Method and device for determining intelligent pressure optimization and control parameters of airport apron oil supply system

Abstract

The invention provides an intelligent pressure optimization and control parameter determination method and device for an airport apron oil supply system, and relates to the technical field of airport apron oil supply system control. The method comprises the following steps: establishing a first target model; the first target model is used for minimizing the energy consumption of the mechanical plateau oil supply system; according to the first target model, the target outlet pressure of the airport apron oil supply system is determined; the target outlet pressure represents the outlet pressure of the airport apron oil supply system corresponding to the minimum energy consumption of the airport apron oil supply system; and according to the target outlet pressure of the airport apron oil supply system, control parameters corresponding to the airport apron oil supply system are determined. According to the method of the embodiment, accurate determination of the control parameters is achieved, energy consumption optimization and outlet pressure optimization of the oil supply system are ensured, and the risks of pipe explosion, leakage and equipment damage are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of apron fuel supply system control, and in particular to a method and device for determining intelligent pressure optimization and control parameters of an apron fuel supply system. Background Art

[0002] In the control process of the apron fuel supply system, the proportional-integral-derivative (PID) parameters are the core content of the control system design. The proportional coefficient, integral time and derivative time of the PID controller need to be determined according to the characteristics of the controlled process.

[0003] In the related art, there is a lack of research on the optimization and adjustment method of the PID parameters of the apron fuel supply system. Therefore, how to accurately tune the PID parameters of the apron fuel supply system and achieve precise control of the apron fuel supply system is a technical problem that technicians in this field need to solve urgently. Summary of the invention

[0004] The present invention provides a method and device for determining the intelligent pressure optimization and control parameters of an apron fuel supply system. The method determines the optimal pipeline pressure value by optimizing the energy consumption of the apron fuel supply system. According to the optimal pipeline pressure value, the control parameters corresponding to the apron fuel supply system are determined, thereby achieving accurate determination of the control parameters, ensuring the optimization of the energy consumption and outlet pressure of the fuel supply system, and reducing the risks of pipe burst, leakage and equipment damage.

[0005] The present invention provides a method for intelligent pressure optimization and control parameter determination of an apron fuel supply system, comprising the following steps.

[0006] Establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; Determine the target outlet pressure of the apron fuel supply system according to the first target model; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; According to the target outlet pressure of the apron fuel supply system, control parameters corresponding to the apron fuel supply system are determined.

[0007] According to a method for determining intelligent pressure optimization and control parameters of an apron fuel supply system provided by the present invention, the first target model is established based on the following formula: in, Indicates the energy consumption of the apron fuel supply system; Indicates the rotation speed; Indicates the outlet pressure of the apron fuel supply system; Indicates the number of pumps started in the apron fuel supply system; Indicates the peak flow rate of the pump in the ramp fuel supply system.

[0008] According to a method for determining intelligent pressure optimization and control parameters of an apron fuel supply system provided by the present invention, determining the target outlet pressure of the apron fuel supply system according to the first target model includes: Based on a genetic algorithm, the first target model is solved to determine a target outlet pressure of the apron fuel supply system.

[0009] According to a method for intelligent pressure optimization and control parameter determination of an apron fuel supply system provided by the present invention, the control parameters corresponding to the apron fuel supply system are determined according to the target outlet pressure of the apron fuel supply system, including: A second target model is established according to the target outlet pressure of the apron fuel supply system; the second target model is used to minimize the difference between the simulation result of the outlet pressure of the apron fuel supply system and the target outlet pressure of the apron fuel supply system; According to the second target model, control parameters corresponding to the apron fuel supply system are determined.

[0010] According to a method for determining intelligent pressure optimization and control parameters of an apron fuel supply system provided by the present invention, the second target model is established based on the following formula: ； Among them, the A difference between a simulation result representing an outlet pressure of an apron fuel supply system and a target outlet pressure of the apron fuel supply system; Simulation results showing the outlet pressure of the apron fuel supply system; Indicates the target outlet pressure of the ramp fuel supply system.

[0011] According to a method for intelligent pressure optimization and control parameter determination of an apron fuel supply system provided by the present invention, the control parameters corresponding to the apron fuel supply system are determined according to the second target model, including: Based on the particle swarm algorithm, the second target model is solved to determine the control parameters corresponding to the apron fuel supply system.

[0012] The present invention also provides a device for intelligent pressure optimization and control parameter determination of an apron fuel supply system, comprising the following modules: Establishing a module for establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; A first determination module is used to determine a target outlet pressure of the apron fuel supply system according to the first target model; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; The second determination module is used to determine the control parameters corresponding to the apron fuel supply system according to the target outlet pressure of the apron fuel supply system.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for determining intelligent pressure optimization and control parameters of an apron fuel supply system as described in any one of the above-mentioned methods is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for determining intelligent pressure optimization and control parameters of an apron fuel supply system as described in any of the above.

[0015] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the intelligent pressure optimization and control parameter determination method of the apron fuel supply system as described in any one of the above.

[0016] The method and device for determining the intelligent pressure optimization and control parameters of the apron fuel supply system provided by the present invention determine the optimal pipeline pressure value by optimizing the energy consumption of the apron fuel supply system; according to the optimal pipeline pressure value, the control parameters corresponding to the apron fuel supply system are determined, thereby achieving accurate determination of the control parameters, ensuring optimization of the energy consumption and outlet pressure of the fuel supply system, and reducing the risks of pipe burst, leakage and equipment damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of the intelligent pressure optimization and control parameter determination method of the apron fuel supply system provided by the present invention.

[0019] Figure 2 It is a schematic diagram showing the power of the centrifugal pump provided by the present invention changing with frequency.

[0020] Figure 3 It is a schematic diagram showing the change of flow rate of the centrifugal pump provided by the present invention with frequency.

[0021] Figure 4 It is a schematic diagram showing the change of outlet pressure of the centrifugal pump provided by the present invention with frequency.

[0022] Figure 5 It is a schematic diagram of a flow chart for determining an optimal pipeline outlet pressure provided by the present invention.

[0023] Figure 6 It is a schematic diagram comparing the measured data and the simulation data of the centrifugal pump outlet flow provided by the present invention.

[0024] Figure 7 It is a schematic diagram comparing the measured data and the simulation data of the outlet pressure of the centrifugal pump provided by the present invention.

[0025] Figure 8 It is a flow chart of determining PID controller parameters based on particle swarm optimization algorithm provided by the present invention.

[0026] Fig. 9 It is a diagram of the iterative process of the centrifugal pump outlet pressure based on PID control provided by the present invention.

[0027] Fig.10 It is a PID control parameter iteration process diagram provided by the present invention.

[0028] Fig.11 It is another flow chart of the method for determining the intelligent pressure optimization and control parameters of the apron fuel supply system provided by the present invention.

[0029] Fig.12 It is a schematic diagram of the intelligent pressure optimization and control parameter determination device of the apron fuel supply system provided by the present invention.

[0030] Fig.13 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Combine the following Figure 1-Figure 13 The invention describes the intelligent pressure optimization and control parameter determination method and device of the apron fuel supply system.

[0033] In order to facilitate a clearer understanding of the technical solutions of the embodiments of the present application, some technical contents related to the embodiments of the present application are first introduced.

[0034] In the pipeline operation and maintenance of the apron fuel supply system, the optimization of the outlet pressure value of the fuel supply pipeline (the inlet pressure value of the apron pipeline network) is crucial. It not only affects the oil transportation efficiency and energy consumption, but also directly relates to the safe operation of the pipeline and equipment. The appropriate pressure value can reduce the flow resistance of the oil in the pipeline and improve the oil transportation efficiency, thereby achieving efficient and fast oil transportation. At the same time, excessive pressure will cause the pipeline and related equipment to bear excessive pressure, increasing the risk of pipe burst, leakage and equipment damage. By reasonably adjusting the pressure value, this situation can be avoided, the wear and failure of the pipeline and equipment can be reduced, and the safety and reliability of the system can be guaranteed. In addition, optimizing the pressure value can effectively reduce the energy consumption and operating costs during the oil transportation process. By reducing unnecessary energy waste, the energy demand and cost expenditure of the entire system are reduced. The stable pressure value also ensures the continuity and reliability of the oil supply, and can provide sufficient oil to the aircraft in a timely and stable manner to meet its refueling needs and maintain the normal operation of the airport.

[0035] That is, in the pipeline operation and maintenance of the apron fuel supply system, the optimization and adjustment of pressure values ​​are a key link. By scientifically and rationally controlling the pressure value in the pipeline, it is possible to ensure that the oil flows efficiently in the pipeline, reduce resistance and energy consumption, and thus improve the efficiency of oil transportation. Appropriate pressure values ​​can also effectively prevent wear and damage to the pipeline caused by excessive pressure, ensure the safe operation of the pipeline and equipment, and extend its service life. At the same time, maintaining a stable pressure value helps to ensure the continuity and reliability of the oil supply and avoid oil supply interruptions caused by abnormal pressure. Through these measures, preventive maintenance of the pipeline system can be achieved, abnormal conditions can be discovered and adjusted in time, potential failures can be prevented, and the efficient, reliable and economical operation of the fuel supply system can be ensured.

[0036] There is a lack of research on the PID optimization and adjustment methods of existing apron fuel supply systems in related fields, and related research is still in the exploratory and starting stages. In CN118399844A "A PID-based motor control method", a PID enhanced control model is used to control the motor speed, and a temperature correction amount is added to the PID enhanced control model to reduce the output of the PID enhanced control model, reduce the motor speed, wait for the temperature to drop, extend the motor life, and improve the stability and reliability of the entire motor automation system, solving the problem that the existing PID control model does not consider the impact of temperature changes on motor performance, resulting in motor performance degradation or damage in high temperature environments. In CN114564052A "Pressure control method and device, electronic equipment, and storage medium for apron fuel supply system", a steady-state computer apron pipe network model is first established and stabilized to obtain the steady-state operating information of the system. Then, based on the steady-state information and the refueling event list, a transient simulation is performed to analyze the changes in flow and pressure over time. Finally, by setting controller parameters and adjusting the pump speed and start-stop operations, the refueling pressure was ensured to be stable within the preset range, which solved the problems of transient hydraulic simulation of the apron pipeline network and automatic control of the refueling pressure, so that the refueling pressure of the apron fuel supply system can be kept stable.

[0037] The traditional PID control-based regulation method only optimizes and regulates the real-time speed of the motor from the perspective of algorithm improvement, but does not consider the correlation between production line equipment. Although this method can improve the performance of a single motor to a certain extent, it ignores the synergy and mutual influence between production line equipment, which may lead to poor operating efficiency of the entire system. In addition, relying solely on the PID control algorithm for regulation cannot dynamically adapt to the changing working conditions and external disturbances in the production process, which can easily lead to unstable regulation effects. The method proposed in "Pressure Control Method and Device, Electronic Equipment, and Storage Medium for Apron Fuel Supply System" establishes a steady-state model of the apron pipeline network, and ensures the pipeline network pressure value during refueling through transient simulation and controller adjustment. This method fails to fully consider the real-time requirements of the system and the optimization of pressure values ​​and PID control parameters.

[0038] Figure 1 It is one of the flow charts of the intelligent pressure optimization and control parameter determination method of the apron fuel supply system provided by the present invention, such as Figure 1 As shown, the method includes the following: Step 101, establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system.

[0039] Specifically, in the embodiment of the present application, the first target model is first established, wherein the first target model is used to minimize the energy consumption of the apron fuel supply system. That is, in the process of optimizing the PID parameters of the apron fuel supply system, the energy consumption of the apron fuel supply system needs to be minimized, thereby achieving energy consumption optimization and precise control of the apron fuel supply system.

[0040] Step 102: Determine the target outlet pressure of the apron fuel supply system according to the first target model; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system.

[0041] Specifically, since the energy consumption of the apron fuel supply system is related to the outlet pressure value of the fuel supply pipeline of the apron fuel supply system, the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system can be determined through the first objective model, and the optimal pipeline pressure value can be obtained. Based on the optimal pipeline pressure value, not only can the energy consumption of the apron fuel supply system be effectively controlled and optimized, but also the risks of pipe burst, leakage and equipment damage can be reduced.

[0042] Step 103: Determine control parameters corresponding to the apron fuel supply system according to the target outlet pressure of the apron fuel supply system.

[0043] Specifically, after determining the target outlet pressure of the apron fuel supply system according to the first target model, the corresponding control parameters of the apron fuel supply system can be further determined. That is, through the corresponding control parameters of the apron fuel supply system, the outlet pressure of the apron fuel supply system is made to be the optimal pipeline pressure value, thereby achieving the effect of controlling and optimizing the energy consumption of the apron fuel supply system and reducing the risks of pipe burst, leakage and equipment damage.

[0044] The method of the above embodiment determines the optimal pipeline pressure value by optimizing the energy consumption of the apron fuel supply system; according to the optimal pipeline pressure value, the control parameters corresponding to the apron fuel supply system are determined, thereby achieving accurate determination of the control parameters, ensuring the optimization of the energy consumption and outlet pressure of the fuel supply system, and reducing the risks of pipe burst, leakage and equipment damage.

[0045] In one embodiment, the first target model is established based on the following formula: in, Indicates the energy consumption of the apron fuel supply system; Indicates the rotation speed; Indicates the outlet pressure of the apron fuel supply system; Indicates the number of pumps started in the apron fuel supply system; Indicates the peak flow rate of the pump in the ramp fuel supply system.

[0046] Specifically, by simulating the power and flow rate of a single centrifugal pump as the frequency of the centrifugal pump changes, it can be seen from Figure 2 that as the frequency of the centrifugal pump increases, the power of the centrifugal pump increases. Comparing Figures 3 and 4, it can be found that the mass flow rate of the centrifugal pump fluid and the centrifugal pump outlet pressure increase as the frequency of the pump increases, and the change trend of the outlet pressure is higher than the outlet flow rate of the pump. Therefore, through the above experiments and simulations, it can be determined that the energy consumption and fuel efficiency of the airport oil depot fuel supply system are most affected by the outlet pressure of the centrifugal pump pipeline, that is, the energy consumption of the airport oil depot fuel supply system is strongly related to the outlet pressure of the apron fuel supply system.

[0047] In addition, there is a phenomenon of energy loss in the oil transportation process, which is mainly concentrated in the friction between the centrifugal pump oil and the pipeline. Optionally, the equipment information of the airport oil depot centrifugal pump is shown in Table 1.

[0048] Table 1

[0049] Therefore, in the process of establishing the first target model, in addition to introducing the outlet pressure value of the apron fuel supply system, it is also necessary to introduce the maximum instantaneous flow rate, number of open units, speed and other parameters of the centrifugal pump. Optionally, the first target model is as follows: (1) in, Indicates the speed after change, r / min; Indicates the number of pump starts; Indicates the actual maximum peak flow rate of the pump, .

[0050] Optionally, the centrifugal pump inlet pressure , the constraints are as follows: According to the similarity law, if the shape of the performance curve of a pump at a certain speed or a certain impeller diameter is known, the similarity law can be used to accurately predict the performance of the same pump at different speeds or impellers of different diameters. Therefore, the pressure output of the centrifugal pump at different speeds can be calculated. The specific formula is as follows: (2) in, For centrifugal pumps at speed Outlet pressure value, MPa.

[0051] Substituting the above formula (2) into formula (1), we can also obtain the first objective model with the minimum energy consumption of the oil supply pipeline system as the optimization goal: .

[0052] That is, in this application, based on the output characteristics of the centrifugal pump in the apron fuel supply system, the outlet pressure of the pipeline is determined as the decision variable, and the minimum energy consumption of the fuel supply system is taken as the optimization goal to establish the first target model.

[0053] The method of the above embodiment determines the factors that affect the energy consumption of the apron fuel supply system, and then establishes a first target model with the minimum energy consumption of the fuel supply pipeline system as the optimization goal. Then, the optimal pipeline pressure value and control parameters of the apron fuel supply system can be determined through the first target model, thereby realizing accurate determination and precise control of the control parameters of the apron fuel supply system.

[0054] In one embodiment, determining the target outlet pressure of the apron fuel supply system according to the first target model includes: Based on the genetic algorithm, the first target model is solved to determine the target outlet pressure of the apron fuel supply system.

[0055] Specifically, in the embodiment of the present application, a genetic evolution algorithm is used to adjust the output flow rate, the number of opened units and the speed of the centrifugal pump by using population variation, crossover and selection to obtain the optimal outlet pressure value. The main process is shown in FIG5 .

[0056] 1) Initialize population-related parameters: Set the maximum instantaneous flow rate, number of open units, and speed of the centrifugal pump as variables and the value range is , , , the number of individuals in the population , maximum number of iterations , crossover probability , mutation probability . Use binary encoding to establish the relationship between variables and binary strings: in is the decimal number corresponding to the binary string, is the minimum value of the variable, is the maximum value of the variable, and then the fitness value of each individual in the population is calculated. The sorting method is used to select the population. First, the fitness values ​​of n=10 individuals are sorted from small to large to obtain the individual positions after sorting. According to the individual positions after sorting, the linear scaling method is used to assign higher fitness values ​​to the top-ranked individuals: in It represents the position number of the 𝑖th individual after sorting, and then calculates the percentage of the fitness value, that is, the proportion of each individual’s fitness value in the total fitness value, for subsequent selection operations.

[0057] According to the sorted population and the calculated fitness value, the roulette wheel selection method is used to perform a selection operation to generate a new generation of individuals.

[0058] The crossover operation is performed on the generated new generation of individuals. By randomly pairing individuals in the population and exchanging binary gene fragments for each pair of individuals at a certain crossover probability, new individuals are generated. The specific process includes extracting individual parameters, randomly pairing, and according to the crossover probability Decide whether to perform crossover, generate crossover points and exchange gene segments, and update and return a new population.

[0059] After the crossover operation is completed, the last step is mutation operation. By traversing each individual in the population and randomly mutating each bit of its binary code, the mutation probability is Change 0 to 1 or 1 to 0 by updating the mutated individuals into the new population.

[0060] Recalculate the fitness value of each individual in the population, perform binary decoding to update the optimal solution, and then calculate the current average fitness value. Or the maximum number of iterations has been exceeded , stop iteration and get the best solution, otherwise continue with selection, crossover and mutation operations.

[0061] Therefore, the optimal individual ,Right now , then the optimal outlet pressure of the pipeline is: The method of the above embodiment, based on a genetic algorithm, determines the optimal outlet pressure value of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system, thereby optimizing the outlet pressure value of the apron fuel supply system, thereby achieving precise control of the energy consumption of the apron fuel supply system and reducing the risks of pipe burst, leakage and equipment damage.

[0062] In one embodiment, according to the target outlet pressure of the apron fuel supply system, the control parameters corresponding to the apron fuel supply system are determined, including: A second target model is established according to the target outlet pressure of the apron fuel supply system; the second target model is used to minimize the difference between the simulation result of the outlet pressure of the apron fuel supply system and the target outlet pressure of the apron fuel supply system; According to the second target model, the control parameters corresponding to the apron fuel supply system are determined.

[0063] Specifically, after determining the target outlet pressure of the apron fuel supply system, the embodiment of the present application takes the minimization of the difference between the simulation result of the outlet pressure of the apron fuel supply system and the target outlet pressure of the apron fuel supply system as the second target model; then, by solving the second target model, the optimal control parameters of the apron fuel supply system can be obtained, thereby achieving accurate determination and precise control of the control parameters of the apron fuel supply system.

[0064] Alternatively, if the first target model is solved based on a genetic algorithm to determine that the target outlet pressure of the apron fuel supply system is 0.78 MPa, then the second target model is: = in, represents the difference between the simulation result of the outlet pressure of the apron fuel supply system and the target outlet pressure of the apron fuel supply system; Simulation results showing the outlet pressure of the apron fuel supply system; Indicates the target outlet pressure of the ramp fuel supply system.

[0065] Optionally, in the embodiment of the present application, based on the mechanism characteristics of the centrifugal pump, a real-time simulation model of the apron oil supply system is constructed to simulate the outlet pressure of its pipeline. Optionally, the real-time simulation model is mainly composed of three parts: a centrifugal pump module, a pipeline loss module, and a state monitoring subsystem.

[0066] The input parameters of the centrifugal pump are the motor control frequency (Hz) and inlet pressure (MPa); the output parameters are outlet pressure (MPa) and flow rate. The centrifugal pump is driven by an electric motor. The pump body and the suction pipe are filled with liquid. The motor drives the impeller to rotate at high speed, and the impeller drives the liquid between the blades to rotate together. Due to the centrifugal force, the liquid is thrown from the center of the impeller to the outer edge of the impeller and flows out along the discharge port at a higher pressure. At the same time, a certain vacuum is formed at the center of the impeller due to the liquid being thrown out, and the pressure at the liquid surface of the inlet storage tank (hot well, water tank, storage tank, etc.) is higher than that at the center of the impeller. Therefore, the liquid in the storage tank enters the pump under the action of the pressure difference. The impeller keeps rotating, and the liquid is continuously sucked in and pressed out.

[0067] By querying the performance curve data of the centrifugal pump, the performance curve can be obtained by fitting, and the hydraulic characteristics modeling of the centrifugal pump can be completed. The centrifugal pump module mainly includes: oil tank, solver, fluid characteristics setting, centrifugal pump, ordinary pipeline module, centrifugal angular velocity source, gain module and variable area hole module in the blockage subsystem. The ordinary pipeline module is used to simulate ordinary pipelines without bending changes. Its diameter and length are derived from the process installation diagram of the oil pump room; the variable area hole module is used to simulate the blockage of the pipeline and control its blockage degree. The type of motor that provides the speed for the centrifugal pump is an asynchronous motor, which controls the shaft speed of the motor by controlling the frequency; the gain module converts the frequency into the shaft speed; the ideal angular velocity source outputs the speed according to the control signal s, and the speed is input to the centrifugal pump module. In order to simulate the energy loss caused by friction between the oil and the pipeline, the pipeline loss module is constructed after the centrifugal pump module, which mainly consists of the pipeline interface module, the ordinary pipeline module, the elbow pipeline module, the constant area hole module, the flow monitoring module, the liquid transmission and the filter. The pipeline interface module is mainly used to simulate the connection between pipelines of different diameters; the elbow pipeline module is mainly used to simulate the elbows in the pipeline system; the ordinary pipeline module is used to simulate ordinary pipelines without bending changes; the constant area hole module is used to control the leakage area. The filter subsystem consists of two parts: the coalescing filter element and the separation filter element subsystem, which correspond to the coalescing filter element and the separation filter in the equipment respectively. The material inside the filter needs to go through four processes of filtration, coalescence, sedimentation, and separation to filter out impurities, remove moisture, alkali solution, and organic acid salts soluble in water. This subsystem is mainly used to monitor the output pressure and flow of the centrifugal pump and simulate real pressure and flow sensors. According to the different installation positions of the actual sensors, insert the modules into different positions of the model.

[0068] In the apron fuel supply system, the parameters of the control variable output are mainly determined by setting the error between the optimal pipeline outlet pressure of the centrifugal pump and the actual outlet pressure, so as to judge whether the entire control system is increasing or decreasing the pressure, and then realize the dynamic adjustment of the motor rotation frequency in the centrifugal pump simulation model.

[0069] Optionally, after using Simulink to build a real-time simulation model of the apron fuel supply system, the simulated outlet flow and outlet pressure can be compared with the measured signal outlet flow and outlet pressure, as shown in Figures 6 and Figure 7 As shown, the accuracy of the simulation results is determined and the simulation model is corrected. Optionally, if the simulation signal is similar to the measured signal in value and has the same basic change trend, it means that the simulation accuracy of the model is high. (The error between the two is: ).

[0070] The method of the above embodiment, after determining the target outlet pressure of the apron fuel supply system, takes the minimization of the difference between the simulation result of the outlet pressure of the apron fuel supply system and the target outlet pressure of the apron fuel supply system as the second target model; then by solving the second target model, the optimal control parameters of the apron fuel supply system can be obtained, thereby realizing the accurate determination and precise control of the control parameters of the apron fuel supply system.

[0071] In one embodiment, according to the second target model, determining the control parameters corresponding to the apron fuel supply system includes: Based on the particle swarm algorithm, the second objective model is solved to determine the control parameters corresponding to the apron fuel supply system.

[0072] Specifically, in the embodiment of the present application, the particle swarm algorithm is used to solve the second target model to obtain the optimal control parameters of the apron fuel supply system, as shown in FIG. Figure 8 As shown: 1) First set the dimension of the particle swarm , the number of particle swarms , acceleration constant , inertia factor , the particle speed is , maximum number of iterations .

[0073] 2) Calculate the fitness value of the particle: compare the calculated result with the individual extreme value and the group extreme value to obtain the optimal solution, which also includes the individual optimal solution. The algorithm formula for simulating the output of the PID controller is: The simulation sampling time , output , e is the discrete error under time scale. Then the pipeline outlet pressure output of the centrifugal pump real-time simulation model is: in, The mapping relationship of the centrifugal pump real-time simulation model is shown in Figure 2. The objective function is the fitness function. For the PID controller, it is a function that measures the performance index of the PID controller. The square deviation integral (ISE) function that can measure the system regulation quality is used: 3) Adjust the speed and position of the particle: The method is to compare the current particle speed with the specified speed range and make adjustments. The same method is used to adjust the particle position. If the particle position exceeds the set maximum range, it is used as the maximum boundary of the particle group; if the particle position does not exceed the set minimum range, it is used as the minimum boundary of the particle group. The particle speed and position can be adjusted by the following formula: 4) Determine whether the algorithm has reached the termination stage: if the update iteration of the particle swarm algorithm has reached the maximum number of times, the operation is stopped and the optimal solution is finally obtained; otherwise, continue to step 2 for iteration.

[0074] The real-time simulation results of the centrifugal pump based on PID control are as follows: Fig. 9 As shown in the figure, when the number of iterations of the particle swarm optimization algorithm exceeds 4, the outlet pressure of the main pipeline of the aviation fuel production line, that is, the simulated output of the pump, stabilizes at 0.78MPa. PID control parameters The iteration results are as follows Fig.10 As shown, the visible parameters As the number of iterations increases, it gradually stabilizes, indicating that the PID control parameter search using the particle swarm algorithm is faster.

[0075] The method of the above embodiment establishes an energy loss model (first target model) based on the characteristics of the centrifugal pump during the oil transportation process, and uses a genetic algorithm to calculate the optimal outlet pressure value; and constructs a centrifugal pump real-time simulation model through simulink to achieve real-time simulation of the actual centrifugal pump equipment and simulate the PID control module of the motor; finally, based on the outlet pressure value obtained by optimization, the error between the optimal pressure value and the pipeline pressure value output by the real-time simulation is used as the optimization target, and the PID control parameters are optimized using the particle swarm algorithm to achieve energy consumption optimization and precise control of the oil depot oil supply system, thereby ensuring the efficiency and safety of pipeline transportation and reducing pipeline transportation energy consumption.

[0076] For example, in the oil depot fuel supply system of a large international airport, the centrifugal pump is responsible for transporting oil from the storage tank to various refueling stations. In order to ensure the stability of the fuel supply and the efficient operation of the system, the centrifugal pump must maintain the best operating state under different working conditions. Traditional control methods are difficult to take into account both system energy consumption and equipment relevance at the same time, resulting in high energy consumption and poor operating efficiency. In response to this demand, an embodiment of the present application provides a method for determining the intelligent pressure optimization and control parameters of an apron fuel supply system, which is applied to the optimization and regulation of the apron fuel supply system. Fig.11 As shown, the specific process is as follows: (1) Based on the output characteristics of the centrifugal pump in the apron fuel supply system, the outlet pressure of the pipeline is determined as the decision variable, that is, the inlet pressure of the apron pipe network, and the minimum energy consumption of the fuel supply system is taken as the optimization goal to establish the first target model. That is, based on the characteristics of the centrifugal pump in the fuel transportation process, an energy loss model is established, and the maximum instantaneous flow rate, number of centrifugal pumps, speed, etc. are taken as constraints. Through the power relationship, the system energy consumption is minimized as the optimization goal.

[0077] (2) Using the genetic evolution algorithm, the output flow rate, number of centrifugal pumps opened, and speed are adjusted by using population mutation, crossover, and selection to obtain the optimal individual and calculate the optimal outlet pressure of the pipeline. In other words, the genetic evolution algorithm is used to calculate the optimal outlet pressure value of the pipeline, that is, the optimal pressure value.

[0078] (3) Based on the mechanism characteristics of the centrifugal pump, a real-time simulation model of the centrifugal pump is constructed to simulate the outlet pressure of its pipeline. The optimal outlet pressure of the oil supply pipeline is used as the optimization target to establish the second target model. Optionally, based on the mechanism characteristics of the centrifugal pump, a high-fidelity real-time simulation model of the centrifugal pump is constructed using Simulink, which significantly improves the real-time control of the centrifugal pump. The simulation model can accurately simulate the operating state of the centrifugal pump under different working conditions, providing a reliable basis for the subsequent optimization of the control strategy. On this basis, the PID controller used for motor frequency control is simulated to control the outlet pressure of the centrifugal pump in real time.

[0079] (4) Construct a PID controller for controlling the motor input of the centrifugal pump, use the particle swarm algorithm to determine the search space of particles, and obtain the optimal parameters of the centrifugal pump PID controller. That is, through the particle swarm algorithm, the PID control parameters are optimized so that the output pressure of the centrifugal pump is always maintained at the optimal pressure value, ensuring the energy consumption optimization and precise control of the oil supply system.

[0080] The method of the above embodiment significantly reduces the energy consumption of the oil supply system and improves the operating efficiency and stability of the centrifugal pump. In addition, this method not only improves the operating efficiency and reduces energy consumption in the oil supply system of the airport oil depot, but also has broad application prospects in the transportation, oil and gas, chemical, water treatment, energy and electricity, intelligent manufacturing and environmental protection industries. By optimizing the operating parameters of the fluid conveying system, the method can improve the overall efficiency of the system, reduce energy consumption, ensure the safe operation of the equipment, and promote its sustainable development, providing strong technical support for the intelligent and efficient operation of various industries.

[0081] The following is a description of the intelligent pressure optimization and control parameter determination device of the apron fuel supply system provided by the present invention. The intelligent pressure optimization and control parameter determination device of the apron fuel supply system described below and the intelligent pressure optimization and control parameter determination method of the apron fuel supply system described above can be referred to each other. Fig.12 As shown, including: Establishing module 1210, for establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; The first determination module 1220 is used to determine the target outlet pressure of the apron fuel supply system according to the first target model; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; The second determination module 1230 is used to determine the control parameters corresponding to the apron fuel supply system according to the target outlet pressure of the apron fuel supply system.

[0082] Fig.13 An example of a physical structure diagram of an electronic device is provided, and the electronic device may include: a processor 1310, a communication interface 1320, a memory 1330, and a communication bus 1340, wherein the processor 1310, the communication interface 1320, and the memory 1330 communicate with each other through the communication bus 1340. The processor 1310 may call the logic instructions in the memory 1330 to execute the intelligent pressure optimization and control parameter determination method of the apron fuel supply system, and the method includes: establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; according to the first target model, determining the target outlet pressure of the apron fuel supply system; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to the energy consumption of the apron fuel supply system being minimized; and determining the control parameters corresponding to the apron fuel supply system according to the target outlet pressure of the apron fuel supply system.

[0083] In addition, the logic instructions in the above-mentioned memory 1330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0084] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the intelligent pressure optimization and control parameter determination method of the apron fuel supply system provided by the above-mentioned methods, and the method includes: establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; according to the first target model, determining the target outlet pressure of the apron fuel supply system; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; according to the target outlet pressure of the apron fuel supply system, determining the control parameters corresponding to the apron fuel supply system.

[0085] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for intelligent pressure optimization and control parameter determination of the apron fuel supply system provided by the above-mentioned methods, the method comprising: establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; according to the first target model, determining the target outlet pressure of the apron fuel supply system; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; according to the target outlet pressure of the apron fuel supply system, determining the control parameters corresponding to the apron fuel supply system.

[0086] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0087] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent pressure optimization and control parameter determination of an apron fuel supply system, characterized in that: include: Establishing a first target model; the first target model is used to minimize the energy consumption of the apron fuel supply system; Determine the target outlet pressure of the apron fuel supply system according to the first target model; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; According to the target outlet pressure of the apron fuel supply system, control parameters corresponding to the apron fuel supply system are determined.

2. The method for intelligent pressure optimization and control parameter determination of the apron fuel supply system according to claim 1 is characterized in that: The first target model is established based on the following formula: in, Indicates the energy consumption of the apron fuel supply system; Indicates the rotation speed; Indicates the outlet pressure of the apron fuel supply system; Indicates the number of pumps started in the apron fuel supply system; Indicates the peak flow rate of the pump in the ramp fuel supply system.

3. The method for intelligent pressure optimization and control parameter determination of the apron fuel supply system according to claim 1 is characterized in that: Determining the target outlet pressure of the apron fuel supply system according to the first target model includes: Based on a genetic algorithm, the first target model is solved to determine a target outlet pressure of the apron fuel supply system.

4. The method for intelligent pressure optimization and control parameter determination of the apron fuel supply system according to any one of claims 1 to 3, characterized in that: Determining the control parameters corresponding to the apron fuel supply system according to the target outlet pressure of the apron fuel supply system includes: A second target model is established according to the target outlet pressure of the apron fuel supply system; the second target model is used to minimize the difference between the simulation result of the outlet pressure of the apron fuel supply system and the target outlet pressure of the apron fuel supply system; According to the second target model, control parameters corresponding to the apron fuel supply system are determined.

5. The method for intelligent pressure optimization and control parameter determination of the apron fuel supply system according to claim 4 is characterized in that: The second target model is established based on the following formula: ； Among them, the A difference between a simulation result representing an outlet pressure of an apron fuel supply system and a target outlet pressure of the apron fuel supply system; Simulation results showing the outlet pressure of the apron fuel supply system; Indicates the target outlet pressure of the ramp fuel supply system.

6. The method for intelligent pressure optimization and control parameter determination of the apron fuel supply system according to claim 5 is characterized in that: Determining the control parameters corresponding to the apron fuel supply system according to the second target model includes: Based on the particle swarm algorithm, the second target model is solved to determine the control parameters corresponding to the apron fuel supply system.

7. An intelligent pressure optimization and control parameter determination device for an apron fuel supply system, characterized in that: include: A building module, used for building a first target model; The first objective model is used to minimize the energy consumption of the apron fuel supply system; A first determination module is used to determine a target outlet pressure of the apron fuel supply system according to the first target model; the target outlet pressure represents the outlet pressure of the apron fuel supply system corresponding to minimizing the energy consumption of the apron fuel supply system; The second determination module is used to determine the control parameters corresponding to the apron fuel supply system according to the target outlet pressure of the apron fuel supply system.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for determining the intelligent pressure optimization and control parameters of the apron fuel supply system according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the intelligent pressure optimization and control parameters of the apron fuel supply system according to any one of claims 1 to 6 is implemented.

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