle speeds from the M different vehicle speeds in the step 2-3, and calculating the dynamic response function of each sensor under the minimum vehicle speed;
the calculation method of the dynamic response function of each sensor comprises the following steps:
step 2-4 (1), setting the dynamic response function g (x) of each sensor as a standard Gaussian function, and calculating the formula as follows:
wherein x is time; σ is the standard deviation;
step 2-4 (2), a grounding ideal pressure model f (x) when the tire is pressed and rolled is set as a bimodal Gaussian function, and the calculation formula is as follows:
wherein a, b and c are all coefficients and are all constants;
step 2-4 (3), when the tire passes through the sensor for weighing the vehicle, the pressure signal f' (x) acquired by the sensor is as follows:
wherein,
calculating for convolution;
step 2-4 (4), substituting the pressure signals of the N tires acquired by each sensor at the minimum vehicle speed into the step 2-4 (3), and iteratively solving a best fit solution to obtain the tire pressure signal, wherein the tire pressure signal comprises the following components: the sigma value in the dynamic response function of each sensor and the a, b and c values in the ideal pressure model function of each tire at the minimum vehicle speed;
step 2-5, according to the pressure signals collected by each sensor under M-1 different vehicle speeds except the minimum vehicle speed and the dynamic response function of each sensor in the step 2-4, carrying out iteration on the formula in the step 2-4 (3) to obtain an optimal fitting solution, and calculating to obtain an ideal pressure model of each tire under different vehicle speeds;
step 2-6, integrating the ideal pressure model of each tire at the same speed to obtain the pressure characteristic value of each tire passing through different sensors at the same speed, and dividing the sum of the pressure characteristic values of all the sensors at the same speed by m to obtain the finished automobile weight characteristic value at the same speed;
step 2-7, substituting M different speeds v and the finished automobile weight characteristic values f (v) corresponding to the different speeds v into a formula:
f(v)＝h·exp(q*v)+k
performing exponential function fitting to obtain optimal fitting parameters h, q and k;
step 3, when any multi-shaft vehicle to be weighed passes through the calibrated weighing system in the step 2, acquiring the speed v of the vehicle to be weighed s And pressure signals collected by each sensor;
according to the pressure signal acquired by each sensor and the dynamic response function of each sensor in the step 2-4, carrying out iteration on the formula in the step 2-4 (3) to obtain an optimal fitting solution, and calculating to obtain an ideal pressure model of each tire of the vehicle to be weighed; then according to the same method in the step 2-6, calculating to obtain the current speed v of the vehicle to be weighed s Lower whole vehicle weight characteristic value w s ；
Will speed v s Obtaining a whole vehicle weight characteristic value f (v) corresponding to the vehicle for calibrating the sensor in a formula obtained by fitting in the step 2-7 s )，f(v s ) Corresponding to h.exp (q. X.v) s ) + k; the dynamic weighing weight W of the vehicle to be weighed s Is composed of
2. The method for calibrating and weighing the sensor of the dynamic weighing system of the vehicle according to claim 1, characterized in that: the sensor for weighing the vehicle in the step 1 is a narrow-band sensor.
3. The method for calibrating and weighing the sensor of the dynamic weighing system of the vehicle according to claim 2, characterized in that: in the step 1, the spacing distance d between the sensors reused by any two adjacent groups of vehicles is the same.
4. The method for calibrating and weighing the sensor of the dynamic weighing system of the vehicle according to claim 3, characterized in that: the vehicle speed obtaining method of the vehicle for sensor calibration in the step 2-3 comprises the following steps:
calculating the vehicle speed according to the pressure signals acquired by each sensor in the step 2-2; the specific calculation method comprises the following steps:
acquiring peak positions in pressure signals acquired by m first sensors or m second sensors on the same side, calculating the time difference corresponding to the two adjacent peak positions, wherein the time difference is the time difference of the same tire passing through the two adjacent first sensors or second sensors, and obtaining the speed of the same tire passing through the two adjacent first sensors or second sensors by keeping the sensor interval distance d for weighing the vehicle at the time difference;
and according to the same method, calculating the vehicle speed according to the peak position of each tire passing through each sensor, and taking the average value of all the speeds as the final vehicle speed.
5. The method for calibrating and weighing the sensor of the dynamic weighing system of the vehicle according to claim 4, characterized in that: the speed v of the vehicle to be weighed in the step 3 s The obtaining method of (2) is the same as that in step (2-3).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211087900.5A CN115371790A (en) | 2022-09-07 | 2022-09-07 | Sensor calibration and weighing method of vehicle dynamic weighing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211087900.5A CN115371790A (en) | 2022-09-07 | 2022-09-07 | Sensor calibration and weighing method of vehicle dynamic weighing system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115371790A true CN115371790A (en) | 2022-11-22 |
Family
ID=84071282
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211087900.5A Pending CN115371790A (en) | 2022-09-07 | 2022-09-07 | Sensor calibration and weighing method of vehicle dynamic weighing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115371790A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115683296A (en) * | 2022-12-30 | 2023-02-03 | 广东泓胜科技股份有限公司 | Dynamic threshold processing method of road weighing sensor data and related equipment |
| CN116007725A (en) * | 2023-03-06 | 2023-04-25 | 中国兵器科学研究院宁波分院 | High-speed dynamic weighing method for vehicle |
| CN116124269A (en) * | 2023-04-18 | 2023-05-16 | 深圳亿维锐创科技股份有限公司 | Weighing calibration method, device, equipment and storage medium of dynamic truck scale |
| CN116481626A (en) * | 2023-06-28 | 2023-07-25 | 深圳市汉德网络科技有限公司 | Vehicle-mounted weighing self-adaptive high-precision calibration method and system |
| CN116884210A (en) * | 2023-06-02 | 2023-10-13 | 厦门市坤衡轩科技实业有限公司 | Dynamic vehicle detection method and system |
| CN117542208A (en) * | 2023-11-22 | 2024-02-09 | 广东泓胜科技股份有限公司 | Dynamic speed measuring system and method for automobile |
-
2022
- 2022-09-07 CN CN202211087900.5A patent/CN115371790A/en active Pending
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115683296A (en) * | 2022-12-30 | 2023-02-03 | 广东泓胜科技股份有限公司 | Dynamic threshold processing method of road weighing sensor data and related equipment |
| CN116007725A (en) * | 2023-03-06 | 2023-04-25 | 中国兵器科学研究院宁波分院 | High-speed dynamic weighing method for vehicle |
| CN116124269A (en) * | 2023-04-18 | 2023-05-16 | 深圳亿维锐创科技股份有限公司 | Weighing calibration method, device, equipment and storage medium of dynamic truck scale |
| CN116884210A (en) * | 2023-06-02 | 2023-10-13 | 厦门市坤衡轩科技实业有限公司 | Dynamic vehicle detection method and system |
| CN116481626A (en) * | 2023-06-28 | 2023-07-25 | 深圳市汉德网络科技有限公司 | Vehicle-mounted weighing self-adaptive high-precision calibration method and system |
| CN116481626B (en) * | 2023-06-28 | 2023-08-29 | 深圳市汉德网络科技有限公司 | Vehicle-mounted weighing self-adaptive high-precision calibration method and system |
| CN117542208A (en) * | 2023-11-22 | 2024-02-09 | 广东泓胜科技股份有限公司 | Dynamic speed measuring system and method for automobile |
| CN117542208B (en) * | 2023-11-22 | 2024-07-02 | 广东泓胜科技股份有限公司 | Dynamic speed measuring system and method for automobile |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115371790A (en) | Sensor calibration and weighing method of vehicle dynamic weighing system | |
| US6459050B1 (en) | Method and appartus for converting static in-ground vehicle scales into weigh-in-motion systems | |
| US20190234834A1 (en) | Method and system for measuring vertical wheel impact force in real-time based on tire pressure monitoring | |
| CN110361082B (en) | Monitoring system and monitoring method for measuring total weight of vehicle in real time | |
| CN111625752B (en) | Dynamic truck scale metering method with automatic parameter fitting function | |
| CN109649396B (en) | Safety detection method for commercial vehicle driver | |
| CN104792937A (en) | Bridge head bump detection evaluation method based on vehicle-mounted gravitational acceleration sensor | |
| CN106918459B (en) | Truck overload judgment method | |
| CN111348048B (en) | Truck overload alarm method, device, equipment and storage medium | |
| CN104792395A (en) | Entire-vehicle type dynamic vehicle scale axle load measurement and calibration method | |
| CN102288268B (en) | Dynamic vehicle weighing method | |
| CN107314899A (en) | Railway locomotive and motor train unit bogie bearing on-line monitoring method | |
| CN112528208A (en) | Weighing-free AI intelligent recognition truck overload estimation method, device and system | |
| CN204676401U (en) | A kind of subgrade resilient modulus Analytical system based on two rear axle inspection vehicle | |
| CN101576477A (en) | Pavement friction coefficient testing car | |
| McAuliffe et al. | Track-based aerodynamic testing of a two-truck platoon | |
| CN104568095A (en) | Vehicular weighing method | |
| CN113223294B (en) | Expressway automobile balance period checking method based on social vehicle big data | |
| Cole et al. | Spatial repeatability of measured dynamic tyre forces | |
| CN112304830A (en) | Method for monitoring road dust load by using social vehicles | |
| CN201434818Y (en) | Road surface friction coefficient testing carriage | |
| KR101058559B1 (en) | Braking Tester Calibration Device | |
| CN2861252Y (en) | Jounce accumulation type tester for road planeness | |
| CN110514276B (en) | Method for checking vehicle off-site overrun detection data | |
| Gururaja | Evaluation of Coastdown Analysis Techniques to Determine Aerodynamic Drag of Heavy-Duty Vehicles |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |