CN112665695B - Axle information recognition early warning method and system based on bridge transverse strain - Google Patents
Axle information recognition early warning method and system based on bridge transverse strain Download PDFInfo
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- CN112665695B CN112665695B CN202011484832.7A CN202011484832A CN112665695B CN 112665695 B CN112665695 B CN 112665695B CN 202011484832 A CN202011484832 A CN 202011484832A CN 112665695 B CN112665695 B CN 112665695B
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Abstract
The invention provides an axle information identification early warning method and system based on bridge transverse strain, wherein the method comprises the following steps: respectively arranging sensing units at the bridge entrance end and the bridge exit end of the bridge; obtaining axle parameters of a standard vehicle under a standard load working condition, collecting and processing strain response data of an axle entering end and an axle exiting end of the standard vehicle to obtain a strain difference value and a vehicle speed of the standard vehicle caused by axle weight; acquiring strain response data of a sensing unit at an axle entering end and an axle exiting end under the load working condition of a vehicle to be identified to obtain the speed, the wheelbase and the axle-weight ratio of the vehicle to be identified, and obtaining the total weight of the vehicle to be identified according to the axle weight of a front axle of a standard vehicle, the strain difference value of the standard vehicle and the speed; and carrying out vehicle overspeed and overload early warning according to the total weight of the vehicle to be identified and the vehicle speed, wherein the system comprises a regional distribution sensing monitoring system, a data system, an analysis system and an early warning system. The invention does not need to identify various physical parameters of the bridge, thereby conveniently and rapidly finishing the bridge overspeed and overload early warning on the bridge.
Description
Technical Field
The invention relates to the field of axle information identification, in particular to an axle information identification early warning method and system based on bridge transverse strain.
Background
Bridges are important components of highways and railway networks. In recent years, with the continuous development of socioeconomic performance, vehicle overload has become one of the main causes of bridge destruction and collapse. The repeated running of the overloaded vehicle seriously damages the safety of the upper structure of the bridge and accelerates the fatigue damage of the bridge. Especially, in the old bridge with a large proportion of the built bridge, the strength of the bridge is reduced and the resistance of the bridge is attenuated continuously due to the long construction time, and the bridge can be seriously damaged or even collapsed under the action of an overloaded vehicle. Meanwhile, as the maintenance and management cost of bridges continuously increases, bridge managers need to control the actual vehicle load acting on the bridges so as to ensure the safety and the residual service life of the serving bridges.
Axle information identification is important content of research of a bridge dynamic weighing system, and accurate identification of axle information can directly influence result accuracy of bridge dynamic weighing. Vehicle information, particularly vehicle speed, axle weight, and vehicle gross weight, is particularly important for monitoring vehicle overspeed and overload. Although a large number of bridge dynamic weighing technologies have been researched by a large number of scholars at the present stage, most of the technologies have low identification precision and high maintenance cost.
The theoretical research of the existing bridge dynamic weighing technology can be mainly divided into two categories: one is static inverse problem solving based on influence line theory, namely establishing a linear superposition relation between strain and vehicle axle load through the influence line so as to obtain the static axle load of the vehicle; the other type is the research of a dynamic response problem, namely, an axle is moved while a bridge face is directly identified from the dynamic response of the bridge, and then the static axle weight of the vehicle is calculated. In the first method, the number of axles, the wheelbase and the vehicle speed are all necessary data for calculating the axle weight; early bridge dynamic weighing technologies all required at least two sensors with a certain distance to be installed in the middle of a road surface to detect an axle and then calculate the vehicle speed, and are also used for vehicle type classification and axle weight calculation, but the main defects of the early bridge dynamic weighing technologies are that installation and maintenance interfere with traffic and the early bridge dynamic weighing technologies are not durable. Later, the method for identifying the axle by using the strain peak generated by the strain history under the action of the axle provided a bridge dynamic weighing technology without an axle detection device, but the method cannot effectively identify all vehicles. The durability of a bridge dynamic weighing technology system is greatly enhanced by introducing a new method of a non-pavement type bridge dynamic weighing technology, however, the accuracy of a bridge strain influence line and axle information seriously affects the test precision of the bridge dynamic weighing technology, and the bridge dynamic weighing technology system is more difficult to accurately identify under the working condition of multiple vehicle loads.
Disclosure of Invention
The invention aims to provide an axle information identification early warning method and system based on bridge transverse strain, which can conveniently and quickly finish dynamic weighing and overload early warning of a bridge on a medium-small span bridge without identifying various physical parameters of the bridge by driving a standard vehicle from the bridge to establish reference values of all units.
In order to achieve the purpose, the invention provides the following scheme: the invention provides an axle information identification and early warning method based on bridge transverse strain, which comprises the following steps:
acquiring a target bridge, and respectively arranging a bridge entrance end sensing unit and a bridge exit end sensing unit at a bridge entrance end and a bridge exit end of the bridge;
obtaining axle information of a standard vehicle under a standard load working condition, collecting and processing strain response data of sensing units at an axle entering end and an axle exiting end of the standard vehicle to obtain a strain difference value and vehicle speed of the standard vehicle caused by axle weight, and using the strain difference value and the vehicle speed as reference values to identify the axle information of the vehicle to be identified;
acquiring strain response data of a sensing unit at an axle entering end and an axle exiting section of a vehicle to be identified under a load working condition of the vehicle to be identified to obtain a strain difference value, a vehicle speed, a wheel base and a wheel-to-weight ratio of the vehicle to be identified, and obtaining a total weight of the vehicle to be identified according to a front axle weight of a standard vehicle, a strain difference value of the standard vehicle and a standard vehicle speed;
and carrying out vehicle overspeed and overload early warning according to the total weight of the vehicle to be identified and the vehicle speed.
Preferably, the calculation process of the strain difference is as follows: extracting a strain value at each peak, the occurrence time of the strain value and a strain value at a wave trough before the peak from strain time-course data collected from a sensing unit at the bridge entrance end; and performing difference processing on the peak strain and the trough strain acquired in the sensing unit at the bridge entrance end to obtain a strain difference.
Preferably, the speed of the vehicle to be identified is calculated according to the time of a strain peak corresponding to each axle in the strain time-course data of the axle entering end and the axle exiting end sensing units and the distance between the axle entering end and the axle exiting end sensing units.
Preferably, the vehicle wheel base is obtained by calculating the vehicle speed, the jth peak occurrence time of the bridge entrance end sensing unit and the jth-1 peak occurrence time of the bridge entrance end sensing unit.
Preferably, the calculation process of the vehicle axle-to-weight ratio is as follows: and obtaining the strain difference value corresponding to each axle according to the strain time-course data of the sensing unit at the bridge entrance end, and then respectively making the strain difference value corresponding to each axle and the strain difference value corresponding to the front axle of the vehicle as a ratio to obtain the axle-to-weight ratio of the vehicle.
The invention also provides an axle information identification and early warning system based on the transverse strain of the bridge, which comprises a regional distribution sensing monitoring system, a data system, an analysis system and an early warning system which are sequentially connected;
the area distribution sensing monitoring system is used for acquiring an implementation object and setting sensor layout parameters and positions;
the data system is used for acquiring strain data, preprocessing the acquired strain data, and transmitting and storing the strain data;
the analysis system is used for identifying the axle information of the vehicle according to the preprocessed data;
and the early warning system judges whether the vehicle is overspeed and overloaded according to the identified axle information, and sends out a warning prompt if the vehicle is overspeed and overloaded.
Preferably, the analysis system comprises a to-be-identified vehicle load working condition monitoring module, a vehicle load identification module and a standard vehicle load working condition monitoring module;
the standard vehicle load working condition monitoring module is used for acquiring strain response data of the sensing units at the bridge entrance end and the bridge exit end under the standard vehicle load working condition and calculating the strain variation and the vehicle speed corresponding to the axle weight of the standard vehicle;
the vehicle load working condition detection module to be identified is used for calculating strain difference, vehicle speed, wheel base and wheel-to-weight ratio corresponding to the wheel weight of the vehicle to be identified according to strain response data of the sensing units at the axle entering end and the axle exiting end under the vehicle load working condition to be identified;
the vehicle load identification module is used for identifying the total weight of the vehicle under the vehicle load working condition to be identified according to the strain difference and the vehicle speed corresponding to the axle weight of the front axle of the standard vehicle identified in the standard vehicle load working condition monitoring module and the strain difference, the vehicle speed and the axle weight ratio corresponding to the axle weight of the vehicle to be identified in the vehicle load working condition monitoring module to be identified.
Preferably, the data system comprises a data acquisition module, a data processing module, a data transmission module and a data storage module;
the data acquisition module is used for acquiring strain data of the vehicle passing through the bridge;
the data processing module is used for preprocessing the acquired strain data;
the data transmission module is used for transmitting the preprocessed data;
the data storage module is used for storing the preprocessed data.
Preferably, the early warning system comprises an overspeed vehicle early warning module and an overload vehicle early warning module;
the overspeed vehicle early warning module is used for carrying out overspeed early warning according to the speed of the vehicle;
the overload vehicle early warning module is used for carrying out overload early warning according to the total weight of the vehicle.
The invention discloses the following technical effects:
(1) according to the method, according to the characteristic that a cross section near a bridge support is sensitive to axle information, a transverse unit which is located at a bridge length cross section away from the bridge support 1/20 is selected as a bridge entrance end unit and a bridge exit end unit, and the identification precision of the axle information can be obviously improved through transverse strain data of the bridge entrance end and the bridge exit end, particularly through a difference value between a strain peak and a strain trough before the peak in the data of a sensing unit of the bridge entrance end;
(2) the method is not only suitable for the load working condition of a single vehicle, but also suitable for the load working conditions of a plurality of vehicles, and the practicability of the method is ensured; the invention is not only suitable for the vehicles to be identified with the same speed as the standard vehicle, but also suitable for the vehicles to be identified with the different speeds from the standard vehicle, and the invention is suitable for the different speeds;
(3) the invention needs fewer sensors, only needs to transversely arrange a small number of sensors at the bridge inlet end and the bridge outlet end, and effectively reduces the measurement cost of manpower and material resources and vehicle load working conditions;
(4) the method does not interfere with the normal strain monitoring task of the structure, only drives a standard vehicle from the bridge to establish the strain difference reference values of the bridge inlet end unit and the bridge outlet end unit, does not need to identify various physical parameters of the bridge, can conveniently and quickly complete dynamic weighing of the bridge on the medium and small bridge spans and overspeed overload early warning, is expected to be popularized and applied to engineering practice, and brings huge economic benefit and social benefit.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of an axle information identification method based on bridge transverse strain according to the present invention;
FIG. 2 is a schematic structural diagram of an axle information recognition system based on transverse bridge strain according to the present invention;
FIG. 3 is a schematic view of a standard vehicle according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a strain time course under a single standard vehicle load condition implemented by the present invention, wherein: FIG. 4(a) is a schematic diagram of a transverse strain time course of a standard vehicle load condition at an entrance bridge end, and FIG. 4(b) is a schematic diagram of a transverse strain time course of a standard vehicle load condition at an exit bridge end;
FIG. 5 is a schematic view of a vehicle operating in a plurality of operating modes according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a transverse strain time course of a multi-vehicle to-be-identified vehicle under a load condition in the embodiment of the present invention, wherein: fig. 6(a) is a schematic diagram of transverse strain time course under the working condition of load of a plurality of vehicles to be identified at the bridge entrance end, and fig. 6(b) is a schematic diagram of transverse strain time course under the working condition of load of a plurality of vehicles to be identified at the bridge exit end.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in FIG. 1, the invention provides an axle information identification early warning method based on bridge transverse strain, which comprises the following steps:
and S1, acquiring the target bridge, and respectively arranging long-gauge-length fiber grating strain sensors at the bridge entrance end and the bridge exit end of the bridge to obtain a bridge entrance end sensing unit and a bridge exit end sensing unit.
According to the position and the characteristics of a large-span bridge and an old bridge, a certain span of an auxiliary bridge or a small-span bridge on a necessary route is selected as a target bridge, and according to the structure type and the geometric parameters of the target bridge, long gauge length fiber grating strain sensors are transversely installed on the cross sections of the positions, which are 1/20 bridge lengths away from the bridge entrance end and the bridge exit end of the bridge.
And S2, obtaining axle information of the standard vehicle under the standard load working condition, and acquiring and processing strain response data of the sensing units at the bridge entrance end and the bridge exit end of the standard vehicle to obtain a standard vehicle strain difference value and a vehicle speed.
In the embodiment, a two-axis vehicle is used as a standard vehicle for analysis, and a strain value epsilon 'at a first peak is extracted from strain time-course data collected from a sensing unit at an approach bridge end'0And the time of occurrence and the strain value epsilon' at the trough before the peak0(ii) a To the bridge endAnd performing difference processing on the strain time-course data collected in the sensing unit to finally obtain the strain difference of the standard vehicle, namely:
wherein: epsilon'0The strain value at the first peak of the standard vehicle working condition is obtained; ε0The strain value of the wave trough before the first peak is zero; epsilon0The strain differential of the sensing unit at the approach end for the first axle of a standard vehicle.
The method comprises the following steps of carrying out mean value processing on the time difference of each axle of a standard vehicle entering and exiting a bridge, specifically:
wherein: Δ t0The average time of the standard vehicle passing through the bridge is shown; t is tjThe time of occurrence of the jth peak value in the data of the bridge entrance end sensing unit of the standard vehicle is obtained; t'jThe time of occurrence of the jth peak value in the data of the bridge-outlet end sensing unit of the standard vehicle is obtained; and nj is the number of axles of the standard vehicle.
Average time Deltat for standard vehicle passing through bridge according to equation (2)0Calculating vehicle speed v0The method specifically comprises the following steps:
wherein: a is the distance between the position of the bridge-entering end sensing unit and the support; l is the bridge length.
S3, strain response data of the bridge entrance end and the bridge exit section sensing units under the load working condition of the vehicle to be identified are collected, a strain difference value, a vehicle speed, a wheel base and a wheel-to-weight ratio of the vehicle to be identified are obtained, and the total weight of the vehicle to be identified is obtained according to the front axle weight of the standard vehicle, the strain difference value of the standard vehicle and the speed of the standard vehicle.
The embodiment responds from the strain of the vehicle to be identifiedIdentifying the strain spike caused by single axle weight and the time of occurrence in the data, and calculating the strain difference epsilon of the sensing unit at the bridge access end caused by single axle weightijTherefore, the acquired strain data is utilized to further solve the vehicle speed, the vehicle distance and the axle-to-weight ratio, and the method specifically comprises the following steps:
extracting strain value epsilon 'at each peak from strain time-course data collected from a sensing unit at the bridge-entering end'ijAnd the time t of occurrence thereofijAnd strain value ε ″' at the trough before the peakij(ii) a When a plurality of vehicles run on the bridge at the same time, the wave trough strain value at the front axle of each vehicle is the average value of the last oscillation at the wave trough; extracting time t 'occurring at each peak from strain time course data collected from a sensing unit at the bridge-outlet end'ij；
And (3) carrying out difference processing on the peak strain and the trough strain collected in the sensing unit at the bridge entrance end, and calculating to obtain the strain difference generated by the jth axle of the ith vehicle, namely:
wherein: epsilon'ijThe peak strain of a sensing unit at the bridge entrance end of the jth axle of the ith vehicle in the load working condition of the vehicle to be identified; εijThe wave trough strain of a sensing unit at the bridge entrance end of the jth axle of the ith vehicle in the load working condition of the vehicle to be identified; lac is the distance between the position of the sensing unit at the bridge entrance end and the support at the bridge exit end; l is the bridge length.
The average value processing is carried out on the time difference of each axle of the ith vehicle entering and exiting the bridge, and the average value processing method specifically comprises the following steps:
wherein: Δ tiThe average time of the ith vehicle passing through the bridge; t is tijThe time of occurrence of the jth peak value in the data of the sensing unit at the bridge entrance end of the ith vehicle is obtained; t'ijIn the data of the sensing unit at the bridge-outlet end of the ith vehicleThe time at which the jth peak occurs; nj is the peak number of the ith vehicle.
Average time Deltat for the ith vehicle to pass through the bridge according to equation (5)iCalculating vehicle speed viThe method specifically comprises the following steps:
wherein: and a is the distance from the position of the bridge-entering end sensing unit to the support.
According to the vehicle speed v in equation (6)iCalculating the vehicle wheelbase Ski：
Sk＝vi×(tij-tij-1)(k＝1,2,3…；i＝1,2,3…；j＝2,3,4…) (7)
Calculating the axle weight ratio dkP between the jth axle of the ith vehicle and the 1 st axle of the ith vehicle according to the formula (4)ij：
Wherein: epsilonijGenerating strain difference at the bridge entrance end for the jth axle of the ith vehicle; epsiloni1The strain difference generated at the bridge entrance end for the 1 st axle of the ith vehicle.
And S4, performing vehicle overspeed and overload early warning according to the vehicle load condition parameters and the strain difference of the standard vehicle.
The embodiment carries out vehicle overspeed and overload early warning by calculating the total weight of the identified vehicle and the speed of the vehicle.
The calculation process of the total weight of the vehicle to be identified comprises the following steps:
the front axle weight of the standard vehicle can be known to be P from the standard working condition0The combination of the formulas (1), (4) and (8) can identify the gross vehicle weight CLiThe identification is that:
wherein: cLiThe identified gross weight of the ith vehicle; dkPijThe axle weight ratio between the jth axle of the ith vehicle and the 1 st axle of the ith vehicle is obtained; epsiloni1The strain difference of a sensing unit at the bridge entrance end of a first axle of an ith vehicle in the load working condition of the vehicle to be identified; epsilon0Strain difference of the sensing unit at the axle approach end for a first axle of a standard vehicle; p0The axle weight of a first axle of a standard vehicle; λ is a speed correction coefficient, and specifically is:
the speed v of the standard vehicle passing through the bridge can be known from the standard working condition0Then, combining equation (6) to obtain the correction coefficient:
wherein: v. of0The speed of a standard vehicle passing through the bridge; v. ofiIs the speed of the ith vehicle through the bridge.
The embodiment judges whether the identified vehicle is overspeed and overloaded according to the total weight of the standard vehicle speed and load and the vehicle overspeed and overload standard, if so, the overload vehicle in the system is marked, the warning is given, and the vehicle information is output.
As shown in fig. 2, the embodiment further provides an axle information recognition and early warning system based on the transverse strain of the bridge, which includes a regional distribution sensing and monitoring system, a data system, an analysis system and an early warning system.
The regional distribution sensing monitoring system comprises long-gauge fiber grating strain sensors transversely arranged at the positions, which are both 1/20 bridge long sections, of supports arranged at the bridge entrance end and the bridge exit end of the bridge, and the long-gauge fiber grating strain sensors are used for acquiring implementation objects and setting the layout parameters and positions of the sensors.
And the data system is used for acquiring the strain data, preprocessing the acquired strain data, and transmitting and storing the strain data. The data acquisition system comprises a data acquisition module, a data processing module, a data transmission module and a data storage module.
The data acquisition module is used for acquiring strain data of the vehicle passing through the bridge;
the data processing module is used for preprocessing the acquired strain data;
the data transmission module is used for transmitting the preprocessed data;
and the data storage module is used for storing the preprocessed data.
The analysis system is used for identifying the axle information of the vehicle according to the preprocessed data. The data analysis system comprises a vehicle load working condition monitoring module to be identified, a standard vehicle load working condition monitoring module and a vehicle load identification module.
The standard vehicle load working condition monitoring module is used for acquiring strain response data of the bridge entrance end sensing unit and the bridge exit end sensing unit under the standard vehicle load working condition and calculating the corresponding strain difference of the standard vehicle axle weight and the vehicle speed;
the to-be-identified vehicle load working condition detection module is used for calculating strain difference, vehicle speed, wheel base and wheel-to-axle ratio corresponding to the axle weight of the to-be-identified vehicle according to strain response data of the sensing units at the axle inlet end and the axle outlet end under the to-be-identified vehicle load working condition;
the vehicle load identification module is used for identifying the total weight of the vehicle under the vehicle load working condition to be identified according to the strain difference and the vehicle speed corresponding to the axle weight of the front axle of the standard vehicle identified in the standard vehicle load working condition monitoring module and the strain difference, the vehicle speed and the axle weight ratio corresponding to the axle weight of the vehicle to be identified in the vehicle load working condition monitoring module.
The early warning system judges whether the vehicle is overspeed and overloaded according to the identified axle information, and if the vehicle is overspeed and overloaded, an alarm prompt is sent to the supervision system. The early warning system comprises an overspeed vehicle early warning module and an overload vehicle early warning module;
the overspeed vehicle early warning module is used for carrying out overspeed early warning according to the speed of the vehicle;
the overload vehicle early warning module is used for carrying out overload early warning according to the gross weight of the vehicle.
In the embodiment, the transverse strain of the simply supported box girder bridge under different load working conditions is calculated through finite element software, and the effectiveness and the applicability of the method provided by the invention are verified.
The section parameters of the simply supported box girder bridge selected in the embodiment are as follows:
taking a simply supported girder bridge as an example, the bridge is 50m long, the width of the top plate is 12m, the thickness of the top plate is 0.3m, the width of the bottom plate is 7m, the thickness of the bottom plate is 0.3m, and the height of the box girder is 3 m; the thickness of the web is 0.6 m; the material is C50 concrete, and the elastic modulus is 3.45 x 104 MPa. The size of the unit grid of the bridge is 0.5m, the gauge length of the long gauge FBG sensor is 0.5m with the size of the grid, and the long gauge sensors are transversely arranged at the centers of box girder bottom plates 2.5m away from the support at the bridge inlet end and the bridge outlet end, so that 2 sensors are totally arranged. And verifying the identification result of the invention under the working conditions of a plurality of moving vehicle loads by adopting finite element analysis software.
According to the method, the moving load on the bridge is dynamically weighed by the following steps:
(1) determining standard vehicle load conditions
As shown in fig. 3, the standard vehicle selected in this embodiment is a 2-axle vehicle, the front axle weight is 30Kn, the rear axle weight is 50Kn, the wheel base is 3.5m, the vehicle runs through the box girder bridge at a speed of 25m/s, and the strain time course data under the working condition is acquired by the long gauge length strain sensor. Strain value epsilon 'at first peak of standard vehicle working condition is collected from sensor data'0And the strain value ε "at the trough just before the first peak0The value is zero, and the standard vehicle transverse strain time course data of the embodiment is specifically shown in fig. 4. Calculating the strain epsilon generated by a sensing unit at the bridge entrance end of a standard front axle according to the formula (1)0The specific results are shown in Table 4.
(2) Multi-vehicle mobile load testing of structures
In this embodiment, 3 vehicles are selected as an experimental test object, and the load conditions of the 3 vehicles are specifically as follows: the vehicle 1, the front axle weight is 50Kn, the rear axle weight is 90Kn, the total weight is 140Kn, and the vehicle firstly goes on the bridge at the speed of 20 m/s; the vehicle 2 runs on the axle at the speed of 20m/s, the front axle weight is 70Kn, the rear axle weight is 130Kn, the total weight is 200Kn, and the distance between the vehicle 2 and the vehicle 1 is 1 s; the vehicle 3, the front axle weight of 50Kn, the middle axle weight of 130Kn, the rear axle weight of 240Kn and the total weight of 400Kn, is separated from the vehicle 2 by 1s and runs on the bridge at the speed of 20 m/s. Specific vehicle information is shown in fig. 5.
Long gauge length strain sensor for acquiring strain of vehicle under working conditionTime course data, extracting strain value epsilon 'at each peak'ijAnd the time t of occurrence thereofijAnd strain value ε ″' at the trough before the peakij。
(3) Preliminary processing of multi-vehicle load condition data
Extracting strain value epsilon 'at each peak from strain time course data collected from a sensing unit at the bridge-entering end'ijAnd the time t of occurrence thereofijAnd strain value ε ″' at the trough before the peakijExtracting the time t 'occurring at each peak from the strain time course data collected from the sensing unit at the bridge-outlet end'ijAnd collecting and determining the number of axles and the number of vehicles. The transverse strain time course of the multiple vehicles of the present embodiment is specifically shown in fig. 6.
(4) Initial information determination of vehicle under multiple vehicle load conditions
Calculating the strain value of the front axle of the vehicle to be measured by the formula (4), wherein the specific result is shown in a table 4; according to the formula (6), the formula (7) and the formula (8), the speed, the wheelbase and the axle-weight ratio of each vehicle are identified, the speed and the wheelbase of each vehicle are basically consistent with the actual speed and the wheelbase according to the identification result, the maximum error is 1.5%, the maximum error of the identified axle-weight ratio is 9.81%, and the specific conditions are shown in a table 1, a table 2 and a table 3.
TABLE 1
TABLE 2
TABLE 3
According to the formula (9), the total weight of each vehicle under the working condition to be measured is calculated, and the total weight error of the vehicle is analyzed, so that the maximum total weight error of the vehicle calculated by using the method is 4.78%, the error is smaller when the total weight of the vehicle is larger, and the specific total weight identification result and the error analysis result are shown in table 4.
TABLE 4
(5) Early warning overload of multiple vehicle load working condition
According to the overspeed standard of vehicles (road traffic safety law), when a vehicle travels on a highway, its speed is limited to 80km/h, i.e., 22.22m/s, when the vehicle passes through a bridge.
According to the overload standard of the vehicle: and the number of the 2-axis vehicles is 20t, the number of the 3-axis vehicles is 30t, and the number of the 4-axis vehicles is 40t, and whether the identified vehicle is an overloaded vehicle or not is judged. And calculating the average value of the recognized vehicle load under the working condition, comparing the average value with the overload limit, considering the error of 5 percent of the calculation result, and judging whether the vehicle is an overloaded vehicle. Through calculation, the vehicles 2 and 3 are identified as overloaded vehicles, the vehicles are marked in the system, and corresponding axle parameters are output to give an early warning.
The overspeed information and the overload information of the vehicle under the multiple vehicle load conditions are shown in tables 5 and 6, respectively.
TABLE 5
TABLE 6
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.
Claims (8)
1. An axle information identification early warning method based on bridge transverse strain is characterized by comprising the following steps:
acquiring a target bridge, and respectively arranging a bridge entrance end sensing unit and a bridge exit end sensing unit at a bridge entrance end and a bridge exit end of the bridge; selecting transverse units at the bridge long section position away from a bridge support 1/20 as a bridge entrance end sensing unit and a bridge exit end sensing unit;
obtaining axle information of a standard vehicle under a standard load working condition, collecting and processing strain response data of sensing units at an axle entering end and an axle exiting end of the standard vehicle to obtain a strain difference value and vehicle speed of the standard vehicle caused by axle weight, and using the strain difference value and the vehicle speed as reference values to identify the axle information of the vehicle to be identified;
acquiring strain response data of a sensing unit at an axle inlet end and an axle outlet end of a vehicle to be identified under a load working condition of the vehicle to be identified to obtain the speed, the wheelbase, the axle-weight ratio and the strain difference value of each axle of the vehicle to be identified, and obtaining the total weight of the vehicle to be identified according to the axle weight of a front axle of a standard vehicle, the strain difference value of the standard vehicle and the speed of the standard vehicle;
carrying out vehicle overspeed and overload early warning according to the total weight of the vehicle to be identified and the vehicle speed;
the calculation process of the strain difference value is as follows: extracting a strain value at each peak, the occurrence time of the strain value and a strain value at a wave trough before the peak from strain time-course data collected from a sensing unit at the bridge entrance end; performing difference processing on the peak strain and the trough strain collected in the sensing unit at the bridge entrance end to obtain a strain difference;
the strain difference of the standard vehicle is
Wherein: epsilon'0The strain value at the first peak of the standard vehicle working condition is obtained; ε0The strain value of the wave trough before the first peak is zero; epsilon0A strain difference of the sensing unit at the axle approach end for a first axle of a standard vehicle;
the strain difference value generated by the jth axle of the ith vehicle to be identified is
Wherein: epsilon'ijThe peak strain of a sensing unit at the bridge entrance end of the jth axle of the ith vehicle in the load working condition of the vehicle to be identified; εijThe wave trough strain of a sensing unit at the bridge entrance end of the jth axle of the ith vehicle in the load working condition of the vehicle to be identified; lac is the distance between the position of the sensing unit at the bridge entrance end and the support at the bridge exit end; l is the bridge length.
2. The axle information identification and early warning method based on the transverse bridge strain is characterized in that the speed of the vehicle to be identified is calculated according to the time of a strain peak corresponding to each axle in the strain time-course data of the sensing units at the bridge entrance end and the bridge exit end and the distance between the sensing units at the bridge entrance end and the bridge exit end.
3. The axle information identification and early warning method based on the transverse strain of the bridge as claimed in claim 1, wherein the vehicle wheelbase is calculated by the vehicle speed, the jth peak occurrence time of the bridge entrance end sensing unit and the jth-1 peak occurrence time of the bridge entrance end sensing unit.
4. The bridge transverse strain-based axle information recognition early warning method according to claim 1, wherein the calculation process of the vehicle axle-to-weight ratio is as follows: and obtaining the strain difference value corresponding to each axle according to the strain time-course data of the sensing unit at the bridge entrance end, and then respectively making the strain difference value corresponding to each axle and the strain difference value corresponding to the front axle of the vehicle as a ratio to obtain the axle-to-weight ratio of the vehicle.
5. An axle information identification early warning system based on bridge transverse strain, which is used in the method of any one of claims 1 to 4 and is characterized by comprising a regional distribution sensing monitoring system, a data system, an analysis system and an early warning system which are connected in sequence;
the area distribution sensing monitoring system is used for acquiring an implementation object and setting sensor layout parameters and positions;
the data system is used for acquiring strain data, preprocessing the acquired strain data, and transmitting and storing the strain data;
the analysis system is used for identifying the axle information of the vehicle according to the preprocessed data;
and the early warning system judges whether the vehicle is overspeed and overloaded according to the identified axle information, and sends out a warning prompt if the vehicle is overspeed and overloaded.
6. The bridge transverse strain-based axle information recognition and early warning system according to claim 5, wherein the analysis system comprises a to-be-recognized vehicle load condition monitoring module, a vehicle load recognition module and a standard vehicle load condition monitoring module;
the standard vehicle load working condition monitoring module is used for acquiring strain response data of the sensing units at the bridge entrance end and the bridge exit end under the standard vehicle load working condition, and calculating a strain difference value corresponding to the axle weight of a standard vehicle and the vehicle speed;
the vehicle load working condition monitoring module to be identified is used for calculating a strain difference value, a vehicle speed, a wheel base and a wheel-to-axle weight ratio corresponding to the wheel weight of the vehicle to be identified according to strain response data of the sensing units at the axle entering end and the axle exiting end under the vehicle load working condition to be identified;
the vehicle load identification module is used for identifying the total weight of the vehicle under the vehicle load working condition to be identified according to the strain difference value and the vehicle speed corresponding to the axle weight of the front axle of the standard vehicle identified in the standard vehicle load working condition monitoring module, and the strain difference value, the vehicle speed and the axle-weight ratio corresponding to the axle weight of the vehicle to be identified in the vehicle load working condition monitoring module to be identified.
7. The bridge transverse strain-based axle information recognition and early warning system according to claim 5, wherein the data system comprises a data acquisition module, a data processing module, a data transmission module and a data storage module;
the data acquisition module is used for acquiring strain data of the vehicle passing through the bridge;
the data processing module is used for preprocessing the acquired strain data;
the data transmission module is used for transmitting the preprocessed data;
the data storage module is used for storing the preprocessed data.
8. The bridge transverse strain-based axle information recognition and early-warning system according to claim 5, wherein the early-warning system comprises an overspeed vehicle early-warning module and an overload vehicle early-warning module;
the overspeed vehicle early warning module is used for carrying out overspeed early warning according to the speed of the vehicle;
the overload vehicle early warning module is used for carrying out overload early warning according to the total weight of the vehicle.
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| CN114323512B (en) * | 2021-12-17 | 2023-06-16 | 中铁桥隧技术有限公司 | Heavy-load vehicle identification method and system |
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