A bridge runoff intelligent monitoring and early warning method

Abstract

The present invention relates to the field of intelligent monitoring of bridge deck runoff, and provides an intelligent monitoring and early warning method for bridge deck runoff, comprising: calculating the runoff detection area of ​​each bridge deck based on the stored position information of each bridge deck; respectively allocating corresponding point cloud detection points to the bridge deck area and two buffer areas corresponding to the bridge deck area; adjusting the runoff detection area of ​​the bridge deck and using it as the real-time runoff detection area; defining accident sampling points of the real-time runoff detection area, and simulating the runoff conditions of the real-time runoff detection area when different types of pollutants are leaked under various meteorological conditions at each accident sampling point; respectively obtaining image information of each simulated runoff condition of the real-time runoff detection area, and training the emission execution action of the runoff collection system under each runoff condition; when pollutant leakage occurs, controlling the emission execution action of the runoff collection system based on the runoff condition of the currently leaked pollutant.

Description

Technical Field

[0001] The invention relates to the field of intelligent early warning of bridge deck runoff, and in particular to an intelligent monitoring and early warning method for bridge deck runoff. Background Art

[0002] Refer to the patent application with application number 202110527978.3, which discloses a bridge deck runoff collection and treatment system and a water treatment method, wherein the system includes a main beam and a water treatment device, and a safe parking area is extended outward from the junction of the main beam and the roadbed, and a controller is provided at the safe parking area. A number of drainage holes are opened at the edges of both sides of the main beam, and runoff troughs are provided on both sides of the main beam below the drainage holes. The elevation of the water treatment device is lower than the runoff trough, and the water treatment device is connected to the runoff trough through a drainage pool and an inlet pipe A. The water quality monitoring component is used to monitor the water quality in the drainage pool, and the water quality monitoring component is electrically connected to the controller. In addition, in this patent application, the water quality in the drainage pool is monitored by the water quality monitoring component, and the bridge deck runoff is classified and treated according to the water quality conditions, which can not only avoid increasing the amount of harmful liquid treatment, but also avoid harmful liquids from flowing into surface water bodies and causing water pollution.

[0003] However, it does not take into account factors such as deformation of the bridge deck due to the climatic characteristics of the bridge deck's geographical location or damage to the bridge deck caused by consumption during normal use. In addition, it only considers classifying runoff after monitoring water quality, and cannot promptly know the types of pollutants, nor can it provide a real-time basis for the timely dispatch of the remote monitoring system. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent monitoring and early warning method for bridge deck runoff, which can obtain accurate runoff detection area data based on the real-time road conditions of the bridge deck and the two front and rear buffer zones connected to the bridge deck area, and can determine the types of pollutants in real time. At the same time, when pollutants leak, timely response can be made according to the types of pollutants, the leakage locations of the types of pollutants in the real-time runoff detection area and the real-time meteorological conditions.

[0005] The present invention solves the technical problem and adopts the following technical solution:

[0006] A bridge runoff intelligent monitoring and early warning method comprises the following steps:

[0007] Storing the position information of each bridge deck, and calculating the runoff detection area of ​​each bridge deck based on the stored position information of each bridge deck, wherein the runoff detection area of ​​the bridge deck includes the bridge deck area and two buffer areas in front and behind that are connected to the bridge deck according to the driving direction of the bridge deck area;

[0008] Acquire image information of a bridge deck area and two buffer areas corresponding to the bridge deck area, and respectively assign corresponding point cloud detection points to the bridge deck area and the two buffer areas corresponding to the bridge deck area;

[0009] Adjusting the runoff detection area of ​​the bridge deck based on the point cloud detection points, and using the adjusted runoff detection area of ​​the bridge deck as the real-time runoff detection area;

[0010] Defining accident sampling points of the real-time runoff detection area, and simulating the runoff conditions of the real-time runoff detection area when different types of pollutants leak under various meteorological conditions at each accident sampling point;

[0011] Respectively obtain image information of each simulated runoff situation of the real-time runoff detection area, and train the discharge execution action of the runoff collection system under each runoff situation;

[0012] When a pollutant leak occurs, the type of pollutant, the leak location of the type of pollutant in the real-time runoff detection area and the real-time meteorological conditions are obtained respectively;

[0013] Match the leak location with the nearest accident sampling point and obtain the runoff of the currently leaked pollutants;

[0014] Controlling discharge from a runoff collection system based on the runoff of currently leaking pollutants performs actions.

[0015] As a further preference, image information of the bridge deck area and two buffer areas corresponding to the bridge deck area is obtained by a camera group arranged above the bridge deck, and the camera group is evenly arranged on both sides of the road.

[0016] As a further preference, after the cameras in the camera group collect image information of the bridge deck area and the two buffer areas corresponding to the bridge deck area, the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area are calculated according to the image information, and corresponding point cloud detection points are allocated to the bridge deck area and the two buffer areas corresponding to the bridge deck area according to the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area.

[0017] As a further preferred embodiment, the runoff detection area of ​​the bridge deck is adjusted based on the point cloud detection points, and the adjusted runoff detection area of ​​the bridge deck is used as the real-time runoff detection area, specifically referring to:

[0018] A change threshold of each point cloud detection point is pre-set. When the position change of the point cloud detection point exceeds the corresponding change threshold, the corresponding point cloud detection point is reallocated to the bridge deck area and the two buffer areas corresponding to the bridge deck area, and the size of the two buffer areas is expanded and / or reduced based on the reallocated point cloud detection points.

[0019] As a further preferred embodiment, when defining the accident sampling points in the real-time runoff detection area, the accident rate of the bridge deck in the runoff detection area is pre-counted, and the accident sampling points in each lane of the bridge deck in the real-time runoff detection area are defined in order of the accident rate.

[0020] As a further preference, the meteorological conditions refer to meteorological conditions that can form runoff in the real-time runoff detection area when pollutants leak and can be collected by the runoff collection system.

[0021] As a further preference, when pollutants leak, if the pollutants cannot form runoff in the real-time runoff detection area or cannot be collected by the runoff collection system, the remote monitoring system is notified, and a solution to the leaked pollutants in the real-time runoff detection area is made through the remote monitoring system.

[0022] As a further preferred embodiment, after respectively acquiring the image information of each simulated runoff situation in the real-time runoff detection area, the type of pollutant is determined based on the image information, and the runoff volume collected in the runoff collection system is calculated, and the remote monitoring system is notified.

[0023] As a further preferred embodiment, the training of the discharge execution action of the runoff collection system under various runoff conditions specifically refers to:

[0024] When the remote monitoring system receives the notification, if the pollutants are of the type that do not affect the normal indicators of the water under the bridge after treatment, the remote monitoring system controls the runoff collection system to store the collected runoff in the treatment pool for treatment and discharge. At the same time, the dispatch time for dispatching vehicles to clean the treatment pool is set according to the location of the real-time runoff detection area and the meteorological conditions;

[0025] If the pollutants are of a type that has been treated to affect the normal indicators of water flowing under the bridge, the remote monitoring system controls the runoff collection system to store the collected runoff in the specified reservoir, and calculates the time to dispatch a vehicle to clean the reservoir based on the location of the real-time runoff detection area, the meteorological conditions of the real-time runoff detection area and the volume of runoff stored in the reservoir.

[0026] As a further preference, when the leakage location is matched with the accident sampling point closest to it, if there are multiple accident sampling points with the same distance to the leakage location and closest to it, any one of the accident sampling points closest to it is selected and matched with the leakage location.

[0027] The beneficial effects of the present invention are as follows: firstly, based on the position of the bridge deck, the accurate bridge deck runoff detection area is determined in combination with the bridge deck area and the front and rear buffer areas connected to the bridge deck according to the driving direction of the bridge deck area, and the deformation of the bridge deck or the road surface of the surrounding buffer areas will not affect the subsequent sewage discharge judgment. At the same time, accident sampling points can be defined according to the real-time runoff detection area, and the runoff conditions of the real-time runoff detection area under various meteorological conditions when different types of pollutants are leaked can be simulated in advance at each accident sampling point. At this time, the image information of each runoff condition can be simulated to train the emission execution action of the runoff collection system under each runoff condition. When pollutant leakage occurs, the runoff collection system can be controlled to make accurate emission execution actions in time according to the type of pollutant, the leakage position of the type of pollutant in the real-time runoff detection area and the real-time meteorological conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 The present invention is a flowchart of a method for intelligent monitoring and early warning of bridge runoff in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0030] Example

[0031] The embodiment of the present invention provides a bridge runoff intelligent monitoring and early warning method, the flow chart of which is shown in FIG. Figure 1 , wherein the method comprises the following steps:

[0032] S1. Storing the position information of each bridge deck, and calculating the runoff detection area of ​​each bridge deck based on the stored position information of each bridge deck, wherein the runoff detection area of ​​the bridge deck includes the bridge deck area and two buffer areas in front and behind that are connected to the bridge deck according to the driving direction of the bridge deck area;

[0033] S2. Obtain image information of the bridge deck area and two buffer areas corresponding to the bridge deck area, and respectively assign corresponding point cloud detection points to the bridge deck area and the two buffer areas corresponding to the bridge deck area;

[0034] S3. Adjusting the runoff detection area of ​​the bridge deck based on the point cloud detection points, and using the adjusted runoff detection area of ​​the bridge deck as the real-time runoff detection area;

[0035] S4. Define the accident sampling points of the real-time runoff to be detected area, and simulate the runoff of the real-time runoff of different types of pollutants in the leaked area to be detected under various meteorological conditions at each accident sampling point;

[0036] S5. respectively obtain the image information of each runoff situation of the simulated real-time runoff detection area, and train the discharge execution action of the runoff collection system under each runoff situation;

[0037] S6. When a pollutant leak occurs, the type of pollutant, the leak location of the type of pollutant in the real-time runoff detection area and the real-time meteorological conditions are obtained respectively;

[0038] S7. Match the leakage location with the nearest accident sampling point and obtain the runoff of the currently leaked pollutants;

[0039] S8. Perform an action to control the discharge of the runoff collection system based on the runoff situation of the currently leaked pollutants.

[0040] Here, since the location of the bridge deck may cause the road surface to deform or become damaged due to climate or operational use, when the bridge deck is deformed or damaged, it may affect the runoff collection of the runoff collection system, and may even cause the runoff containing pollutants to flow directly under the bridge, causing pollution. Therefore, in this embodiment, considering the location of the bridge deck and the surrounding terrain, the road surface conditions of the bridge deck area and the road surface conditions of the two front and rear buffer areas connected to the bridge deck in the driving direction of the bridge deck area are calculated in real time, and the bridge deck area and the two front and rear buffer areas connected to the bridge deck in the driving direction of the bridge deck area are combined together as the runoff detection area of ​​the bridge deck. Based on the historical storage data and real-time collected data of the bridge deck position, the real-time runoff detection area can be calculated, which will not cause any impact when the runoff collection system collects runoff later. In addition, if there is indeed an abnormality in the runoff detection area and human participation is required for repair or maintenance, the relevant personnel can also be notified in time to respond.

[0041] In addition, in this embodiment, the accident sampling points of the real-time runoff to be detected area can be defined according to the historical accident data, multiple accident sampling points are set at the location where the accidents are more concentrated, and fewer accident sampling points are set at the location where the accidents are more sparse, and then the runoff conditions of the real-time runoff to be detected area when the different types of pollutants are leaked under various meteorological conditions are simulated at each accident sampling point. During the simulation process, the image information of each simulated runoff condition of the real-time runoff to be detected area is obtained respectively, and the discharge execution action of the runoff collection system under each runoff condition is trained, so that when the accident occurs, timely response can be made according to the specific location of the accident, the surrounding meteorological conditions at that time and the type of pollutant. Finally, when the pollutant leaks, the type of pollutant, the leakage location of the type of pollutant in the real-time runoff to be detected area and the real-time meteorological conditions are obtained respectively, and the leakage location is matched with the accident sampling point closest to it, and the runoff condition of the currently leaked pollutant is obtained. Then, the discharge execution action of the runoff collection system is controlled based on the runoff condition of the currently leaked pollutant. Due to the pre-simulation process, correct discharge execution actions can be made when different locations, different meteorological conditions and different pollutants leak.

[0042] In the above method, image information of the bridge deck area and two buffer areas corresponding to the bridge deck area can be obtained by a camera group arranged above the bridge deck. Generally speaking, the camera group can be evenly arranged on both sides of the road. The high-position cameras used for vehicle information collection can be reused, or corresponding cameras can be installed separately to enable road surface information, vehicle information and pollutant information collection.

[0043] Specifically, after the cameras in the camera group collect image information of the bridge deck area and the two buffer areas corresponding to the bridge deck area, the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area are calculated based on the image information, and corresponding point cloud detection points are allocated to the bridge deck area and the two buffer areas corresponding to the bridge deck area according to the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area. Here, the allocation of point cloud detection points needs to take into account the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area. The bridge deck area is generally relatively fixed, while the two buffer areas corresponding to the bridge deck area will change due to changes in the surrounding road surface.

[0044] It should be pointed out that adjusting the runoff detection area of ​​the bridge deck based on the point cloud detection points and using the adjusted runoff detection area of ​​the bridge deck as the real-time runoff detection area specifically refers to:

[0045] A change threshold of each point cloud detection point is pre-set. When the position change of the point cloud detection point exceeds the corresponding change threshold, the corresponding point cloud detection point is reallocated to the bridge deck area and the two buffer areas corresponding to the bridge deck area, and the size of the two buffer areas is expanded and / or reduced based on the reallocated point cloud detection points.

[0046] Here, the point cloud detection points may change due to the adjustment of the two buffer areas. The point cloud detection points are adjusted only when the two buffer areas change greatly, which is beneficial to the stability of the runoff collection system in the overall method after collecting the runoff.

[0047] In addition, in this embodiment, when defining the accident sampling points of the real-time runoff detection area, the accident rate of the bridge deck in the runoff detection area is pre-counted, and the accident sampling points in each lane of the bridge deck in the real-time runoff detection area are defined in order of the accident rate, that is, more accident sampling points are set at points with high accident occurrence, and fewer accident sampling points are set at points with low accident occurrence, and the accident rate is updated in real time with the passage of time.

[0048] In this embodiment, the meteorological conditions refer to: meteorological conditions that can form runoff in the real-time runoff detection area and can be collected by the runoff collection system when the pollutants leak. When the pollutants leak, if the pollutants cannot form runoff in the real-time runoff detection area or cannot be collected by the runoff collection system, the remote monitoring system is notified, and a solution to the leaked pollutants in the real-time runoff detection area is made through the remote monitoring system. Here, not all pollutant leakage situations need to perform subsequent steps. If runoff is not enough to form, or the surrounding meteorological conditions are not enough to cause pollutants to leak directly into the water under the bridge, rescue can be carried out according to the specific situation.

[0049] In this embodiment, after respectively acquiring the image information of each simulated runoff situation of the real-time runoff detection area, the type of pollutant is determined according to the image information, and the runoff volume collected in the runoff collection system is calculated, and the remote monitoring system is notified. Here, when determining the type of pollutant according to the image, the type of pollutant can be determined based on the relevant signs on the vehicle and the characteristics of the leaked pollutants. When calculating the runoff volume collected in the runoff collection system, if the weather conditions are relatively bad at the time, such as continuous heavy rain, it is necessary to promptly notify the remote monitoring system, and the remote monitoring system promptly notifies relevant personnel for rescue.

[0050] It should be noted that the training of the discharge execution actions of the runoff collection system under various runoff conditions specifically refers to:

[0051] When the remote monitoring system receives the notification, if the pollutants are of the type that do not affect the normal indicators of the water under the bridge after treatment, the remote monitoring system controls the runoff collection system to store the collected runoff in the treatment pool for treatment and discharge. At the same time, the dispatch time for dispatching vehicles to clean the treatment pool is set according to the location of the real-time runoff detection area and the meteorological conditions;

[0052] If the pollutants are of a type that has been treated to affect the normal indicators of water flowing under the bridge, the remote monitoring system controls the runoff collection system to store the collected runoff in the specified reservoir, and calculates the time to dispatch a vehicle to clean the reservoir based on the location of the real-time runoff detection area, the meteorological conditions of the real-time runoff detection area and the volume of runoff stored in the reservoir.

[0053] Here, when the leakage location is matched with the accident sampling point closest to it, if there are multiple accident sampling points with the same distance to the leakage location and closest to it, any one of the accident sampling points closest to it is selected and matched with the leakage location. When selecting the accident sampling points, each accident sampling point can be compared with the leakage location respectively, so as to screen out one or more accident sampling points closest to the leakage location.

Claims

1. A bridge runoff intelligent monitoring and early warning method, characterized in that: The steps include: Storing the position information of each bridge deck, and calculating the runoff detection area of ​​each bridge deck based on the stored position information of each bridge deck, wherein the runoff detection area of ​​the bridge deck includes the bridge deck area and two buffer areas in front and behind that are connected to the bridge deck according to the driving direction of the bridge deck area; Acquire image information of a bridge deck area and two buffer areas corresponding to the bridge deck area, and respectively assign corresponding point cloud detection points to the bridge deck area and the two buffer areas corresponding to the bridge deck area; Adjusting the runoff detection area of ​​the bridge deck based on the point cloud detection points, and using the adjusted runoff detection area of ​​the bridge deck as the real-time runoff detection area; Defining accident sampling points of the real-time runoff detection area, and simulating the runoff conditions of the real-time runoff detection area when different types of pollutants leak under various meteorological conditions at each accident sampling point; Respectively obtain image information of each simulated runoff situation of the real-time runoff detection area, and train the discharge execution action of the runoff collection system under each runoff situation; When a pollutant leak occurs, the type of pollutant, the leak location of the type of pollutant in the real-time runoff detection area and the real-time meteorological conditions are obtained respectively; Match the leak location with the nearest accident sampling point and obtain the runoff of the currently leaked pollutants; Controlling discharge from a runoff collection system based on the runoff of currently leaking pollutants performs actions.

2. The intelligent monitoring and early warning method for bridge runoff according to claim 1 is characterized in that: Image information of the bridge deck area and two buffer areas corresponding to the bridge deck area is obtained through a camera group arranged above the bridge deck, and the camera group is evenly arranged on both sides of the road.

3. The intelligent monitoring and early warning method for bridge runoff according to claim 2 is characterized in that: After the cameras in the camera group collect image information of the bridge deck area and the two buffer areas corresponding to the bridge deck area, the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area are calculated according to the image information, and corresponding point cloud detection points are allocated to the bridge deck area and the two buffer areas corresponding to the bridge deck area according to the size of the bridge deck area and the size of the two buffer areas corresponding to the bridge deck area.

4. The intelligent monitoring and early warning method for bridge runoff according to claim 1 is characterized in that: The adjusting the runoff detection area of ​​the bridge deck based on the point cloud detection points, and using the adjusted runoff detection area of ​​the bridge deck as the real-time runoff detection area, specifically refers to: A change threshold of each point cloud detection point is pre-set. When the position change of the point cloud detection point exceeds the corresponding change threshold, the corresponding point cloud detection point is reallocated to the bridge deck area and the two buffer areas corresponding to the bridge deck area, and the size of the two buffer areas is expanded and / or reduced based on the reallocated point cloud detection points.

5. The intelligent monitoring and early warning method for bridge runoff according to claim 1 is characterized in that: When defining the accident sampling points in the real-time runoff detection area, the accident rate of the bridge deck in the runoff detection area is counted in advance, and the accident sampling points in each lane of the bridge deck in the real-time runoff detection area are defined in order of the accident rate.

6. The intelligent monitoring and early warning method for bridge runoff according to claim 1 is characterized in that: The meteorological conditions refer to meteorological conditions that can form runoff in the real-time runoff detection area when pollutants leak and can be collected by the runoff collection system.

7. The intelligent monitoring and early warning method for bridge runoff according to claim 6 is characterized in that: When pollutants leak, if the pollutants cannot form runoff in the real-time runoff detection area or cannot be collected by the runoff collection system, the remote monitoring system will be notified, and a solution to the leaked pollutants in the real-time runoff detection area will be made through the remote monitoring system.

8. The intelligent monitoring and early warning method for bridge runoff according to claim 1 is characterized in that: After respectively acquiring the image information of each simulated runoff situation in the real-time runoff detection area, the type of pollutant is determined according to the image information, and the runoff volume collected in the runoff collection system is calculated, and the remote monitoring system is notified.

9. The intelligent monitoring and early warning method for bridge runoff according to claim 8 is characterized in that: The training of the discharge execution actions of the runoff collection system under various runoff conditions specifically refers to: When the remote monitoring system receives the notification, if the pollutants are of the type that do not affect the normal indicators of the water under the bridge after treatment, the remote monitoring system controls the runoff collection system to store the collected runoff in the treatment pool for treatment and discharge. At the same time, the dispatch time for dispatching vehicles to clean the treatment pool is set according to the location of the real-time runoff detection area and the meteorological conditions; If the pollutants are of a type that has been treated to affect the normal indicators of water flowing under the bridge, the remote monitoring system controls the runoff collection system to store the collected runoff in the specified reservoir, and calculates the time to dispatch a vehicle to clean the reservoir based on the location of the real-time runoff detection area, the meteorological conditions of the real-time runoff detection area and the volume of runoff stored in the reservoir.

10. The intelligent monitoring and early warning method for bridge runoff according to claim 1 is characterized in that: When the leakage position is matched with the accident sampling point closest to it, if there are multiple accident sampling points with the same distance to the leakage position and closest to it, any one of the accident sampling points closest to it is selected and matched with the leakage position.

Images