Anti-flooding door early warning opening and closing control method based on particle swarm optimization algorithm
Through the combination of particle swarm optimization algorithm and hydraulic pressure measurement points, the automatic opening and closing control of the anti-flood door is realized, which solves the problems of cumbersome manual operation and safety hazards, and improves the operating efficiency and safety of the anti-flood door.
Patent Information
- Application Number
- CN202411375207.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2025-01-03
AI Technical Summary
The existing manual anti-flood doors are cumbersome and inefficient when closed, pose safety risks, and rely on manpower, and may not be closed in time in an emergency, increasing the risk of flooding.
The early warning opening and closing control method based on the particle swarm optimization algorithm is adopted, and the opening and closing function is established by setting the water pressure measurement point and the particle swarm algorithm, and it is automatically determined whether the anti-flood door needs to be closed, and an automatic opening and closing is achieved through mechanical devices.
It improves the opening and closing efficiency and safety of the anti-flood door, achieves more accurate control, reduces the complexity and safety risks of manual operation, and ensures that the anti-flood door can be closed in time in an emergency.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of flood prevention door opening and closing control methods, and in particular to a flood prevention door early warning opening and closing control method based on a particle swarm optimization algorithm. Background Art
[0002] Subway flood prevention doors are a type of facility used to prevent flooding in subway stations. They are usually installed at the entrance of a subway station or the exit of an underground passage to prevent flooding, heavy rain or other water events from causing flooding inside the subway station.
[0003] The opening and closing of flood-proof doors generally adopts manual flood-proof doors. The steps for manually opening and closing subway flood-proof doors usually include the following aspects: 1. Before operation, ensure the safety of the surrounding environment and confirm that there is no water inflow or other dangerous situations. 2. Prepare tools: According to the design of the flood-proof door, prepare the required tools, such as wrenches, handles, etc. 3. Unlock the flood-proof door: If the flood-proof door has a lock, use a key or unlocking tool to unlock it. 4. Loosen the fixing device: Check the fixing device of the flood-proof door (such as buckles or bolts) and use tools to loosen it so that the door can move freely. 5. Open the door: According to the design of the flood-proof door, gently push or pull the door open, making sure to pay attention to the weight and swing range of the door during operation to avoid accidents. 6. Check the status of the door: Make sure the flood-proof door is fully opened, and check whether the hinges and sealing strips of the door are normal. 7. Close the flood-proof door: When the flood-proof door needs to be closed, pull the door back to the closed position according to the reverse steps, make sure the door is fully closed, and check whether the sealing strip is fitted.
[0004] However, the existing manual flood prevention door has the following problems when closing:
[0005] 1) Complicated and inefficient operation: Manual opening and closing requires manual operation, which may involve multiple steps, increasing the complexity and time consumption of the operation. In an emergency, manual operation may not be completed quickly, resulting in the flood control door failing to close in time, thereby increasing the risk of flooding.
[0006] 2) Safety hazards: In severe weather or sudden floods, operators may face safety risks, and manual operation may increase the possibility of accidents.
[0007] 3) Dependence on manpower: Specialized operators are required to complete the opening and closing actions. Operators must undergo special training to ensure that they can perform manual opening and closing operations correctly and safely. In the case of insufficient manpower or lack of personnel, manual opening and closing may not be carried out smoothly, affecting the effectiveness of the flood control door. Summary of the invention
[0008] The object of the present invention is to provide a flood prevention door early warning opening and closing control method based on a particle swarm optimization algorithm, thereby realizing automatic opening and closing, and achieving more accurate control through a particle swarm optimization algorithm.
[0009] The technical solution adopted by the flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm disclosed in the present invention is:
[0010] 1. A flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm, comprising the following steps:
[0011] The water pressure measurement points set up on site are used as variables;
[0012] Establish the opening and closing function between the water pressure value and the opening and closing threshold, f(x i )=Σq i (x i ), where f(x i )=q i (x i ) is the opening and closing threshold, x i is the measured value of each water pressure measurement point, q i is the water pressure measurement point weight, which is the variable in the particle swarm algorithm;
[0013] Set an opening and closing threshold value f(Q), and set each weight coefficient to the same value Σq i =1, if the opening and closing threshold is greater than the opening and closing threshold value f(x i )≥f(Q), the program determines that the flood control door needs to be closed;
[0014] Each weight coefficient q i As a variable, it is incorporated into the particle swarm algorithm for optimization analysis. The optimized weight coefficient and the water pressure value corresponding to this iteration are substituted into the opening and closing function to determine whether the weight coefficient conforms to the actual flood situation. According to the above optimization results, it is decided whether the weight coefficient should be updated.
[0015] As a preferred solution, the algorithm flow of the particle swarm algorithm is as follows:
[0016] Set the project variables, such as k variables, and set each design variable to: (D-dimensional space), that is, the position and velocity of all particles are
[0017] k design variables as particles Forming the initial particle swarm Calculate the best historical position experienced by each particle i during the current calculation, denoted as pbest i(t); calculate all particles until the current optimal position is found, that is, the global optimal position, denoted as gbest(t);
[0018] The next flight of the particle swarm is t=t+1. The speed and position of the particles are updated according to the following formulas 1 and 2 to obtain the individual optimal solution pbest of the next generation of particle swarms: i (t) and the group optimal solution gbest(t);
[0019] Formula 1: v id (t) = wv id (t-1)+c1γ1[pbest id (t-1)-p id (t-1)]
[0020] +c2γ2[gbest id (t-1)-p id (t-1)]
[0021] Formula 2: p id (t) = p id (t-1)+v id (t);
[0022] Among them, v id (t) is the updated speed of the particle flight in the tth cycle; w is the inertia coefficient; γ1,γ2 is a random number generated in the interval [0,1]; c1,c2 are learning factors; p id (t) is the position of the particle at the tth cycle;
[0023] Determine whether the termination condition of the particle swarm algorithm PSO is met. If it is met, output gbest(t) to stop the algorithm, otherwise go to the above steps to continue iterative calculation.
[0024] As a preferred solution, the above optimization procedure is repeated, and the weight coefficient will be continuously updated and fixed at a certain value. The result reflects the corresponding relationship between each water pressure point and the final flood situation, and further determines whether the subway flood prevention door is opened or closed in the case of a flood, thereby improving the control accuracy.
[0025] As a preferred solution, based on the results obtained by the above-mentioned optimization program, when the program determines that the flood-proof door needs to be closed to cope with the impending flood situation, the matching flood-proof door mechanical opening and closing device will start to close the flood-proof door leaf and lock the corresponding control parts and waterproof strips.
[0026] As a preferred solution, during the layout of water pressure measurement points, in order to prevent the distance between the water pressure measurement point and the flood control door from being too small, resulting in the flood control door being flooded when the water pressure at the measurement point is greater than the limit value, the measurement point is arranged in advance in the flood control door area.
[0027] The beneficial effect of a flood prevention door early warning opening and closing control method based on a particle swarm optimization algorithm disclosed in the present invention is: by setting a water pressure measurement point at the entrance and exit of the corresponding subway or ground passage, using the variables monitored by multiple water pressure measurement points, combining the particle swarm algorithm to establish an opening and closing function, and comparing the value obtained according to the opening and closing function with the set opening and closing valve limit value, so as to judge whether closing is required, achieve the purpose of automatic control, and achieve more accurate control of the opening and closing of the flood prevention door. DETAILED DESCRIPTION
[0028] The present invention will be further elaborated and described below in conjunction with specific embodiments:
[0029] A flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm includes the following steps:
[0030] The water pressure measuring points set up on site are taken as variables. During the layout of the water pressure measuring points, in order to prevent the distance between the water pressure measuring points and the flood control gate from being too small, resulting in the flood control gate being flooded when the water pressure at the measuring point is greater than the limit value, the measuring points are arranged in advance in the flood control gate area.
[0031] Establish the opening and closing function between the water pressure value and the opening and closing threshold, f(x i )=Σq i (x i ), where f(x i )=q i (x i ) is the opening and closing threshold, x i is the measured value of each water pressure measurement point, q i is the water pressure measurement point weight, which is the variable in the particle swarm algorithm;
[0032] Set an opening and closing threshold value f(Q), and set each weight coefficient to the same value Σq i =1, if the opening and closing threshold is greater than the opening and closing threshold value f(x i )≥f(Q), the program determines that the flood control door needs to be closed;
[0033] The algorithm flow of the particle swarm algorithm is as follows:
[0034] Set the project variables, such as k variables, and set each design variable to: (D-dimensional space), that is, the position and velocity of all particles are
[0035] k design variables as particles Forming the initial particle swarm Calculate the best historical position experienced by each particle i during the current calculation, denoted as pbest i(t); calculate all particles until the current optimal position is found, that is, the global optimal position, denoted as gbest(t);
[0036] The next flight of the particle swarm is t=t+1. The speed and position of the particles are updated according to the following formulas 1 and 2 to obtain the individual optimal solution pbest of the next generation of particle swarms: i (t) and the group optimal solution gbest(t);
[0037] Formula 1: v id (t) = wv id (t-1)+c1γ1[pbest id (t-1)-p id (t-1)]
[0038] +c2γ2[gbest id (t-1)-p id (t-1)]
[0039] Formula 2: p id (t) = p id (t-1)+v id (t);
[0040] Among them, v id (t) is the updated speed of the particle flight in the tth cycle; w is the inertia coefficient; γ1,γ2 is a random number generated in the interval [0,1]; c1,c2 are learning factors; p id (t) is the position of the particle at the tth cycle;
[0041] Determine whether the termination condition of the particle swarm algorithm PSO is met. If it is met, output gbest(t) to stop the algorithm, otherwise go to the above steps to continue iterative calculation.
[0042] Each weight coefficient q i As a variable, it is incorporated into the particle swarm algorithm for optimization analysis. The optimized weight coefficient and the water pressure value corresponding to this iteration are substituted into the opening and closing function to determine whether the weight coefficient conforms to the actual flood situation. According to the above optimization results, it is decided whether the weight coefficient should be updated.
[0043] By repeating the above optimization procedure, the weight coefficient will be continuously updated and fixed at a certain value. The result reflects the corresponding relationship between each water pressure point and the final flood situation, and further determines whether the subway flood prevention door is opened or closed in the case of a flood, thereby improving the control accuracy.
[0044] Based on the results obtained from the above optimization program, when the program determines that the flood-proof door needs to be closed to cope with the impending flood situation, the matching flood-proof door mechanical opening and closing device will start to close the flood-proof door leaf and lock the corresponding control parts and waterproof strips.
[0045] The above arrangement will also result in the situation that the measurement points and the flood conditions of the flood control gate cannot be accurately corresponded. Therefore, the particle swarm intelligent optimization algorithm is introduced into the flood control gate early warning opening and closing judgment program. According to the water pressure measurement values at different points, combined with the functional relationship between the water pressure value and the opening and closing threshold, the particle swarm intelligent optimization algorithm is used to continuously update the test point weights. With the increase of local water pressure historical data and the continuous iteration of the algorithm, the test weights of each point will be fixed to a value suitable for the local project. Finally, the weight obtained by the particle swarm algorithm determines the functional relationship between the water pressure value at each point and the opening and closing threshold, and the opening and closing of the flood control door can be controlled according to the above function.
[0046] The present invention provides a flood prevention door early warning opening and closing control method based on a particle swarm optimization algorithm. By setting a water pressure measurement point at the entrance and exit of a corresponding subway or ground passage, using the variables monitored by multiple water pressure measurement points, and combining the particle swarm algorithm to establish an opening and closing function, the value obtained according to the opening and closing function is compared with the set opening and closing valve limit value, so as to judge whether closing is required, realize the purpose of automatic control, and realize more accurate control of the opening and closing of the flood prevention door.
[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.
Claims
1. A flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm, characterized in that: The following steps are involved: The water pressure measurement points set up on site are used as variables; Establish the opening and closing function between the water pressure value and the opening and closing threshold, f(x i )=Σq i (x i ), where f(x i )=q i (x i ) is the opening and closing threshold, x i is the measured value of each water pressure measurement point, q i is the water pressure measurement point weight, which is the variable in the particle swarm algorithm; Set an opening and closing threshold value f(Q), and set each weight coefficient to the same value Σq i =1, if the opening and closing threshold is greater than the opening and closing threshold value f(x i )≥f(Q), the program determines that the flood control door needs to be closed; Each weight coefficient q i As a variable, it is incorporated into the particle swarm algorithm for optimization analysis. The optimized weight coefficient and the water pressure value corresponding to this iteration are substituted into the opening and closing function to determine whether the weight coefficient conforms to the actual flood situation. According to the above optimization results, it is decided whether the weight coefficient should be updated.
2. A flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm as claimed in claim 1, characterized in that: The algorithm flow of the particle swarm algorithm is as follows: Set the project variables, such as k variables, and set each design variable to: (D-dimensional space), that is, the position and velocity of all particles are k design variables as particles Forming the initial particle swarm Calculate the best historical position experienced by each particle i during the current calculation, denoted as pbest i (t); calculate all particles until the current optimal position is found, that is, the global optimal position, denoted as gbest(t); The next flight of the particle swarm is t=t+1. The speed and position of the particles are updated according to the following formulas 1 and 2 to obtain the individual optimal solution pbest of the next generation of particle swarms: i (t) and the group optimal solution gbest(t); Formula 1: v id (t) = wv id (t-1)+c1γ1[pbest id (t-1)-p id (t-1)] +c2γ2[gbest id (t-1)-p id (t-1)] Formula 2: p id (t) = p id (t-1)+v id (t); Among them, v id (t) is the updated speed of the particle flight in the tth cycle; w is the inertia coefficient; γ1,γ2 is a random number generated in the interval [0,1]; c1,c2 are learning factors; p id (t) is the position of the particle at the tth cycle; Determine whether the termination condition of the particle swarm algorithm PSO is met. If it is met, output gbest(t) to stop the algorithm, otherwise go to the above steps to continue iterative calculation.
3. A flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm as claimed in claim 2, characterized in that: By repeating the above optimization procedure, the weight coefficient will be continuously updated and fixed at a certain value. The result reflects the corresponding relationship between each water pressure point and the final flood situation, and further determines whether the subway flood prevention door is opened or closed in the case of a flood, thereby improving the control accuracy.
4. A flood prevention door early warning opening and closing control method based on particle swarm optimization algorithm as claimed in claim 3, characterized in that: Based on the results obtained from the above optimization program, when the program determines that the flood-proof door needs to be closed to cope with the impending flood situation, the matching flood-proof door mechanical opening and closing device will start to close the flood-proof door leaf and lock the corresponding control parts and waterproof strips.
5. The method for controlling flood prevention door opening and closing based on particle swarm optimization algorithm according to claim 1, characterized in that: During the layout of water pressure measurement points, in order to prevent the distance between the water pressure measurement point and the flood control gate from being too small, resulting in the flood control gate being flooded when the water pressure at the measurement point is greater than the limit value, the measurement point is arranged in advance in the flood control gate area.