CN112562278B - Method for realizing bridge load early warning monitoring based on traffic big data - Google Patents

Method for realizing bridge load early warning monitoring based on traffic big data Download PDF

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CN112562278B
CN112562278B CN202011353180.3A CN202011353180A CN112562278B CN 112562278 B CN112562278 B CN 112562278B CN 202011353180 A CN202011353180 A CN 202011353180A CN 112562278 B CN112562278 B CN 112562278B
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bridge
vehicle
load
early warning
time
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CN112562278A (en
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陈迎迎
杨霖
倪旭煌
钟会玲
王晨
姜雪明
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Zhejiang Supcon Information Industry Co Ltd
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Zhejiang Supcon Information Industry Co Ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
    • G01G19/03—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions

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Abstract

The invention discloses a method for realizing bridge load early warning monitoring based on traffic big data, which comprises the following steps: s1, setting a prediction time period, dividing the prediction time period into N time slices, and calculating the dynamic load of the bridge in each time slice according to the data of the traffic information platform; s2, judging the dynamic load according to a preset load, and outputting early warning information or not giving an early warning according to a judgment result; and S3, judging whether the early warning information exceeds a preset early warning information grade, and regulating and controlling the time of the vehicle passing through the bridge if the early warning information exceeds the preset early warning information grade. The invention utilizes the traffic information platform data to evaluate the overload risk of the bridge, and takes coordination measures in advance to avoid the occurrence of overload events and reduce the accident risk.

Description

Method for realizing bridge load early warning monitoring based on traffic big data
Technical Field
The invention relates to the technical field of bridge monitoring, in particular to a method for realizing bridge load early warning monitoring based on traffic big data.
Background
With the gradual increase of the load capacity and the traffic flow of vehicles, the durability and the safety of cities and highway bridges are subjected to verification tests. Once a safety accident occurs, not only can huge economic loss be caused, but also casualties can be caused, and the social influence is severe. Multiple analysis results show that overload is the main cause in the bridge overturning accident. Most of the existing bridge load monitoring systems need to install sensors on bridge bodies, a communication system periodically collects working parameters including real-time load and the like in a normal operation state of a bridge, a central control system analyzes and processes the collected parameters, the collected parameters are compared with an index threshold value of a bridge structure health monitoring system, an alarm is given when the collected parameters exceed the index threshold value, and only an alarm is given after an overload event occurs.
For example, chinese patent document CN205027429U discloses "a bridge load monitoring system", which includes: the device comprises a weighing platform, a coil, an automobile electronic identification read-write device and a data acquisition processor, wherein the weighing platform is arranged at the upper bridge end of the bridge to be monitored, and the automobile electronic identification read-write device is arranged at the lower bridge end of the bridge to be monitored. The system obtains vehicle information on the bridge through the automobile electronic identification read-write equipment arranged at the upper bridge end and the lower bridge end, and obtains the weight of the vehicle through the weighing platform, so that the calculation of the load of the bridge is realized. The above patent documents have the disadvantage that the load of the bridge can only be monitored in real time, and cannot be predicted.
Disclosure of Invention
The invention mainly solves the technical problem that the existing bridge load monitoring method cannot carry out prediction regulation and control on the load of the bridge; the method for realizing the bridge load early warning monitoring based on the traffic big data is provided, the traffic information platform data is utilized to evaluate the bridge overload risk, and coordination measures are taken in advance to avoid the occurrence of overload events and reduce the accident risk.
The technical problem of the invention is mainly solved by the following technical scheme: the invention comprises the following steps:
s1, setting a prediction time period, dividing the prediction time period into N time slices, and calculating the dynamic load of the bridge in each time slice according to the data of the traffic information platform;
s2, judging the dynamic load according to a preset load, and outputting early warning information according to a judgment result;
and S3, judging whether the early warning information exceeds a preset early warning information grade, and regulating and controlling the time of the vehicle passing through the bridge if the early warning information exceeds the preset early warning information grade.
According to the invention, no additional bridge load monitoring equipment is needed, the overload risk of the bridge is evaluated by utilizing the traffic information platform data, wherein the traffic information platform data comprises real-time GPS positioning data, electronic waybill data, travel route data, road surface flow, traffic conditions and the like of large heavy-duty vehicles including two-passenger-one-dangerous vehicles and the like, and coordination measures are taken in advance to regulate and control the time of the vehicles passing through the bridge, avoid the occurrence of overload events and reduce the accident risk.
Preferably, the step S1 specifically includes:
s11, setting a prediction time period T, and dividing the prediction time period T equally into N time slices τ, i.e., T ═ N × τ;
s12, obtaining a key monitoring vehicle set G of which the predicted time period T passes through the bridgepThe selection basis of the key monitoring vehicles is as follows: the distance between the current position of the vehicle and the bridge is less than or equal to Len meters, and the bridge is positioned on a route in front of the vehicle, wherein Len is T multiplied by v, v is the running speed of the vehicle, and the value range of v is 10 m/s-20 m/s;
s13, acquiring important monitoring vehicle set of each time slice tau passing through the bridge
Figure BDA0002801872910000021
k＝1,2,3…N；
And S14, calculating the dynamic load of the bridge in the upward direction and the dynamic load of the bridge in the downward direction in each time slice tau.
Because the bridge is divided into two unilateral directions of an ascending direction and a descending direction, when the unilateral load of the bridge exceeds the upper limit of the shear resistant load, the bridge has the risk of structural shear failure, and when the unilateral load of the bridge exceeds the upper limit of the overturn resistant load, the bridge has the risk of overturning. Therefore, the dynamic load of the bridge in the uplink direction and the dynamic load of the bridge in the downlink direction in each time slice are respectively calculated, and the accuracy of bridge overload risk assessment is guaranteed.
Preferably, the step S13 specifically includes:
s131, calculating the time t when the vehicle reaches the bridge1，
Figure BDA0002801872910000022
Wherein L is1Distance of the current position of the vehicle from the bridge, L2The length of the bridge is shown, and v is the running speed of the vehicle;
s132, if (n-1) tau is less than or equal to t1<N τ, N equals 1,2 … N, the vehicle is logged in the nth timeSlicing;
s134, a counterweight monitoring vehicle set GpEach vehicle in the group goes through steps S131 to S133, and a key monitoring vehicle set with each time slice tau passing through the bridge is obtained
Figure BDA0002801872910000023
Preferably, the step S14 specifically includes:
s141, according to the vehicle information Vh (Po, wg, Tr, v) acquired by the traffic information platform, the important monitoring vehicle sets of each time slice tau passing through the bridge
Figure BDA0002801872910000024
Set of vehicles for up-direction key monitoring
Figure BDA0002801872910000025
And downward direction key monitoring vehicle set
Figure BDA0002801872910000026
Wherein Po is a vehicle position vector, wg is a vehicle load, Tr is a vehicle driving route vector, v is a vehicle driving speed,
Figure BDA0002801872910000027
the total number of vehicles in the upward direction,
Figure BDA0002801872910000028
the total number of vehicles in the descending direction;
s142, calculating dynamic loads applied to the bridge in the upward direction by the important monitoring vehicles in the upward direction of each time slice tau
Figure BDA0002801872910000031
And the downward direction mainly monitors the dynamic load applied by the vehicle to the downward direction of the bridge
Figure BDA0002801872910000032
S143, acquiring the ascending of the bridge in each time slice tauDirectional traffic flow
Figure BDA0002801872910000033
And the traffic flow in the downstream direction
Figure BDA0002801872910000034
Calculating the basic dynamic load of the tau bridge in the upward direction of each time slice
Figure BDA0002801872910000035
And basic dynamic load of bridge descending direction
Figure BDA0002801872910000036
Wherein Wo is a vehicle average load parameter;
s144, calculating the dynamic load of the bridge in the upward direction in each time slice tau
Figure BDA0002801872910000037
And dynamic load in the downstream direction
Figure BDA0002801872910000038
When the dynamic load is calculated, the vehicle load capacity of each key monitoring vehicle is calculated to serve as the dynamic load applied to the bridge by the key monitoring vehicle, and the dynamic load applied to the bridge by the other vehicles is calculated by adopting the vehicle average load parameter for the other vehicles, so that the calculation accuracy of the dynamic load of the bridge is ensured.
Preferably, the step S2 specifically includes:
the upper limit value pk of the anti-overturning load of the bridgeupDynamic loading of the bridge in the upstream direction for a predetermined load for each time slice
Figure BDA0002801872910000039
And dynamic load in the downstream direction
Figure BDA00028018729100000310
And (4) judging:
1) make things unnecessary forEarly warning:
Figure BDA00028018729100000311
and is
Figure BDA00028018729100000312
2) Primary alarm:
Figure BDA00028018729100000313
or
Figure BDA00028018729100000314
3) And (4) secondary alarm:
Figure BDA00028018729100000315
or
Figure BDA00028018729100000318
4) And (3) three-level alarm:
Figure BDA00028018729100000316
or
Figure BDA00028018729100000317
The upper limit of the load influencing the safety and the usability of the bridge is the upper limit of the shear resistance load and the upper limit of the overturn resistance load. When the unilateral load of bridge exceeds the upper limit of shear load, there is the structural shear failure risk in the bridge, when the unilateral load of bridge exceeds the upper limit of antidumping load, there is the risk of toppling. Generally, the upper limit of the anti-overturning load is lower than the upper limit of the anti-shearing load. Therefore, the upper limit of the anti-overturning load is taken as the judgment criterion.
Preferably, the step S3 specifically includes:
s31, counting the number S of time slices with three-level alarms in the N time slices, if S is equal to 0, the time of the vehicle passing through the bridge does not need to be regulated, and if S is not equal to 0, the first time slice with three-level alarms is located;
s32, generating three-level alarm according to the first oneThe key monitoring vehicle set passing through the bridge in the time slice
Figure BDA0002801872910000041
Obtaining a subset satisfying the following conditions
Figure BDA0002801872910000042
1) Collection
Figure BDA0002801872910000043
The dynamic load of the vehicle to the bridge is smaller than the upper limit value of the anti-overturning load; 2) among all the subsets satisfying the condition 1),
Figure BDA0002801872910000044
the number of the medium elements is minimum;
s33, calculating a set of the data
Figure BDA0002801872910000045
When the time of the middle vehicle passing the bridge is delayed from the r-th time slice to the r + 1-th time slice, the time is integrated
Figure BDA0002801872910000046
The speed of the vehicle to be maintained and will
Figure BDA0002801872910000047
Merging collections
Figure BDA0002801872910000048
In the middle, namely the set of the key monitoring vehicles passing through the bridge at the (r + 1) th time slice after adjustment is
Figure BDA0002801872910000049
S34, determining whether r is equal to N, if r is equal to N, performing step S36, otherwise, performing step S35;
s35, recalculating the dynamic loads of the bridge in the r-th and r + 1-th time slices according to the step S1, re-judging the dynamic loads of the bridge in the r-th and r + 1-th time slices according to the step S2, and returning to the step S31;
and S36, sending the vehicle speed which is calculated in the step S33 and is required to be kept by each vehicle to each key monitoring vehicle, and regulating and controlling the time of the vehicles passing through the bridge.
And coordination measures are taken in advance, the time of the vehicle passing through the bridge is regulated and controlled, the occurrence of overload events is avoided, and the accident risk is reduced.
Preferably, in step S36, the vehicle speed to be maintained by each vehicle is lower than the minimum vehicle speed vminAnd regulating and controlling the vehicle to stop at the side for waiting.
The invention has the beneficial effects that: no additional bridge load monitoring equipment is needed, and the cost is low; and evaluating the overload risk of the bridge by using the data of the traffic information platform, and adopting a coordination measure in advance to regulate and control the time of the vehicle passing through the bridge, so that the occurrence of an overload event is avoided, and the accident risk is reduced.
Drawings
FIG. 1 is a flow chart of a method of the present invention.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b): the method for realizing bridge load early warning monitoring based on traffic big data in the embodiment is shown in fig. 1 and comprises the following steps:
s1, setting a prediction time period, dividing the prediction time period into N time slices, and calculating the dynamic load of the bridge in each time slice according to traffic information platform data, wherein the traffic information platform data comprises real-time GPS positioning data, electronic waybill data, travel route data, road surface flow, traffic conditions and the like of large heavy-duty vehicles including two-passenger-one-dangerous vehicles and the like:
s11, setting a prediction time period T, and dividing the prediction time period T equally into N time slices τ, i.e., T ═ N × τ;
s12, obtaining a key monitoring vehicle set G of which the predicted time period T passes through the bridgepThe selection basis of the key monitoring vehicle is as follows: the distance between the current position of the vehicle and the bridge is less than or equal to Len meters, and the bridge is positioned on a route in front of the vehicle, and the distance is less than or equal to Len metersThe middle Len is T multiplied by v, v is the running speed of the vehicle, the value range of v is 10 m/s-20 m/s, the speed of an important vehicle on the high speed is limited to 80 kilometers per hour, the speed of a common road is limited to 40 kilometers per hour, the speed of a converted vehicle is 22.22 meters per second and 11.11 meters per second, and the 10 m/s-20 m/s is obtained by rounding;
s13, acquiring important monitoring vehicle set of each time slice tau passing through the bridge
Figure BDA0002801872910000051
S131, calculating the time t when the vehicle reaches the bridge1，
Figure BDA0002801872910000052
Wherein L is1Is the distance from the current position of the vehicle to the bridge, L2The length of the bridge is shown, and v is the running speed of the vehicle;
s132, if (n-1) tau is less than or equal to t1<If N τ, N is 1,2 … N, the vehicle is recorded in the nth time slot;
s134, a counterweight monitoring vehicle set GpEach vehicle in the time slice T passes through the key monitoring vehicle set of the bridge in the steps S131 to S133
Figure BDA0002801872910000053
S14, calculating the dynamic load of the bridge in the upward direction and the dynamic load of the bridge in the downward direction within each time slice tau:
s141, according to the vehicle information Vh (Po, wg, Tr, v) acquired by the traffic information platform, the important monitoring vehicle sets of each time slice tau passing through the bridge
Figure BDA0002801872910000054
Set of vehicles for up-direction key monitoring
Figure BDA0002801872910000055
And downward direction key monitoring vehicle set
Figure BDA0002801872910000056
Wherein Po is a vehicle position vector, wg is a vehicle load, Tr is a vehicle driving route vector, v is a vehicle driving speed,
Figure BDA0002801872910000057
the total number of vehicles in the upward direction,
Figure BDA0002801872910000058
the total number of vehicles in the descending direction;
s142, calculating dynamic loads applied to the bridge in the upward direction by the important monitoring vehicles in the upward direction of each time slice tau
Figure BDA0002801872910000059
And the downward direction mainly monitors the dynamic load applied by the vehicle to the downward direction of the bridge
Figure BDA00028018729100000510
Wherein
Figure BDA00028018729100000511
The vehicle load capacity corresponding to each vehicle;
s143, acquiring the traffic flow of the bridge in the upward direction in each time slice tau
Figure BDA00028018729100000512
And the traffic flow in the downstream direction
Figure BDA00028018729100000513
Calculating the basic dynamic load of the tau bridge in the upward direction of each time slice
Figure BDA0002801872910000061
And basic dynamic load of bridge descending direction
Figure BDA0002801872910000062
Wherein Wo is a vehicle average load parameter;
s144, calculating the dynamic load of the bridge in the upward direction in each time slice tau
Figure BDA0002801872910000063
And dynamic load in the downstream direction
Figure BDA0002801872910000064
Because the bridge is divided into two unilateral directions of an ascending direction and a descending direction, when the unilateral load of the bridge exceeds the upper limit of the shear resistant load, the bridge has the risk of structural shear failure, and when the unilateral load of the bridge exceeds the upper limit of the overturn resistant load, the bridge has the risk of overturning. Therefore, the dynamic load of the bridge in the uplink direction and the dynamic load of the bridge in the downlink direction in each time slice are calculated respectively, and the accuracy of bridge overload risk assessment is guaranteed.
When the dynamic load is calculated, the vehicle load capacity of each important monitoring vehicle is calculated to serve as the dynamic load applied to the bridge by the important monitoring vehicle, and the dynamic load applied to the bridge by other vehicles is calculated by adopting the vehicle average load parameter for other vehicles, so that the calculation accuracy of the dynamic load of the bridge is ensured.
S2, judging the dynamic load according to the preset load, and outputting early warning information according to the judgment result:
the upper limit value pk of the anti-overturning load of the bridgeupDynamic loading of the bridge in the upstream direction for a predetermined load for each time slice
Figure BDA0002801872910000065
And dynamic load in the downstream direction
Figure BDA0002801872910000066
And (4) judging:
1) no early warning is given:
Figure BDA0002801872910000067
and is
Figure BDA0002801872910000068
2) Primary alarm:
Figure BDA0002801872910000069
or
Figure BDA00028018729100000610
3) Secondary alarm:
Figure BDA00028018729100000611
or
Figure BDA00028018729100000612
4) And (3) three-level alarm:
Figure BDA00028018729100000613
or
Figure BDA00028018729100000614
The upper limit of the load influencing the safety and the usability of the bridge is the upper limit of the shear resistance load and the upper limit of the overturn resistance load. When the unilateral load of bridge exceeds the upper limit of shear load, there is the structural shear failure risk in the bridge, when the unilateral load of bridge exceeds the upper limit of antidumping load, there is the risk of toppling. Generally, the upper limit of the anti-overturning load is lower than the upper limit of the anti-shearing load. Therefore, the upper limit of the anti-overturning load is taken as the judgment criterion.
S3, judging whether the early warning information exceeds a preset early warning information grade, and if the early warning information exceeds the preset early warning information grade, regulating and controlling the time of the vehicle passing through the bridge:
s31, counting the number S of time slices with three-level alarms in the N time slices, if S is equal to 0, the time of the vehicle passing through the bridge does not need to be regulated, and if S is not equal to 0, the first time slice with three-level alarms is located;
s32, according to the important monitoring vehicle set passing through the bridge in the first time slice of generating the three-level alarm
Figure BDA0002801872910000071
Obtaining a subset satisfying the following conditions
Figure BDA0002801872910000072
1) Collection
Figure BDA0002801872910000073
The dynamic load of the vehicle to the bridge is smaller than the upper limit value of the anti-overturning load; 2) among all the subsets satisfying the condition 1),
Figure BDA0002801872910000074
the number of the medium elements is minimum;
s33, calculating a set of the data
Figure BDA0002801872910000075
When the time of the middle vehicle passing the bridge is delayed from the r-th time slice to the r + 1-th time slice, the time is integrated
Figure BDA0002801872910000076
The speed of the vehicle to be kept and will
Figure BDA0002801872910000077
Merging collections
Figure BDA0002801872910000078
In the middle, namely the set of the key monitoring vehicles passing through the bridge at the (r + 1) th time slice after adjustment is
Figure BDA0002801872910000079
S34, determining whether r is equal to N, if r is equal to N, performing step S36, otherwise, performing step S35;
s35, recalculating the dynamic loads of the bridge in the upward direction and the downward direction in the r and r +1 th time slices according to the step S14, re-judging the dynamic loads of the bridge in the r and r +1 th time slices according to the step S2, and returning to the step S31;
s36, sending the vehicle speed which is calculated in the step S33 and is required to be kept by each vehicle to each important monitoring vehicle, regulating and controlling the time of the vehicles passing through the bridge, and if the vehicle speed which is required to be kept by each vehicle is lower than the minimum vehicle speed vminThen, thenRegulating and controlling the vehicle to stop at the side for waiting.
According to the embodiment, additional bridge load monitoring equipment is not needed, the cost is low, the overload risk of the bridge is evaluated by utilizing the data of the traffic information platform, and coordination measures are taken in advance to regulate and control the time of a vehicle passing through the bridge, so that the occurrence of an overload event is avoided, and the accident risk is reduced.

Claims (6)

1. A bridge load early warning monitoring method based on traffic big data is characterized by comprising the following steps:
s1, setting a prediction time period, dividing the prediction time period into N time slices, and calculating the dynamic load of the bridge in each time slice according to the data of the traffic information platform;
s2, judging the dynamic load according to a preset load, and outputting early warning information according to a judgment result, wherein the early warning information comprises no warning, a first-level warning, a second-level warning and a third-level warning;
s3, judging whether the early warning information exceeds a preset early warning information grade, and regulating and controlling the time of the vehicle passing through the bridge if the early warning information exceeds the preset early warning information grade;
s3 specifically includes:
s31, counting the number S of time slices with three-level alarms in the N time slices, if S is equal to 0, the time of the vehicle passing through the bridge does not need to be regulated, and if S is not equal to 0, the first time slice with three-level alarms is located;
s32, according to the important monitoring vehicle set passing through the bridge in the first time slice of generating the three-level alarm
Figure FDA0003456409420000011
Obtaining a subset satisfying the following conditions
Figure FDA0003456409420000012
1) Collection
Figure FDA0003456409420000013
Dynamic loading of the bridge by the vehicle in (1)Less than the upper limit value of the overturn resisting load; 2) among all the subsets satisfying the condition 1),
Figure FDA0003456409420000014
the number of the medium elements is minimum;
s33, calculating a set of the data
Figure FDA0003456409420000015
When the time of the middle vehicle passing the bridge is delayed from the r-th time slice to the r + 1-th time slice, the time is integrated
Figure FDA0003456409420000016
The speed of the vehicle to be maintained and will
Figure FDA0003456409420000017
Merging collections
Figure FDA0003456409420000018
In the middle, namely the set of the key monitoring vehicles passing through the bridge at the (r + 1) th time slice after adjustment is
Figure FDA0003456409420000019
S34, determining whether r is equal to N, if r is equal to N, performing step S36, otherwise, performing step S35;
s35, recalculating the dynamic loads of the bridge in the r-th and r + 1-th time slices according to the step S1, re-judging the dynamic loads of the bridge in the r-th and r + 1-th time slices according to the step S2, and returning to the step S31;
and S36, sending the vehicle speed which is calculated in the step S33 and is required to be kept by each vehicle to each key monitoring vehicle, and regulating and controlling the time of the vehicles passing through the bridge.
2. The method for realizing bridge load early warning and monitoring based on traffic big data as claimed in claim 1, wherein the step S1 specifically comprises:
s11, setting a prediction time period T, and dividing the prediction time period T equally into N time slices τ, i.e., T ═ N × τ;
s12, obtaining a key monitoring vehicle set G of which the predicted time period T passes through the bridgepThe selection basis of the key monitoring vehicles is as follows: the distance between the current position of the vehicle and the bridge is less than or equal to Len meters, and the bridge is positioned on a route in front of the vehicle, wherein Len is T multiplied by v, v is the running speed of the vehicle, and the value range of v is 10 m/s-20 m/s;
s13, acquiring important monitoring vehicle set of each time slice tau passing through the bridge
Figure FDA0003456409420000021
And S14, calculating the dynamic load of the bridge in the upward direction and the dynamic load of the bridge in the downward direction in each time slice tau.
3. The method for realizing bridge load early warning and monitoring based on traffic big data as claimed in claim 2, wherein the step S13 specifically comprises:
s131, calculating the time t when the vehicle reaches the bridge1，
Figure FDA0003456409420000022
Wherein L is1Distance of the current position of the vehicle from the bridge, L2The length of the bridge and v is the running speed of the vehicle;
s132, if (n-1) tau is less than or equal to t1If N is less than N tau, N is 1,2 … N, recording the vehicle into the nth time slice;
s134, a counterweight monitoring vehicle set GpEach vehicle in the time slice T passes through the key monitoring vehicle set of the bridge in the steps S131 to S133
Figure FDA0003456409420000023
4. The method for realizing bridge load early warning and monitoring based on traffic big data as claimed in claim 2, wherein said step S14 specifically comprises:
s141, according to the vehicle information Vh (Po, wg, Tr, v) acquired by the traffic information platform, the important monitoring vehicle sets of each time slice tau passing through the bridge
Figure FDA0003456409420000024
Set of vehicles for monitoring key in uplink direction
Figure FDA0003456409420000025
And downward direction key monitoring vehicle set
Figure FDA0003456409420000026
Wherein Po is a vehicle position vector, wg is a vehicle load, Tr is a vehicle driving route vector, v is a vehicle driving speed,
Figure FDA0003456409420000027
the total number of vehicles in the upward direction,
Figure FDA0003456409420000028
the total number of vehicles in the descending direction;
s142, calculating dynamic loads applied to the bridge in the upward direction by the important monitoring vehicles in the upward direction of each time slice tau
Figure FDA0003456409420000029
And the downward direction mainly monitors the dynamic load applied by the vehicle to the downward direction of the bridge
Figure FDA00034564094200000210
S143, obtaining the traffic flow of the upward direction of the bridge in each time slice tau
Figure FDA00034564094200000211
And the traffic flow in the downstream direction
Figure FDA00034564094200000212
Calculating the basic dynamic load of the tau bridge in the upward direction of each time slice
Figure FDA00034564094200000213
And basic dynamic load of bridge descending direction
Figure FDA0003456409420000031
Wherein Wo is a vehicle average load parameter;
s144, calculating the dynamic load of the bridge in the upward direction in each time slice tau
Figure FDA0003456409420000032
And dynamic load in the downstream direction
Figure FDA0003456409420000033
5. The method for realizing bridge load early warning and monitoring based on traffic big data as claimed in claim 1, wherein said step S2 specifically includes:
dynamic load of the bridge in the upward direction in each time slice by taking the upper limit value W of the anti-overturning load of the bridge as a preset load
Figure FDA0003456409420000034
And dynamic load in the downstream direction
Figure FDA0003456409420000035
And (4) judging:
1) no early warning is given:
Figure FDA0003456409420000036
and is
Figure FDA0003456409420000037
2) Primary alarm:
Figure FDA0003456409420000038
or
Figure FDA0003456409420000039
3) Secondary alarm:
Figure FDA00034564094200000310
or
Figure FDA00034564094200000311
4) And (3) three-level alarm:
Figure FDA00034564094200000312
or
Figure FDA00034564094200000313
6. The method as claimed in claim 1, wherein in step S36, if the vehicle speed to be maintained by each vehicle is lower than the minimum vehicle speed vminAnd regulating and controlling the vehicle to stop at the side for waiting.
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CN113781783B (en) * 2021-10-26 2023-01-24 长兴县交通投资集团有限公司 Road network level vehicle overload identification and emergency early warning method
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