CN114485878A - Method and system for measuring dynamic weight of vehicle based on dynamic energy spectrum analysis - Google Patents
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- 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
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Abstract
The invention discloses a method for measuring the dynamic weight of a vehicle based on dynamic energy spectrum analysis, which mainly comprises the following steps: converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain graph to form an energy spectrum of the vibration signal; based on a preset vehicle dynamic energy spectrum identification model, dynamically identifying and separating a dynamic energy spectrum signal of each vehicle in real time in a frequency domain-time domain diagram; and calculating the intensity of the energy spectrum signal based on the separated dynamic energy spectrum signal of each vehicle to obtain the dynamic weight information of the vehicle. The invention firstly obtains all the composite vibration signals generated by the passing vehicles, then converts the vibration signals into energy spectrums, and then analyzes and identifies the energy spectrums, so that the energy spectrums generated by each passing vehicle can be analyzed, individual vehicle discrimination can be carried out, and the dynamic weight of the vehicle can be obtained according to the distribution condition of the energy spectrums in time.
Description
Technical Field
The invention relates to the technical field of vehicle dynamic weight measurement, in particular to a vehicle dynamic weight measurement technology based on dynamic energy spectrum analysis.
Background
Vehicle dynamic weight measurement (WIM) refers to a technique for measuring the dynamic weight of a running vehicle in real time. The dynamic weight pressure of the vehicle is equivalent to the pressure generated on the road surface in the moving process of the vehicle, the weight of the vehicle in the stationary state cannot be simply used for replacing the pressure generated on the road surface in the moving process of the vehicle, and the pressure is closely related to the road surface condition and the vehicle speed besides the whole vehicle weight in the stationary state of the vehicle. The WIM technology is widely applied to the fields of road operation and maintenance management, bridge maintenance and the like. The vehicle is a complex elastic system, so that the vehicle generates continuous mechanical vibration during the running process of the ground, the vibration can cause the contact surface between the vehicle and the ground to continuously change, and therefore, the dynamic weight can continuously fluctuate around a constant value, which is the reason why the dynamic weight cannot be accurately measured.
The conventional vehicle dynamic weight measurement technique suffers from several problems in application:
1) conventional vehicle dynamic weight measurement usually uses a pressure strain resistor or piezoelectric quartz as a measuring sensor, and usually only can measure point-shaped or linear stress.
2) At present, vehicles with two or more shafts are common in road running, an indirect measurement method is adopted for measuring the dynamic weight of the traditional vehicle, the dynamic weight of a single shaft of the vehicle is calculated by measuring the impulse force generated when the single shaft of the vehicle passes through, and the dynamic weight of the vehicle is obtained by calculation after combination. However, in some dynamic weighing cases, it can be seen that when a driver performs instantaneous refueling or braking of the vehicle through a conventional dynamic weighing system, the measured value can be affected by nearly 20%, resulting in a large deviation of the measurement result.
3) Most of the traditional dynamic weight measurement systems are in a mode of instantaneous value measurement. In the moving process of the vehicle, factors influencing the dynamic weight are many and can be changed along with the movement of the vehicle. The instantaneous value measurement is therefore not truly representative of the current vehicle dynamic weight.
4) Traditional dynamic weight equipment suppliers will modify the equipment installation measurement environment appropriately when the equipment installation is implemented. The measuring equipment is large in size and high in cost, the construction cost of the measuring system is high, a special construction and installation space is needed, the existing road needs to be damaged, and meanwhile, a special construction period is needed. The measurement accuracy of the system is influenced by the installation environment and the installation condition, and after the installation is finished, the measurement accuracy under the experimental environment (under the ideal condition) can not be achieved under the normal condition. In order to ensure the accuracy of the measurement, a plurality of precondition are adopted for limitation (for example, the running speed and the running direction of the vehicle are controlled, the flatness and the levelness of the road surface are measured, and the transient measurement value is corrected by measuring a plurality of transient changes in the passing process of the vehicle. The measurement method has higher requirements on measurement conditions, so that the construction and construction costs of the measurement system are high.
5) The traditional vehicle dynamic weight measurement technology can only measure one passing vehicle at a time, and does not support simultaneous measurement of multiple vehicles.
6) When the traditional vehicle dynamic weight is measured, clear limitation is provided for the running speed and the lane of the vehicle, and strict requirements are provided for the speed and the direction when the vehicle passes through, otherwise, a large measurement deviation is generated, and the measured weight value has certain deviation with the dynamic weight of the vehicle in actual running, so that the running condition of the vehicle cannot be completely reflected.
Disclosure of Invention
The present invention aims to solve the above problems and provide a method for measuring the dynamic weight of a vehicle (one or more vehicles) running on a specific road (or bridge) at the same time, which can be used for monitoring the vehicle overload or the road (or bridge) health safety.
In the road vehicle motion model, the vehicle can be regarded as being formed by connecting a plurality of rigid bodies with springs perpendicular to the ground. When the vehicle runs on a road surface, the vehicle generates continuous mechanical vibration (the mechanical vibration is formed by combining a plurality of mechanical vibration waves with different frequencies) and is transmitted to the ground through a contact surface of a wheel and the ground, the continuous mechanical vibration can be measured through a vibration sensor arranged on the ground, and the integral of the amplitude of the vibration in time is in linear relation with the dynamic weight of the vehicle.
By analyzing the vibration waveform, we can find that: the amplitude of the vibration waveform and the ground pressure of the vehicle have a correlation; the area of the amplitude envelope of the vibration waveform is correlated with the dynamic weight of the vehicle; the peak value of the vibration waveform has correlation with the axle of the vehicle; the characteristic components of the vibration waveform in each frequency in the frequency domain have correlation with the structure of a vehicle suspension system, and can be used for vehicle type identification; the effective length of the vibration waveform has a correlation with the vehicle speed.
Furthermore, the vibration waveform is analyzed in real time through a design algorithm, and the information of the vehicle type characteristics, the vehicle speed and the dynamic weight of the moving vehicle can be obtained simultaneously.
However, in the case of passing a plurality of vehicles on a road, the sensor measures the superposition (complex vibration) of vibrations generated by all vehicles passing on the road at the present time. Because of the fluctuation characteristic of the mechanical wave, the wave crests and the wave troughs at a certain moment are mutually offset, and therefore, the continuous integral of the complex vibration in time and the dynamic weight of the vehicle have no direct linear relation.
However, according to the law of conservation of energy, the sum of the vibration energy measured by the sensors over time is still the sum of all the generated vibration energy by the vehicle.
Therefore, the dynamic energy spectrum is introduced, the energy spectrum generated by each passing vehicle is analyzed by analyzing and identifying the energy spectrum of the collected vibration signals, and the dynamic weight of the vehicle is obtained through the distribution condition of the energy spectrum in time. The technical scheme adopted by the invention is as follows:
a method for vehicle dynamic weight measurement based on dynamic energy spectrum analysis, comprising,
s1, acquiring vibration signals generated by all passing vehicles;
s2, converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram to form an energy spectrum of the vibration signal;
s3, based on the preset vehicle dynamic energy spectrum recognition model, in a frequency domain-time domain diagram, dynamically recognizing and separating the dynamic energy spectrum signal of each vehicle in real time;
and S4, calculating the intensity of the energy spectrum signal based on the separated dynamic energy spectrum signal of each vehicle, and obtaining the dynamic weight information of the vehicle.
The specific contents of the dynamic energy spectrum identification models of the vehicles of different vehicle types are as follows: firstly, acquiring a characteristic energy spectrum under the condition that vehicles of different vehicle types pass through at a constant speed independently, establishing an incidence relation between the characteristic energy spectrum and a road surface, vehicle types, vehicle speeds and vehicle weights, and establishing a characteristic dynamic energy spectrum library of the vehicles of different vehicle types; and then, a machine learning algorithm is adopted to construct a vehicle dynamic energy spectrum identification model under the conditions of different road surfaces, different vehicle speeds and different vehicle weights.
The method comprises the steps of firstly obtaining all composite vibration signals generated by passing vehicles, then converting the vibration signals into energy spectrums, then analyzing and identifying the energy spectrums, analyzing the energy spectrums generated by each passing vehicle, and then obtaining the dynamic weight of the vehicle according to the distribution situation of the energy spectrums in time.
Due to the adoption of the technical scheme, the invention has the following beneficial effects:
1. the method for measuring the dynamic weight of the vehicle based on the dynamic energy spectrum analysis comprises the steps of firstly obtaining a plurality of vibration signals generated by all passing vehicles, then converting the vibration signals into energy spectrums, then analyzing and identifying the energy spectrums, analyzing the energy spectrums generated by all passing vehicles, distinguishing individual vehicles, and obtaining the dynamic weight of the vehicles according to the distribution condition of the energy spectrums in time.
2. The method can measure when multiple vehicles pass through to obtain the dynamic weight of each vehicle; the method can also be used for measuring when a single vehicle passes through so as to eliminate partial interference data and improve the measurement precision of the dynamic weight of the vehicle.
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FIG. 1 is a flow chart of a vehicle dynamic weight measurement method of the present invention.
FIG. 2 is a system block diagram of the vehicle dynamic weight measurement system of the present invention.
Detailed Description
The following further describes the embodiments of the present invention with reference to the drawings.
Example 1
As shown in fig. 1, the method for measuring the dynamic weight of a vehicle based on dynamic spectrum analysis of the present embodiment 1 includes the following steps,
s1, acquiring vibration signals generated by all passing vehicles;
s2, converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram to form an energy spectrum of the vibration signal;
s3, dynamically identifying and separating the dynamic energy spectrum signal of each vehicle in real time in a frequency domain-time domain diagram based on a preset vehicle dynamic energy spectrum identification model;
and S4, calculating the intensity of the energy spectrum signal based on the separated dynamic energy spectrum signal of each vehicle, and obtaining the dynamic weight information of the vehicle.
In step S1, the vibration signal is obtained by measuring with a vibration sensor or a vibration sensor array in a road surface or bridge surface measurement area, and then is uploaded to a processing center.
The specific content of step S2 is as follows: firstly, carrying out consistency processing on vibration signals measured by a vibration sensor or a vibration sensor array; and converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram through a short-time Fourier transform algorithm to form an energy spectrum of the vibration signal divided according to the frequency.
In step S3, the specific contents of the dynamic energy spectrum identification models of vehicles of different vehicle types are as follows: firstly, acquiring a characteristic energy spectrum under the condition that vehicles of different vehicle types pass through at a constant speed independently, establishing an incidence relation between the characteristic energy spectrum and a road surface, vehicle types, vehicle speeds and vehicle weights, and establishing a characteristic dynamic energy spectrum library of the vehicles of different vehicle types; and then, a machine learning algorithm is adopted to construct a vehicle dynamic energy spectrum identification model under the conditions of different road surfaces, different vehicle speeds and different vehicle weights.
The method comprises the steps of firstly obtaining all composite vibration signals generated by passing vehicles, then converting the vibration signals into energy spectrums, then analyzing and identifying the energy spectrums, analyzing the energy spectrums generated by each passing vehicle, and then obtaining the dynamic weight of the vehicle according to the distribution situation of the energy spectrums in time.
As an option, based on the foregoing example, in an example, the step S1 further acquires license plate information of a vehicle passing through the measurement area, which is output by a license plate recognition unit provided at an entrance of the measurement area. Therefore, the vehicle information can be input, the vehicle information including license plates, dynamic weight, vehicle speed and the like can be output, the license plates can be compared with a continuously updated vehicle information base, the vehicle types corresponding to the license plates can be obtained in real time, and then the vehicle type information is combined for recognition and analysis operation. The following will be specifically explained.
Firstly, an algorithm is prepared, and a vehicle dynamic energy spectrum identification model is prepared before dynamic energy spectrum identification and analysis, wherein the method specifically comprises the following steps:
1. establishing a characteristic dynamic energy spectrum library of different vehicle types, obtaining a characteristic energy spectrum of a specific vehicle under the condition that the specific vehicle passes through a measuring road surface at a constant speed independently at a certain speed, and establishing an incidence relation between the characteristic energy spectrum and the road surface, the vehicle speed, the vehicle dynamic weight and the vehicle type in a database by analyzing the characteristic energy spectrum which contains information related to the measuring road surface, the vehicle speed, the vehicle dynamic weight and the vehicle type;
2. and then, constructing a vehicle dynamic spectrum model identification algorithm under the conditions of different road surfaces, different vehicle speeds and different vehicle weights through a machine learning algorithm.
Secondly, the construction process is as follows:
1. selecting a hardened highway with a measuring area of two-way two lanes, wherein the length of a road section is 40 meters, and the width of the road is about 20 meters, and taking the area as the measuring area; wherein, the measuring area needs to be longer than 30 meters;
2. installing a camera with a license plate recognition function at the entrance end of the measurement area to recognize license plate information of passing vehicles;
3. a sensor array is constructed by adopting 4 three-axis high-precision vibration sensors, the sampling frequency is 200Hz, and the sensors are connected with a computing host through wireless WIFI;
4. the computer host is an industrial notebook computer, 8G memory, i5CPU and main frequency 2 Ghz;
5. the computer runs algorithm software to calculate the dynamic weight and speed of the running vehicle in real time and bind with the license plate, and the vehicle information base can transmit data with a traffic system and the like to update relevant information such as the license plate and the like.
Thirdly, environmental index calibration is carried out, after the field monitoring system is installed, the environmental index calibration is required to be carried out, and the method specifically comprises the following steps:
1. according to the sampling frequency, the sampling precision and the basic smoothness of the road surface of the field sensor, the required calculation step length and the calculation period of the short-time Fourier transform algorithm are selected through the parameter selection algorithm, so that the conversion result can have clear contrast and resolution;
2. through calibration, the vehicle is used for passing through the monitoring road section under various conditions, and reference monitoring data is obtained.
Fourthly, monitoring the dynamic weight of the vehicle, and monitoring after the calibration is completed, wherein the monitoring is as follows:
1. firstly, carrying out data consistency processing on the results acquired by a vibration sensor; because the influence of the vertical distance from the vehicle to the sensor needs to be considered, algorithm compensation is carried out in a vibration sensor array (multi-vibration sensor) mode, and the vibration signal acquisition precision is improved;
2. then, after the vibration signal is converted into an energy signal, mapping the energy signal into a frequency domain-time domain graph through a short-time Fourier transform algorithm, and constructing an energy spectrum of the vibration signal divided by frequency;
3. secondly, dynamically identifying and separating the dynamic energy spectrum signal of each vehicle in real time in a frequency domain-time domain graph based on a characteristic energy spectrum model algorithm, wherein the energy spectrum signal is distributed in a frequency domain and a time domain and is the energy spectrum signal of the vehicle when the vehicle passes through;
4. finally, through analysis and calculation of the individual vehicle energy spectrum signals, vehicle speed and vehicle weight dynamic weight information can be obtained. As described above, the total signal intensity of the individual vehicle spectrum and the dynamic weight of the vehicle are in a linear relationship, and therefore the dynamic weight of the vehicle can be calculated from the spectrum total signal intensity. And the width of the vehicle energy spectrum signal is related to time, and the vehicle speed when the vehicle passes can be calculated under the condition that the passing distance and the time are known. By selecting the vibration sensor array, the vehicle speed and the vehicle running direction can be calculated, and the length of a vehicle axle can be read out.
As described above, signal extraction and machine learning techniques are used throughout the calculation process. When the method is implemented on site, the mechanical vibration wave signals are captured in the whole measuring area in a vibration sensor array mode, inherent deviation of the sensors can be offset, and multi-vehicle real-time measuring resolution and measuring precision are improved. The measuring area usually selects a hardened road surface or a large bridge road surface, and the resonance effect of the axle resonance body is good under the condition, so that the measurement is convenient. The vibration sensor array can work together with auxiliary sensing equipment such as license plate recognition equipment and the like to recognize the license plate, so that the measurement resolution and the measurement precision are improved.
Moreover, the vibration sensor used by the measuring method can be directly purchased in the market under the condition of meeting the precision requirement; the mode of road outside roadbed installation is usually adopted during the installation, does not need to reform transform the road surface specially. Therefore, the measuring method has low implementation cost, is quick and convenient to install, does not damage the road surface, and can be used immediately after installation. The method supports simultaneous measurement of multiple vehicles, can perform simultaneous measurement of dynamic weight of multiple vehicles, and does not influence the running condition of road traffic. The consistency of the measured data is good, the weight of each shaft can be measured at the same time, the whole vehicle weight measurement can be completed at one time, and the measurement result is not interfered by the driving habits of the driver. After the system is installed and stably operates, the vehicle in operation can not be interfered, and the measurement precision can be continuously improved through continuous algorithm optimization.
Example 2
This embodiment 2 is the system of the foregoing embodiment 1, and please refer to the foregoing embodiment 1 for a complete description.
As shown in fig. 2, the system for measuring the dynamic weight of a vehicle based on dynamic spectrum analysis of the present embodiment 2 includes the following components,
the vibration acquisition module is used for acquiring vibration signals generated by all passing vehicles;
the energy spectrum conversion module is used for converting the vibration signal into an energy signal and mapping the energy signal into a frequency domain-time domain graph to form an energy spectrum of the vibration signal;
the identification separation module is used for dynamically identifying and separating the dynamic energy spectrum signal of each vehicle in real time in a frequency domain-time domain diagram based on a preset vehicle dynamic energy spectrum identification model;
and the weight obtaining module is used for calculating the intensity of the energy spectrum signal based on the separated dynamic energy spectrum signal of each vehicle to obtain the dynamic weight information of the vehicle.
In the vibration acquisition module, a vibration signal is obtained by measuring in a road surface or bridge surface measurement area by adopting a vibration sensor array.
The specific content of the energy spectrum conversion module is as follows: the device is used for carrying out consistency processing on vibration signals measured by a vibration sensor or a vibration sensor array; and converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram through a short-time Fourier transform algorithm to form an energy spectrum of the vibration signal divided according to the frequency.
In the identification and separation module, the specific contents of the dynamic energy spectrum identification models of vehicles of different vehicle types are as follows: firstly, acquiring a characteristic energy spectrum under the condition that vehicles of different vehicle types pass through at a constant speed independently, establishing an incidence relation between the characteristic energy spectrum and a road surface, vehicle types, vehicle speeds and vehicle weights, and establishing a characteristic dynamic energy spectrum library of the vehicles of different vehicle types; and then, a machine learning algorithm is adopted to construct a vehicle dynamic energy spectrum identification model under the conditions of different road surfaces, different vehicle speeds and different vehicle weights.
The method comprises the steps of firstly obtaining a plurality of vibration signals generated by all passing vehicles, then converting the vibration signals into energy spectrums, then analyzing and identifying the energy spectrums, analyzing the energy spectrums generated by all the passing vehicles, and then obtaining the dynamic weight of the vehicles according to the distribution situation of the energy spectrums in time.
As an option, based on the foregoing example, in one example, the obtaining vibration module is further configured to obtain license plate information of a vehicle passing through the measurement area, which is output by a license plate recognition unit disposed at an entrance of the measurement area. Therefore, the vehicle information can be input, the vehicle information including license plates, dynamic weight, vehicle speed and the like can be output, the license plates can be compared with a continuously updated vehicle information base, the vehicle types corresponding to the license plates can be obtained in real time, and then the vehicle type information is combined for recognition and analysis operation.
It should be noted that, the above embodiments may be combined with each other by one or more than two embodiments according to actual needs, and the embodiments are described by using a set of drawings for combining technical features, which are not described herein.
The foregoing description is directed to the details of preferred and exemplary embodiments of the invention, and not to the limitations defined thereby, which are intended to cover all modifications and equivalents of the invention as may come within the spirit and scope of the invention.
Claims (10)
1. A method for measuring the dynamic weight of a vehicle based on dynamic energy spectrum analysis is characterized in that: including the following in-eluding matters,
s1, acquiring vibration signals generated by all passing vehicles;
s2, converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram to form an energy spectrum of the vibration signal;
s3, dynamically identifying and separating the dynamic energy spectrum signal of each vehicle in real time in a frequency domain-time domain diagram based on a preset vehicle dynamic energy spectrum identification model;
and S4, calculating the intensity of the energy spectrum signal based on the separated dynamic energy spectrum signal of each vehicle, and obtaining the dynamic weight information of the vehicle.
2. The method for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 1, wherein: in step S1, the vibration signal is obtained by measuring with a vibration sensor or a vibration sensor array in a road surface or bridge surface measurement area.
3. The method for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 2, wherein: the specific content of step S2 is as follows: firstly, carrying out consistency processing on vibration signals measured by a vibration sensor or a vibration sensor array; and converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram through a short-time Fourier transform algorithm to form an energy spectrum of the vibration signal divided according to the frequency.
4. The method for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 1, wherein: in step S3, the specific contents of the dynamic energy spectrum identification models of vehicles of different vehicle types are as follows: firstly, acquiring a characteristic energy spectrum under the condition that vehicles of different vehicle types pass through at a constant speed independently, establishing an incidence relation between the characteristic energy spectrum and a road surface, vehicle types, vehicle speeds and vehicle weights, and establishing a characteristic dynamic energy spectrum library of the vehicles of different vehicle types; and then, a machine learning algorithm is adopted to construct a vehicle dynamic energy spectrum identification model under the conditions of different road surfaces, different vehicle speeds and different vehicle weights.
5. The method for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 1, wherein: in the step 1, license plate information of the vehicle passing through the measurement area, which is output by a license plate recognition unit arranged at an entrance of the measurement area, is also obtained.
6. The system for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 1, wherein: including the following in-eluding matters,
the vibration acquisition module is used for acquiring vibration signals generated by all passing vehicles;
the energy spectrum conversion module is used for converting the vibration signal into an energy signal and mapping the energy signal into a frequency domain-time domain graph to form an energy spectrum of the vibration signal;
the identification separation module is used for dynamically identifying and separating the dynamic energy spectrum signal of each vehicle in real time in a frequency domain-time domain diagram based on a preset vehicle dynamic energy spectrum identification model;
and the weight obtaining module is used for calculating the intensity of the energy spectrum signal based on the separated dynamic energy spectrum signal of each vehicle to obtain the dynamic weight information of the vehicle.
7. The system for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 6, wherein: in the vibration acquisition module, a vibration signal is obtained by adopting a vibration sensor or a vibration sensor array to measure in a highway pavement or bridge pavement measuring area.
8. The system for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 7, wherein: the specific content of the energy spectrum building module is as follows: the device is used for carrying out consistency processing on vibration signals measured by a vibration sensor or a vibration sensor array; and converting the vibration signal into an energy signal, and mapping the energy signal into a frequency domain-time domain diagram through a short-time Fourier transform algorithm to form an energy spectrum of the vibration signal divided according to the frequency.
9. The system for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 6, wherein: in the identification and separation module, the specific contents of the dynamic energy spectrum identification models of vehicles of different vehicle types are as follows: firstly, acquiring a characteristic energy spectrum under the condition that vehicles of different vehicle types pass through at a constant speed independently, establishing an incidence relation between the characteristic energy spectrum and a road surface, vehicle types, vehicle speeds and vehicle weights, and establishing a characteristic dynamic energy spectrum library of the vehicles of different vehicle types; and then, a machine learning algorithm is adopted to construct a vehicle dynamic energy spectrum identification model under the conditions of different road surfaces, different vehicle speeds and different vehicle weights.
10. The system for vehicle dynamic weight measurement based on dynamic energy spectrum analysis of claim 6, wherein: the obtaining vibration module is also used for obtaining the license plate information of the vehicle passing through the measuring area and output by a license plate recognition unit arranged at an entrance of the measuring area.
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