Bridge collapse vehicle early warning method based on axle coupling vibration and Internet of Vehicles

Abstract

The invention discloses a bridge collapse vehicle early warning method based on axle coupling vibration and Internet of Vehicles. The method comprises the following steps: acquiring historical vibration data of a bridge and historical operation parameters of vehicles running on the bridge; constructing an axle coupling motion model based on the historical vibration data of the bridge and the historical operation parameters of the running vehicle; predicting whether the bridge collapses or not and the collapse position of the bridge through the axle coupling motion model; if it is predicted that the bridge collapses, early warning is carried out on vehicles at different positions; according to the method, the axle coupling vibration values of the vehicles on the bridge are obtained through the axle coupling motion model, whether the bridge collapses or not and the collapse position are predicted based on the axle coupling vibration values, influences of factors such as weather and visual field obstacles are avoided, it can be guaranteed that a driver can still receive early warning in time under the condition of extreme weather or visual field obstacles, and the driving safety is improved. Therefore, dangerous accidents such as bridge falling, rear-end collision and the like are avoided.

Description

Technical Field

[0001] The present invention relates to the field of traffic safety, and in particular to a bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking. Background Art

[0002] Bridges are common infrastructure in the transportation field, and their collapse has caused countless traffic accidents. When a bridge collapses, drivers may not be able to respond in time due to bad weather and obstructed vision, which may lead to falling off the bridge or rear-end collisions. In addition, when a bridge collapses, due to factors such as weather and vision, visual sensors may find it difficult to capture the collapsed position of the bridge in time, so timely warnings cannot be issued.

[0003] In view of this, the present invention is proposed. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention proposes a vehicle early warning method for bridge collapse based on vehicle-bridge coupled vibration and vehicle networking. The vehicle-bridge coupled vibration value of each vehicle on the bridge is obtained through a vehicle-bridge coupled motion model, and the collapse and location of the bridge are predicted based on the vehicle-bridge coupled vibration value. Once it is predicted that the bridge may collapse, the vehicles on the bridge and the vehicles about to pass can be warned, and evacuation work can be carried out.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention proposes a bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking, comprising the following steps:

[0007] S1. Collect historical vibration data of the bridge and historical operating parameters of vehicles traveling on the bridge;

[0008] S2, constructing a vehicle-bridge coupling motion model based on historical vibration data of the bridge and historical operating parameters of the moving vehicle;

[0009] S3, predicting whether the bridge collapses and the bridge collapse position by using the vehicle-bridge coupled motion model; if the bridge collapses, proceeding to step S4;

[0010] S4. Provide early warning for vehicles at different locations.

[0011] Specifically, S2 includes the following sub-steps:

[0012] S21. constructing a bridge model based on historical vibration data of the bridge;

[0013] S22, constructing a vehicle model based on historical operating parameters of the running vehicle;

[0014] S23, constructing a deformation coordination model between the traveling vehicle and the bridge based on the bridge model and the vehicle model, and determining the interaction force between the traveling vehicle and the bridge according to the deformation coordination model and the vehicle model;

[0015] S24. Based on the interaction force between the moving vehicle and the bridge and the vehicle model, a vehicle-bridge coupling motion model is constructed.

[0016] Specifically, in S2, the vehicle-bridge coupled motion model is described by the following formula:

[0017]

[0018] a vb Indicates the vibration acceleration of the vehicle on the bridge; F tb is the force exerted by the bridge on the vehicle; k vb is the stiffness of the vehicle on the bridge; v vb is the speed of the vehicle on the bridge; c vb is the damping of the vehicle on the bridge; is the rate of change of the vehicle's speed on the bridge; m vb is the mass of the vehicle on the bridge.

[0019] Specifically, S3 specifically includes:

[0020] S31, obtaining real-time vibration data of the bridge and real-time operating parameters of vehicles traveling on the bridge, and obtaining vehicle-bridge coupling vibration values ​​through a vehicle-bridge coupling motion model;

[0021] S32. Determine whether the bridge has collapsed based on the instantaneous change of the vehicle-bridge coupled vibration value. If the result of the determination is that the bridge has collapsed, determine the bridge collapse position based on the vehicle-bridge coupled vibration value.

[0022] Specifically, the vehicle-bridge coupled vibration value is vibration acceleration.

[0023] Specifically, in S32, the specific method for determining whether the bridge has collapsed is: if the number of vehicles on the bridge whose vehicle-bridge coupled vibration values ​​change dramatically accounts for more than 30% of the total vehicles on the bridge, it is determined that the bridge has collapsed.

[0024] Specifically, if the coupling vibration value of the vehicle on the bridge after the change is more than twice the coupling vibration value before the change, the vehicle is considered to be a vehicle with a drastic change in the vehicle-bridge coupling vibration value.

[0025] Specifically, in S32, the collapse position of the bridge is determined based on a curve showing that the vehicle-bridge coupled vibration value changes with the bridge position.

[0026] Specifically, in S31, before obtaining the vehicle-bridge coupling vibration value through the vehicle-bridge coupling motion model, the obtained real-time vibration data of the bridge and the real-time operating parameters of the vehicle traveling on the bridge are filtered and denoised.

[0027] Specifically, S4 includes reminding the vehicle to take emergency braking measures when the distance between the vehicle and the collapse position is less than 30m; reminding the vehicle to perform rapid braking when the distance between the vehicle and the collapse position is less than 50m; and reminding the vehicle to take slow deceleration braking when the distance between the vehicle and the collapse position is greater than or equal to 50m.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] (1) The present invention constructs a vehicle-bridge coupled motion model based on the historical vibration data of the bridge and the historical operating parameters of the traveling vehicle, and determines whether the bridge collapses and the collapse location based on the vehicle-bridge coupled motion model. The historical vibration data of the bridge and the historical operating parameters of the traveling vehicle are both real values, so that the prediction results of the constructed vehicle-bridge coupled motion model are closer to the actual scene and have high accuracy;

[0030] (2) The present invention determines whether a bridge has collapsed and the location of the collapse based on the vehicle-bridge coupled motion model. The prediction process and results are not affected by factors such as weather and visual obstruction. This ensures that the driver can still receive warnings and respond in time in extreme weather or with visual obstruction, thus avoiding dangerous accidents such as falling off the bridge and rear-end collisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0032] Figure 1 A flow chart for predicting whether a bridge collapses according to the present invention;

[0033] Figure 2 This is a flow chart of bridge collapse warning of the present invention. DETAILED DESCRIPTION

[0034] The embodiments of the present invention will be described in detail below with reference to examples, but those skilled in the art will understand that the following examples are only used to illustrate the present invention and should not be construed as limiting the scope of the present invention.

[0035] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0036] In the following description, specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in a variety of other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0037] refer to Figure 1 This embodiment proposes a bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking, characterized in that it includes the following steps:

[0038] S1. Collect historical vibration data of the bridge and historical operating parameters of vehicles traveling on the bridge through sensors installed on both sides of the bridge;

[0039] S2. Construct a vehicle-bridge coupling motion model based on the historical vibration data of the bridge and the historical operating parameters of the vehicle; specifically:

[0040] S21. constructing a bridge model based on historical vibration data of the bridge;

[0041] S22, constructing a vehicle model based on historical operating parameters of the running vehicle;

[0042] S23, constructing a deformation coordination model between the traveling vehicle and the bridge based on the bridge model and the vehicle model, and determining the interaction force between the traveling vehicle and the bridge according to the deformation coordination model and the vehicle model;

[0043] S24. Based on the interaction force between the moving vehicle and the bridge and the vehicle model, a vehicle-bridge coupling motion model is constructed. The vehicle-bridge coupling motion model is described by the following formula:

[0044]

[0045] a vb Indicates the vibration acceleration of the vehicle on the bridge; F tb is the force exerted by the bridge on the vehicle; k vb is the stiffness of the vehicle on the bridge; v vb is the speed of the vehicle on the bridge; c vb is the damping of the vehicle on the bridge; is the rate of change of the vehicle's speed on the bridge; m vb is the mass of the vehicle on the bridge.

[0046] S3. Obtain the real-time vibration data of the bridge and the real-time operating parameters of the vehicle on the bridge, and obtain the vibration acceleration a of the vehicle on the bridge through the vehicle-bridge coupling motion model vb , in this embodiment, the vehicle-bridge coupled vibration value is preferably the vibration acceleration of the vehicle on the bridge;

[0047] According to a vb If the bridge collapses, the bridge collapse position is determined based on the curve of the vehicle-bridge coupling vibration value changing with the bridge position, and then the process goes to S4;

[0048] S4. Provide early warning for vehicles at different locations.

[0049] Specifically, in S3, sensors installed on both sides of the bridge collect real-time vibration data of the bridge and real-time operating parameters of vehicles traveling on the bridge, and transmit the data to the data acquisition device on the vehicle. The data acquisition device performs noise reduction and filtering on the received data, and then transmits it to the server through the Internet of Vehicles. After the server processes the received data, it obtains the vibration acceleration of the vehicle on the bridge through the vehicle-bridge coupling motion model, and judges whether the bridge collapses based on the vibration acceleration of the vehicle on the bridge. If the value of the vibration acceleration of the vehicle on the bridge after the change is more than twice the value before the change, it is considered that the vehicle is a vehicle with a drastic change in the vehicle-bridge coupling vibration value. Taking into account factors such as speed bumps and potholes on the ground, if the vehicles on the bridge with drastic changes in the vehicle-bridge coupling vibration value account for more than 30% of the total vehicles, it is judged that the bridge has collapsed; if it is less than 30%, it is considered that the drastic change may be caused by special reasons such as speed bumps and potholes on the road.

[0050] After confirming the collapse of the bridge, the server cleaned up the data, excluded the vibration values ​​of special vehicle parameters such as trucks and buses, and inferred the location of the bridge collapse based on the changes in the values ​​of other common cars and SUVs; based on the weight of a common car of about 1.5 tons, when traveling on a bridge at a speed of 60-80km / h, the common car-car coupling vibration acceleration is about 0.1g to 0.3g, the dynamic load is about 2KN to 6KN, and the vibration speed is usually between a few centimeters per second (cm / s) and tens of centimeters per second (cm / s); when the bridge collapses, the vibration acceleration will increase significantly, reaching several times or even dozens of times the normal level, and other values ​​will also change dramatically. The closer to the bridge collapse position, the more obvious the change. According to the vehicle position and the transmitted numerical change information, when the bridge collapses, the vehicle-bridge coupled vibration acceleration above the bridge shows the most dramatic change at the collapse position, a convex function image that decreases from the collapse position to both sides. Therefore, on the curve of the vehicle-bridge coupled vibration value changing with the bridge position, the position corresponding to the convex point is determined to be the collapse position of the bridge. The vehicle-bridge coupled vibration acceleration value changes most dramatically within 30 meters from the collapse position, and the speed at which the overall convex function decreases to both sides gradually slows down. The vehicle-bridge coupled vibration acceleration value that is farthest from the collapse position is closer to the value before the transformation.

[0051] Before the vehicle-bridge coupled vibration acceleration changes: A couple =A vehicle +Abridge

[0052] After the vehicle-bridge coupled vibration acceleration changes; A couple =m×(A vehicle +A bridge )

[0053] A couple represents the vehicle-bridge coupled vibration acceleration;

[0054] A ve hicle represents the vehicle vibration acceleration;

[0055] A bridge represents the vibration acceleration of the bridge;

[0056] m is a coefficient that represents the multiple of the impact on vehicles when a bridge collapses. The closer the vehicles are to the collapsed bridge, the greater the impact, and the larger the m value. The farther the vehicles are from the collapsed bridge, the less impact they will have, and the smaller the m value.

[0057] Coefficient m:

[0058] d0 represents a reference distance, which is selected according to the type of bridge;

[0059] d represents the distance between the vehicle and the bridge collapse point.

[0060] In this embodiment S4, under normal circumstances, the speed of the vehicle on the bridge does not exceed 80km / h, so when the distance between the vehicle and the collapsed position is less than 30m, the vehicle warning system reminds the vehicle to take emergency braking measures; when the distance between the vehicle and the collapsed position is 30m≤<50m, the vehicle warning system reminds the vehicle to brake quickly; when the distance between the vehicle and the collapsed position is ≥50m, the vehicle warning system reminds the vehicle to take slow deceleration braking. In addition, the server is connected to the hospital and the traffic control department, and when a bridge collapse is detected, it will send a signal to the hospital and the traffic control department to request support so that they can respond quickly and take appropriate actions.

[0061] In the above embodiment, an alarm system can also be installed at both ends of the bridge. The server can synchronously send the bridge collapse information to the alarm system. When the bridge collapse is detected for the first time, the alarms on both sides start to sound the alarm to remind the cars at the entrances at both ends of the bridge to stop.

[0062] Although the present invention has been described in detail in this specification by means of general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements may be made thereto on the basis of the present invention. Therefore, these modifications or improvements made without departing from the present invention all fall within the scope of protection claimed by the present invention.

Claims

1. A bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking, characterized in that: The following steps are involved: S1. Collect historical vibration data of the bridge and historical operating parameters of vehicles traveling on the bridge; S2, constructing a vehicle-bridge coupling motion model based on historical vibration data of the bridge and historical operating parameters of the moving vehicle; S3, predicting whether the bridge will collapse and the collapse location of the bridge through the vehicle-bridge coupling motion model; If the bridge is predicted to collapse, proceed to step S4; S4. Provide early warning for vehicles at different locations.

2. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 1 is characterized in that: S2 includes the following sub-steps: S21. constructing a bridge model based on historical vibration data of the bridge; S22, constructing a vehicle model based on historical operating parameters of the running vehicle; S23, constructing a deformation coordination model between the traveling vehicle and the bridge based on the bridge model and the vehicle model, and determining the interaction force between the traveling vehicle and the bridge according to the deformation coordination model and the vehicle model; S24. Based on the interaction force between the moving vehicle and the bridge and the vehicle model, a vehicle-bridge coupling motion model is constructed.

3. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 1 is characterized in that: In S2, the vehicle-bridge coupled motion model is described by the following formula: a vb Indicates the vibration acceleration of the vehicle on the bridge; F tb is the force exerted by the bridge on the vehicle; k vb is the stiffness of the vehicle on the bridge; v vb is the speed of the vehicle on the bridge; c vb is the damping of the vehicle on the bridge; is the rate of change of the vehicle's speed on the bridge; m vb is the mass of the vehicle on the bridge.

4. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 1 is characterized in that: S3 specifically includes: S31, obtaining real-time vibration data of the bridge and real-time operating parameters of vehicles traveling on the bridge, and obtaining vehicle-bridge coupling vibration values ​​through a vehicle-bridge coupling motion model; S32. Determine whether the bridge has collapsed based on the instantaneous change of the vehicle-bridge coupled vibration value. If the result of the determination is that the bridge has collapsed, determine the bridge collapse position based on the vehicle-bridge coupled vibration value.

5. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 4 is characterized in that: The vehicle-bridge coupled vibration value is a vibration acceleration.

6. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 4 is characterized in that: In S32, the specific method for judging whether the bridge has collapsed is: if the vehicles on the bridge whose vehicle-bridge coupled vibration values ​​change dramatically account for more than 30% of the total vehicles on the bridge, it is judged that the bridge has collapsed.

7. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 6 is characterized in that: If the coupled vibration value of the vehicle on the bridge after the change is more than twice the coupled vibration value before the change, the vehicle is considered to have a drastic change in the vehicle-bridge coupled vibration value.

8. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 4 is characterized in that: In S32, the collapse position of the bridge is determined based on a curve showing the change of the vehicle-bridge coupled vibration value with the bridge position.

9. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 4 is characterized in that: In S31, before obtaining the vehicle-bridge coupling vibration value through the vehicle-bridge coupling motion model, the obtained real-time vibration data of the bridge and the real-time operating parameters of the vehicle traveling on the bridge are filtered and denoised.

10. The bridge collapse vehicle early warning method based on vehicle-bridge coupled vibration and vehicle networking according to claim 1 is characterized in that: S4 includes reminding the vehicle to take emergency braking measures when the distance between the vehicle and the collapse position is less than 30m; reminding the vehicle to perform rapid braking when the distance between the vehicle and the collapse position is less than 50m; and reminding the vehicle to take slow deceleration braking when the distance between the vehicle and the collapse position is ≥50m.

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