CN112562278A - 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 PDFInfo
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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
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- 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
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
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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
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 bridge overload risk 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, coordination measures are taken in advance, the time of the vehicles passing through the bridge is regulated and controlled, the occurrence of overload events is avoided, and the accident risk is reduced.
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 bridgek=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 calculated respectively, 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,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<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
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 bridgeSet of vehicles for up-direction key monitoringAnd downward direction key monitoring vehicle setWherein Po is a vehicle position vector, wg is a vehicle load capacity, and Tr is a vehicle driving route vectorAnd v is the running speed of the vehicle,the total number of vehicles in the upward direction,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 tauAnd the downward direction mainly monitors the dynamic load applied by the vehicle to the downward direction of the bridge
S143, obtaining the traffic flow of the upward direction of the bridge in each time slice tauAnd the traffic flow in the downstream directionCalculating the basic dynamic load of the tau bridge in the upward direction of each time sliceAnd basic dynamic load of bridge descending directionWherein Wo is a vehicle average load parameter;
s144, calculating the dynamic load of the bridge in the upward direction in each time slice tauAnd dynamic load in the downstream direction
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 sliceAnd dynamic load in the downstream directionAnd (4) judging:
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, according to the important monitoring vehicle set passing through the bridge in the first time slice of generating the three-level alarmObtaining a subset satisfying the following conditions
1) CollectionThe dynamic load of the vehicle to the bridge is less than the upper limit value of the anti-overturning load; 2) among all the subsets satisfying the condition 1),the number of the medium elements is minimum;
s33, calculating a set of the dataWhen 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 integratedThe speed of the vehicle to be maintained and willMerging collectionsIn the middle, namely the set of the key monitoring vehicles passing through the bridge at the (r + 1) th time slice after adjustment is
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, the bridge is positioned on a route of the vehicle front, wherein 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 key vehicles at high speed is 80 km/h, the speed of common roads is 40 km/h, the speed of the converted vehicles at second is 22.22 m/s and 11.11 m/s, and the 10 m/s-20 m/s is obtained by rounding;
S131, calculating the time t when the vehicle reaches the bridge1,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<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 carries out the steps S131 to S133, and the important monitoring that each time slice T passes through the bridge is obtainedVehicle assembly
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:
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 bridgeSet of vehicles for up-direction key monitoringAnd downward direction key monitoring vehicle setWherein Po is a vehicle position vector, wg is a vehicle load, Tr is a vehicle driving route vector, v is a vehicle driving speed,the total number of vehicles in the upward direction,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 tauAnd the downward direction mainly monitors the dynamic load applied by the vehicle to the downward direction of the bridgeWhereinThe vehicle load capacity corresponding to each vehicle;
s143, obtaining the traffic flow of the upward direction of the bridge in each time slice tauAnd the traffic flow in the downstream directionCalculating the basic dynamic load of the tau bridge in the upward direction of each time sliceAnd basic dynamic load of bridge descending directionWherein Wo is a vehicle average load parameter;
s144, calculating the dynamic load of the bridge in the upward direction in each time slice tauAnd dynamic load in the downstream direction
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 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.
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 sliceAnd dynamic load in the downstream directionAnd (4) judging:
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 alarmObtaining a subset satisfying the following conditions
1) CollectionThe dynamic load of the vehicle to the bridge is less than the upper limit value of the anti-overturning load; 2) among all the subsets satisfying the condition 1),the number of the medium elements is minimum;
s33, calculating a set of the dataWhen 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 integratedThe speed of the vehicle to be maintained and willMerging collectionsIn the middle, namely the set of the key monitoring vehicles passing through the bridge at the (r + 1) th time slice after adjustment is
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 time slices according to the step S14, re-judging the dynamic loads of the bridge in the r and r +1 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 vminAnd regulating 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 (7)
1. A method for realizing bridge load early warning monitoring 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;
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.
2. The method for realizing bridge load early warning and monitoring based on traffic big data as claimed in claim 1, wherein said 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;
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 said step S13 specifically comprises:
s131, calculating the time t when the vehicle reaches the bridge1,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<If N τ, N is 1,2 … N, the vehicle is recorded in the nth time slot;
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 bridgeSet of vehicles for up-direction key monitoringAnd downward direction key monitoring vehicle setWherein Po is a vehicle position vector, wg is a vehicle load, Tr is a vehicle driving route vector, v is a vehicle driving speed,the total number of vehicles in the upward direction,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 tauAnd the downward direction mainly monitors the dynamic load applied by the vehicle to the downward direction of the bridge
S143, obtaining the traffic flow of the upward direction of the bridge in each time slice tauAnd the traffic flow in the downstream directionCalculating the basic dynamic load of the tau bridge in the upward direction of each time sliceAnd basic dynamic load of bridge descending directionWherein Wo is a vehicle average load parameter;
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:
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 sliceAnd dynamic load in the downstream directionAnd (4) judging:
6. The method for realizing bridge load early warning and monitoring based on traffic big data as claimed in claim 1, wherein said 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, according to the important monitoring vehicle set passing through the bridge in the first time slice of generating the three-level alarmObtaining a subset satisfying the following conditions
1) CollectionThe dynamic load of the vehicle to the bridge is less than the upper limit value of the anti-overturning load; 2) among all the subsets satisfying the condition 1),the number of the medium elements is minimum;
s33, calculating a set of the dataWhen 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 integratedThe speed of the vehicle to be maintained and willMerging collectionsIn the middle, namely the set of the key monitoring vehicles passing through the bridge at the (r + 1) th time slice after adjustment is
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.
7. The method as claimed in claim 6, wherein in step S36, if the vehicle speed that each vehicle should keep is lower than the minimum vehicle speed vminAnd regulating and controlling the vehicle to stop at the side for waiting.
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CN115440010A (en) * | 2022-08-12 | 2022-12-06 | 无锡小淞交通科技发展有限公司 | Bridge remote monitoring early warning device based on thing networking |
CN117373231A (en) * | 2023-07-27 | 2024-01-09 | 交通运输部公路科学研究所 | Front touch type monitoring method and system for dynamic response of medium and small bridges under vehicle load |
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