CN104848924A - Bridge carrying capability monitoring method, device and system - Google Patents
Bridge carrying capability monitoring method, device and system Download PDFInfo
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- CN104848924A CN104848924A CN201410800423.1A CN201410800423A CN104848924A CN 104848924 A CN104848924 A CN 104848924A CN 201410800423 A CN201410800423 A CN 201410800423A CN 104848924 A CN104848924 A CN 104848924A
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Abstract
The invention discloses a bridge carrying capability monitoring method, device and system and relates to the technical field of bridge monitoring. The method includes a step S1 of obtaining vehicle weight and feature information of vehicles at an upper bridge end of a to-be-tested bridge and feature information of vehicles at a lower bridge end in real time; a step 2 of matching the vehicles at the lower bridge end with the vehicles at the upper bridge end according to the feature information; and a step 3 of obtaining the total vehicle weight of the vehicles, which fail in matching, at the upper bridge end and taking the total vehicle weight as the bridge carrying capability. According to the invention, by obtaining vehicle weight and feature information of vehicles at the upper bridge end and feature information of vehicles at the lower bridge end, matching the vehicles at the lower bridge end with the vehicles at the upper bridge end and taking the total vehicle weight of the vehicles, which fail in matching, at the upper bridge end as the bridge carrying capability of the to-be-tested bridge, monitoring of the bridge carrying capability is realized conveniently. The implementation only requires a plurality of comparatively simple devices and is easy. The cost is low. Besides, by adopting near-range feature collection, matching precision is high, so that bridge carrying capability monitoring precision is guaranteed.
Description
Technical Field
The invention relates to the technical field of bridge monitoring, in particular to a bridge monitoring deviceBridge load monitoring method, device and system。
Background
With the rapid development of transportation industry, the increasing of road traffic flow and the increasing of load capacity, the bearing capacity and reliability of the existing bridge structure face a severe test, and for vehicle load, the effect generated in the bridge structure is mainly influenced by a plurality of parameters such as vehicle weight, axle distance, vehicle distance and the like; due to the inherent correlation between load and resistance, the load-bearing capacity of the bridge structure needs to meet the requirements of the vehicle in terms of configuration, load capacity, load distribution on each axle, vehicle position on the bridge, bridge span and the like. The vehicles are crowded and blocked, the distance between the front and the back of the vehicles on a plurality of bridges is only 3.0-5.0 m, the damage of the bridges is aggravated, a vicious circle is formed, and the safety of the vehicles and pedestrians is threatened. More seriously, the bridge collapse accident caused by the accident is very striking.
For a small-span bridge, because the distance between vehicles cannot be infinitely shortened, the maximum load effect of the bridge is generally controlled by the weight of a single vehicle or the axle load of the single vehicle, the safety monitoring of the bridge is realized by controlling the upper limit of the weight of the single vehicle or the upper limit of the axle load of the single vehicle at present, but the bridge safety monitoring of the bridge with medium span and large span cannot be realized.
For bridges with medium and large spans, the maximum load effect of a bridge structure is usually generated under the condition of vehicle congestion, and the main reason is that the distance between vehicles is small and the number of vehicles running on the bridge is large under the condition of vehicle congestion; the traditional method is to use sensors and communication technology to timely or regularly collect the working parameters of the bridge, and the computer identifies, processes and analyzes the collected parameters according to the design parameters of the bridge and the health detection indexes of the bridge, so as to provide the load distribution of the bridge and provide basis and guidance for the decision of bridge maintenance, repair and management. Because the large-span bridge has the characteristics of complex structural form, large span, harsh environment and the like, the dynamic load distribution detection of bridge vehicles has many defects, such as more required sensors, higher cost, easy influence of interference signals on the sensors, easy disorder of wiring, larger workload of arrangement and maintenance equipment, poorer instantaneity and the like.
In the prior art, a detection method for a large-span bridge by using a splicing technology of a panoramic camera is also available, and the detection method realizes tracking and matching of a vehicle and weight by detecting and tracking the vehicle on the whole bridge floor. However, the detection method only depends on videos as identification factors, the matching factors are single, the detection method too depends on a video identification system, tracking failure is easy to occur at night or in poor light environment, and meanwhile, a large number of panoramic cameras need to be installed on the bridge, so that the data processing difficulty is high, and the manufacturing cost is high.
Disclosure of Invention
In view of the above, the present invention provides a solution to the above problems or at least partially to the above problemsBridge load monitoring method, device and system。
According to an aspect of the invention, there is provided a bridge load monitoring method, the method comprising:
s1: acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the characteristic information of a lower bridge end vehicle of a bridge to be monitored in real time;
s2: matching the lower axle end vehicle with the upper axle end vehicle according to the characteristic information;
s3: and acquiring the total vehicle weight of the upper bridge end vehicles which are not successfully matched, and taking the total vehicle weight as the bridge load of the bridge to be monitored.
Wherein, step S2 specifically includes:
s201: calculating a characteristic deviation between the characteristic information of the lower axle end vehicle and the characteristic information of the current upper axle end vehicle, wherein the characteristic information comprises: at least one of axle weight, axle group weight, axle number, license plate, vehicle length, vehicle height, vehicle width and three-dimensional contour;
s202: calculating a similarity evaluation index according to the characteristic deviation;
s203: comparing the similarity evaluation index with a similarity evaluation threshold, if the similarity evaluation index is smaller than the similarity evaluation threshold, determining that the matching is successful, and executing a step S3, otherwise, determining that the matching is unsuccessful, and executing a step S204;
s204: and taking the upper bridge end vehicle which is not selected as a new current upper bridge end vehicle, and returning to the step S201 until all the upper bridge end vehicles are selected.
After step S3, the method further includes:
s4: judging whether the bridge load is in a dangerous load range, and if the bridge load is in the dangerous load range, outputting early warning information;
between step S3 and step S4, the method further includes:
counting the average time of successfully matched vehicles within preset time, and removing the weight of the upper bridge end vehicle from the load of the bridge if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value;
or,
in step S4, before outputting the warning information, the method further includes:
counting the average time of successfully matched vehicles within preset time, and clearing the weight of the upper bridge end vehicle from the load of the bridge if the difference value obtained between the existing time of the upper bridge end vehicle and the average time exceeds a preset value;
and judging whether the bridge load is in a dangerous load range, and if the bridge load is still in the dangerous load range, executing to output early warning information.
Wherein, step S1 specifically includes:
acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the vehicle weight and the characteristic information of a lower bridge end vehicle of a bridge to be monitored in real time;
correspondingly, step S2 specifically includes:
and taking the vehicle weight and the characteristic information as new characteristic information, and matching the lower axle end vehicle with the upper axle end vehicle according to the new characteristic information.
According to another aspect of the present invention, there is provided a bridge load monitoring apparatus, the apparatus comprising:
the information acquisition module is used for acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the characteristic information of a lower bridge end vehicle of the bridge to be monitored in real time;
the information matching module is used for matching the lower bridge end vehicle with the upper bridge end vehicle according to the characteristic information;
and the load calculation module is used for acquiring the total vehicle weight of the upper bridge end vehicles which are not successfully matched, and taking the total vehicle weight as the bridge load of the bridge to be monitored.
Wherein, the information matching module specifically comprises:
a deviation calculation submodule for calculating a characteristic deviation between the characteristic information of the lower axle end vehicle and the characteristic information of the current upper axle end vehicle, the characteristic information including: at least one of axle weight, axle group weight, axle number, license plate, vehicle length, vehicle height, vehicle width and three-dimensional contour;
the index calculation submodule is used for calculating a similarity evaluation index according to the characteristic deviation;
a threshold comparison submodule for comparing the similarity evaluation index with a similarity evaluation threshold, if the similarity evaluation index is smaller than the similarity evaluation threshold, the matching is determined to be successful, otherwise, the matching is determined to be unsuccessful;
and the vehicle selection submodule is used for taking the upper axle end vehicle which is not selected as a new current upper axle end vehicle until all the upper axle end vehicles are selected.
Wherein the apparatus further comprises:
the danger early warning module is used for judging whether the load of the bridge is in a dangerous load range or not, and outputting early warning information if the load of the bridge is in the dangerous load range;
the device further comprises:
the load clearing module is used for counting the average time of successfully matched vehicles within preset time, and if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value, clearing the weight of the upper bridge end vehicle from the bridge load;
or,
the danger early warning module is further used for counting the average time of successfully matched vehicles within preset time, and if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value, the weight of the upper bridge end vehicle is removed from the load of the bridge; and judging whether the bridge load is in a dangerous load range, and if the bridge load is still in the dangerous load range, executing to output early warning information.
The information acquisition module is also used for acquiring the vehicle weight and the characteristic information of the upper bridge end vehicle and the vehicle weight and the characteristic information of the lower bridge end vehicle of the bridge to be monitored in real time;
correspondingly, the information matching module is further configured to use the vehicle weight and the feature information as new feature information, and match the lower axle end vehicle with the upper axle end vehicle according to the new feature information.
According to another aspect of the present invention, there is provided a bridge load monitoring system, the system comprising: the device comprises a first dynamic weighing platform, a first license plate recognition camera, a first vehicle detector, a second license plate recognition camera, a second vehicle detector and the like, wherein the first dynamic weighing platform, the first license plate recognition camera and the first vehicle detector are arranged at the upper bridge end of a bridge to be monitored, the second license plate recognition camera and the second vehicle detector are arranged at the lower bridge end of the bridge to be detected, and the device is connected with the first dynamic weighing platform, the first license plate recognition camera, the first vehicle detector, the second license plate recognition camera and the second vehicle detector.
Wherein the system further comprises: the second dynamic weighing platform is arranged at the lower bridge end of the bridge to be detected and is connected with the device;
and/or the presence of a gas in the gas,
the system further comprises: and the warning unit is connected with the device.
According to the invention, the vehicle weight and the characteristic information of the upper bridge end vehicle and the characteristic information of the lower bridge end vehicle are obtained, the lower bridge end vehicle is matched with the upper bridge end vehicle, the total vehicle weight of the upper bridge end vehicle which is not successfully matched is taken as the bridge load of the bridge to be monitored, the bridge load is conveniently monitored, only a plurality of simpler devices are needed to be arranged, the realization is simple, the cost is low, and the close-range characteristic acquisition is adopted, so that the matching precision is high, and the monitoring precision of the bridge load is ensured.
Drawings
FIG. 1 shows a schematic view of aIs a flow of the bridge load monitoring method of an embodiment of the inventionDrawing (A)；
FIG. 2The invention relates to a structure frame of a bridge load monitoring deviceDrawing (A)；
FIG. 3The invention relates to a structure frame of a bridge load monitoring systemDrawing (A)；
FIG. 4Is thatFIG. 3Side view of the vehicle detectorDrawing (A)；
FIG. 5Is thatFIG. 3In front view of the vehicle detectorDrawing (A)；
FIG. 6Is thatFIG. 3Dynamic weighing platform of (1)Drawing (A)；
FIG. 7Is thatFIG. 3Structural indication of warning unit inDrawing (A)；
FIG. 8Is another embodiment of the inventionStructural frame of systemDrawing (A)。
Detailed Description
Lower surface combinationDrawingsAnd examples, specific embodiments of the present invention are described in further detail. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
FIG. 1 shows a schematic view of aIs a flow of the bridge load monitoring method of an embodiment of the inventionDrawing (A)(ii) a Reference toFIG. 1 shows a schematic view of aThe method comprises the following steps:
s1: acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the characteristic information of a lower bridge end vehicle of a bridge to be monitored in real time;
s2: matching the lower axle end vehicle with the upper axle end vehicle according to the characteristic information;
s3: and acquiring the total vehicle weight of the upper bridge end vehicles which are not successfully matched, and taking the total vehicle weight as the bridge load of the bridge to be monitored.
In this step, the sum of the vehicle weights of the upper axle end vehicles may be accumulated, and then the vehicle weight of the upper axle end vehicle that is successfully matched is removed from the accumulated value, so as to improve the calculation efficiency of step S3.
To ensure the matching accuracy, step S2 preferably includes:
s201: calculating a characteristic deviation between the characteristic information of the lower axle end vehicle and the characteristic information of the current upper axle end vehicle, wherein the characteristic information comprises: at least one of axle weight, axle group weight, axle number, license plate, vehicle length, vehicle height, vehicle width and three-dimensional contour;
s202: calculating a similarity evaluation index according to the characteristic deviation;
s203: comparing the similarity evaluation index with a similarity evaluation threshold eta, if the similarity evaluation index is smaller than the similarity evaluation threshold eta, determining that the matching is successful, and executing a step S3, otherwise, determining that the matching is unsuccessful, and executing a step S204;
s204: and taking the upper bridge end vehicle which is not selected as a new current upper bridge end vehicle, and returning to the step S201 until all the upper bridge end vehicles are selected.
It should be noted that, in the practical process of vehicle matching, there may be a problem of matching delay, so that the "all upper-axle end vehicles" in step S204 refer to the upper-axle end vehicles corresponding to the time when the lower-axle end vehicle is acquired, and for convenience of description, for example, assuming that at 11 pm, the upper bridge end acquires the weight and the feature information of 100 vehicles, and the lower bridge end acquires the feature information of 1 vehicle, the vehicle at the lower bridge end is matched with the 100 vehicles at the upper bridge end, but due to the matching process time course, it is possible that at this time 80 matching succeeds after 5 minutes at 11 pm, the upper bridge end is provided with 10 vehicles within the 5 minutes, the 10 vehicles cannot be taken for matching in the matching process, that is, the "on-coming vehicle" includes only the 100 vehicles acquired at 11 pm.
Taking n as an example, the process of calculating the similarity evaluation index using the feature information in the present embodiment specifically includes:
a1: acquiring characteristic set U ═ x of characteristic information1,x2,x3,x4,x5}. Wherein x is1For license plate matching deviation, x2Is the deviation of the vehicle length, x3Is a deviation of vehicle width, x4Is the vehicle height deviation, x5The three-dimensional contour information of the vehicle. Establishing corresponding weight factor K ═ K1,k2,k3,k4,k5}, cluster center factor Ψ ═ Φ1,φ2,φ3,φ4,φ5The variance factor Σ ═ σ { see1,σ2,σ3,σ4,σ5}。
A2: and judging the matching degree of the factor set U by using the similarity evaluation index, wherein the calculation formula of the similarity evaluation index is as follows:
wherein, mu (x)i) Is a function of the degree of membership, <math><mrow>
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the self-learning process of the parameters in the similarity evaluation index is as follows:
b1: selecting a preset number of pieces of feature information in the feature set as a main dimension, establishing an initial membership function through the main dimension, wherein the preset number is an integer which is not less than 1 and less than n, for example, the preset number is 3, the corresponding feature information is the p-th item, the m-th item and the q-th item, and a weighting factor k is setiThe initial values of (a) are: when i is p, m, q, kiWhen i is other value, k is 1iThe initial membership function is as follows, 0.5:
and (3) acquiring a similarity evaluation index by using a K-means algorithm and taking 0 as a clustering center:
V0＝Σi＝p,m,qki*[μ0(xi)-0]2
when V is0And when the value is 0, the matching is considered to be successful, and the samples which are successfully matched are updated into the sample set A in real time. When the number of the samples in the sample set a is greater than ξ (ξ is a preset value, for example, ξ ═ 10000), the sample set a is updated to be the latest ξ samples, and the procedure goes to step B2. It should be noted that, in this step, in order to ensure the accuracy of parameter self-learning, the main dimension is preferably selected as: at least one of a license plate matching deviation, a vehicle weight deviation, and an axle weight.
B2: training membership function mu of other secondary dimensions according to real-time updated sample set A1(xi) Cluster center phiiAnd a similarity threshold η1，
According to kiAdjustment rule adjustment k ofiSaid k isiThe adjustment rule of (2) is: when D (mu)1(xi))>When is beta, take ki0; when alpha is<D(μ1(xi))<At the time of the beta, the beta is,if k isi<When 0, take ki0; when D (mu)1(xi))<At the time of alpha, the alpha value,kithe maximum iteration value of (a) is not more than 1.5 times of the initial value.
When mu is1(xi) Satisfies the stabilization condition D (. mu.)1(xi) Beta is less than beta, the similarity evaluation index is obtained <math><mrow>
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Wherein phi isi＝E[μ0(xi)],i≠p,m,q， <math><mrow>
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And B3 is executed when the number of the minor dimensions meeting the stability condition is larger than a certain preset value eta, otherwise, the requirement is met along with the real-time updating of the sample set A.
B3, evaluation of index V by similarity1，V2Real-time evaluation of the latest sample, when V1＜η1And V is2When the value is 0, the matching is successful, and the matching is updated to the sample set B in real time.
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when the number of samples of B is larger than that of the samples of BWhen (1)Is a preset value, e.g. taken) Update the sample set B to the latestThe strip sample, and at the same time step B4.
B4, training the membership function mu (x) of the 3 main dimensions in the sample set B updated in real timei) Cluster center phiiAnd a similarity threshold η.
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η ═ e (v) × m, where m is a settable coefficient.
Otherwise, the sample set A is updated in real time until the requirements are met.
It should be noted that the parameter self-learning process of B1-B4 is updated in real time along with the latest vehicle passing data. Therefore, the adaptability of the performance evaluation index parameters is ensured, and the stability of system operation is improved.
In order to perform the danger warning on the bridge load, after step S3, the method further includes:
s4: judging whether the bridge load is in a dangerous load range, and if the bridge load is in the dangerous load range, outputting early warning information;
because matching may have errors, some vehicles have records at the upper bridge end, but the lower bridge end is not successfully matched when actually getting off the bridge, so that the weights of the vehicles are always calculated in the bridge load, which affects the accuracy of the bridge load, in order to avoid this problem, the weights of the vehicles need to be removed from the bridge load, and in order to remove the weights of the vehicles, the removal can be triggered in two ways, the first way is: clearing is carried out every preset period, and the specific process is as follows:
between step S3 and step S4, the method further includes:
counting the average time of successfully matched vehicles within preset time, and removing the weight of the upper bridge end vehicle from the load of the bridge if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value;
the second way is: when the load of the bridge is in the dangerous load range, clearing is carried out, and the specific process is as follows:
in step S4, before outputting the warning information, the method further includes:
counting the average time of successfully matched vehicles within preset time, and removing the weight of the upper bridge end vehicle from the load of the bridge if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value;
and judging whether the bridge load is in a dangerous load range, and if the bridge load is still in the dangerous load range, executing to output early warning information.
In order to calculate the load of the bridge, the vehicle weight of the vehicle at the upper bridge end must be obtained, and when matching the vehicles, the characteristic information can be used, and the vehicle weight can actually be used as one of the characteristic information, so that in the measurement process, in addition to the above characteristic information, the vehicle weight can also be used as the characteristic information for matching, and preferably, the step S1 specifically includes:
acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the vehicle weight and the characteristic information of a lower bridge end vehicle of a bridge to be monitored in real time;
correspondingly, step S2 specifically includes:
and taking the vehicle weight and the characteristic information as new characteristic information, and matching the lower axle end vehicle with the upper axle end vehicle according to the new characteristic information.
Taking n-8 as an example, the present embodiment discloses a process of calculating a similarity evaluation index using new feature information, which specifically includes:
a1': acquiring new characteristic information with characteristic set U ═ x1,x2,x3,x4,x5,x6,x7,x8And establishing a weight factor matrix K (K) for the feature set1,k2,k3,k4,k5,k6,k7,k8}. Wherein x is1Is a vehicleDeviation of card match (match rate), x2As a weight deviation (proportional value), x3As the deviation (difference) of the number of axes, x4Is the mean value (ratio value) of the deviations of the respective axial weights, x5As a deviation of the length of the vehicle (proportional value), x6Is the deviation (ratio) of the vehicle width7As vehicle height deviation (proportional value), x8Is the deviation (proportional value) of the vehicle bridge time difference and the average bridge time. Establishing corresponding weight factor K ═ K1,k2,k3,k4,k5,k6,k7,k8}, cluster center factor Ψ ═ Φ1,φ2,φ3,φ4,φ5,φ6,φ7,φ8The square difference factor Σ ═ σ }1,σ2,σ3,σ4,σ5,σ6,σ7,σ8}。
A2': and judging the matching degree of the factor set U by using a similarity evaluation index, wherein the similarity evaluation index is V:
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the invention also discloses a bridge load monitoring device, and a referenceFIG. 2The device comprises:
the information acquisition module is used for acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the characteristic information of a lower bridge end vehicle of the bridge to be monitored in real time;
the information matching module is used for matching the lower bridge end vehicle with the upper bridge end vehicle according to the characteristic information;
and the load calculation module is used for acquiring the total vehicle weight of the upper bridge end vehicles which are not successfully matched, and taking the total vehicle weight as the bridge load of the bridge to be monitored.
Preferably, the information matching module specifically includes:
a deviation calculation submodule for calculating a characteristic deviation between the characteristic information of the lower axle end vehicle and the characteristic information of the current upper axle end vehicle, the characteristic information including: at least one of axle weight, axle group weight, axle number, license plate, vehicle length, vehicle height, vehicle width and three-dimensional contour;
the index calculation submodule is used for calculating a similarity evaluation index according to the characteristic deviation;
a threshold comparison submodule for comparing the similarity evaluation index with a similarity evaluation threshold, if the similarity evaluation index is smaller than the similarity evaluation threshold, the matching is determined to be successful, otherwise, the matching is determined to be unsuccessful;
and the vehicle selection submodule is used for taking the upper axle end vehicle which is not selected as a new current upper axle end vehicle until all the upper axle end vehicles are selected.
Preferably, the apparatus further comprises:
the danger early warning module is used for judging whether the load of the bridge is in a dangerous load range or not, and outputting early warning information if the load of the bridge is in the dangerous load range;
the device further comprises:
the load clearing module is used for counting the average time of successfully matched vehicles within preset time, and if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value, clearing the weight of the upper bridge end vehicle from the bridge load;
or,
the danger early warning module is further used for counting the average time of successfully matched vehicles within preset time, and if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value, the weight of the upper bridge end vehicle is removed from the load of the bridge; and judging whether the bridge load is in a dangerous load range, and if the bridge load is still in the dangerous load range, executing to output early warning information.
Preferably, the information acquisition module is further configured to acquire the vehicle weight and the characteristic information of an upper bridge end vehicle and the vehicle weight and the characteristic information of a lower bridge end vehicle of the bridge to be monitored in real time;
correspondingly, the information matching module is further configured to use the vehicle weight and the feature information as new feature information, and match the lower axle end vehicle with the upper axle end vehicle according to the new feature information.
The invention further discloses a bridge load monitoring system, and the embodiment takes the dynamic weighing platform, the license plate recognition camera and the vehicle detector which are respectively arranged at the upper bridge end of the bridge and the license plate recognition camera and the vehicle detector at the lower bridge end as examples to illustrate the invention, but does not limit the protection scope of the invention. For details of construction, please refer toFIG. 3The system comprises: the device comprises a first dynamic weighing platform 102, a first license plate recognition camera 103, a first vehicle detector 101, a second license plate recognition camera 105, a second vehicle detector 104 and the device 107, wherein the first dynamic weighing platform 102, the first license plate recognition camera 103, the first vehicle detector 101, the second license plate recognition camera 105 and the second vehicle detector 104 are arranged at the upper bridge end of a bridge to be monitored, the second license plate recognition camera 105 and the second vehicle detector 104 are arranged at the lower bridge end of the bridge to be monitored, and the device 107 is connected with the first dynamic weighing platform 102, the first license plate recognition camera 103, the first vehicle detector 101, the second.
The first vehicle detector 101 is located directly above the first dynamic weighing platform 102 and the first license plate recognition camera 103 is located behind the first dynamic weighing platform 102.
As shown in fig. 4And 5, in the embodiment, the first vehicle detector 101 and the second vehicle detector 104 are both composed of two laser sensors 201, 202 placed at a certain angle, wherein the laser sensor 202 is arranged perpendicular to the road surface, and the installation positions and angles of the laser sensors 201, 202 can be properly calculated through the scanning time and uploading time delay of the laser sensors. The laser sensors 201 and 202 perform 180-degree section scanning distance measurement every 20ms, and can measure the distance between an obstacle in a section and laser.
When a vehicle 203 enters a scanning area of the vehicle detector, namely the vehicle enters a scanning section of the laser sensor 201, judging that the vehicle enters the scanning area after the distance of an obstacle scanned by laser is smaller than a threshold value, recording the time t1 when the vehicle enters the scanning section of the laser sensor 201, controlling a license plate recognition camera to capture, and converting the vehicle width and height data according to the polar coordinate scanned by the section of 180 degrees; when the vehicle continues to move forward to the scanning section of the laser 202, recording the time t2 for entering the scanning section of the laser 202, and converting the time t into the width and height data of the vehicle according to the polar coordinates of the section scanning of 180 degrees; calculating the passing distance delta L of the vehicle passing through the two sections as (H-H) cot alpha according to the height H of the vehicle 203, the height H of the laser and the included angle alpha of the two lasers, and then the running speed v of the vehicle is delta L/(t2-t 1); and recording the time t3 when the vehicle leaves the scanning section 201, and obtaining the length, width, height and three-dimensional profile data of the vehicle when the vehicle length L is equal to v (t3-t 1).
In this embodiment, a dynamic weighing platformAs shown in fig. 6Shown, comprising a load cell 301, a vehicle detector, and a load data processor 303; the load cell 301 is laid on the road surface behind the laser scanning cross-section 302 of the vehicle detector and the signal of the load cell 301 is connected by wires to a load data processing device 303. When a vehicle enters a scanning section 302 of the vehicle detector, the vehicle detector sends the information of the vehicle entering and the vehicle position information to the weighing data processing device 303, then the vehicle runs to the weighing sensor 301 for weighing, the weighing signal of the weighing sensor 301 is uploaded to the weighing data processing device 303 through a conducting wire, and the weighing processing device 303 obtains data of the axle weight, the axle number, the axle distance, the vehicle speed and the like of the vehicle through calculation.
Preferably, the distance between the vehicle detector and the dynamic weighing platform is 0.5-2 m; the distance between the vehicle detector and the license plate recognition camera is 15-25 m.
In order to facilitate the warning prompt, the system further comprises: a warning unit 106, the warning unit 106 being connected to the device 107, the warning unitAs shown in fig. 7The warning unit receives the warning number sent by the deviceAccording to the notice of the short message sending module 502 or the warning lamp 501Legal personAnd the personnel timely take measures to limit the vehicle to continuously get on the bridge.
For obtaining weight of lower axle end, refer toFIG. 8Preferably, the system further comprises: and the second dynamic weighing platform 108 is arranged at the lower bridge end of the bridge to be detected, and the second dynamic weighing platform 108 is connected with the device 107.
The above embodiments are only for illustrating the invention and are not to be construed as limiting the invention, and those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention, therefore, all equivalent technical solutions also belong to the scope of the invention, and the scope of the invention is defined by the claims.
Claims (10)
1. A bridge load monitoring method is characterized by comprising the following steps:
s1: acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the characteristic information of a lower bridge end vehicle of a bridge to be monitored in real time;
s2: matching the lower axle end vehicle with the upper axle end vehicle according to the characteristic information;
s3: and acquiring the total vehicle weight of the upper bridge end vehicles which are not successfully matched, and taking the total vehicle weight as the bridge load of the bridge to be monitored.
2. The method according to claim 1, wherein step S2 specifically comprises:
s201: calculating a characteristic deviation between the characteristic information of the lower axle end vehicle and the characteristic information of the current upper axle end vehicle, wherein the characteristic information comprises: at least one of axle weight, axle group weight, axle number, license plate, vehicle length, vehicle height, vehicle width and three-dimensional contour;
s202: calculating a similarity evaluation index according to the characteristic deviation;
s203: comparing the similarity evaluation index with a similarity evaluation threshold, if the similarity evaluation index is smaller than the similarity evaluation threshold, determining that the matching is successful, and executing a step S3, otherwise, determining that the matching is unsuccessful, and executing a step S204;
s204: and taking the upper bridge end vehicle which is not successfully matched as a new current upper bridge end vehicle, and returning to the step S201 until all the upper bridge end vehicles are selected.
3. The method of claim 1, wherein after step S3, further comprising:
s4: judging whether the bridge load is in a dangerous load range, and if the bridge load is in the dangerous load range, outputting early warning information;
between step S3 and step S4, the method further includes:
counting the average time of successfully matched vehicles within preset time, and removing the weight of the upper bridge end vehicle from the load of the bridge if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value;
or,
in step S4, before outputting the warning information, the method further includes:
counting the average time of successfully matched vehicles within preset time, and removing the weight of the upper bridge end vehicle from the load of the bridge if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value;
and judging whether the bridge load is in a dangerous load range, and if the bridge load is still in the dangerous load range, executing to output early warning information.
4. The method according to any one of claims 1 to 3, wherein the step S1 specifically comprises:
acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the vehicle weight and the characteristic information of a lower bridge end vehicle of a bridge to be monitored in real time;
correspondingly, step S2 specifically includes:
and taking the vehicle weight and the characteristic information as new characteristic information, and matching the lower axle end vehicle with the upper axle end vehicle according to the new characteristic information.
5. A bridge load monitoring device, the device comprising:
the information acquisition module is used for acquiring the vehicle weight and the characteristic information of an upper bridge end vehicle and the characteristic information of a lower bridge end vehicle of the bridge to be monitored in real time;
the information matching module is used for matching the lower bridge end vehicle with the upper bridge end vehicle according to the characteristic information;
and the load calculation module is used for acquiring the total vehicle weight of the upper bridge end vehicles which are not successfully matched, and taking the total vehicle weight as the bridge load of the bridge to be monitored.
6. The apparatus of claim 5, wherein the information matching module specifically comprises:
a deviation calculation submodule for calculating a characteristic deviation between the characteristic information of the lower axle end vehicle and the characteristic information of the current upper axle end vehicle, the characteristic information including: at least one of axle weight, axle group weight, axle number, license plate, vehicle length, vehicle height, vehicle width and three-dimensional contour;
the index calculation submodule is used for calculating a similarity evaluation index according to the characteristic deviation;
a threshold comparison submodule for comparing the similarity evaluation index with a similarity evaluation threshold, if the similarity evaluation index is smaller than the similarity evaluation threshold, the matching is determined to be successful, otherwise, the matching is determined to be unsuccessful;
and the vehicle selection submodule is used for taking the upper axle end vehicle which is not selected as a new current upper axle end vehicle until all the upper axle end vehicles are selected.
7. The apparatus of claim 6, wherein the apparatus further comprises:
the danger early warning module is used for judging whether the load of the bridge is in a dangerous load range or not, and outputting early warning information if the load of the bridge is in the dangerous load range;
the device further comprises:
the load clearing module is used for counting the average time of successfully matched vehicles within preset time, and if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value, clearing the weight of the upper bridge end vehicle from the bridge load;
or,
the danger early warning module is further used for counting the average time of successfully matched vehicles within preset time, and if the ratio of the existing time of the upper bridge end vehicle to the average time exceeds a preset value, the weight of the upper bridge end vehicle is removed from the load of the bridge; and judging whether the bridge load is in a dangerous load range, and if the bridge load is still in the dangerous load range, executing to output early warning information.
8. The device according to any one of claims 5 to 7, wherein the information acquisition module is further configured to acquire the vehicle weight and characteristic information of an upper bridge end vehicle and the vehicle weight and characteristic information of a lower bridge end vehicle of the bridge to be monitored in real time;
correspondingly, the information matching module is further configured to use the vehicle weight and the feature information as new feature information, and match the lower axle end vehicle with the upper axle end vehicle according to the new feature information.
9. A bridge load monitoring system, the system comprising: the device comprises a first dynamic weighing platform, a first license plate recognition camera and a first vehicle detector which are arranged at the upper bridge end of a bridge to be monitored, a second license plate recognition camera and a second vehicle detector which are arranged at the lower bridge end of the bridge to be monitored, and the device as claimed in any one of claims 5 to 8, wherein the first dynamic weighing platform, the first license plate recognition camera, the first vehicle detector, the second license plate recognition camera and the second vehicle detector are all connected with the device.
10. The system of claim 9, wherein the system further comprises: the second dynamic weighing platform is arranged at the lower bridge end of the bridge to be detected and is connected with the device;
and/or the presence of a gas in the gas,
the system further comprises: and the warning unit is connected with the device.
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