Intelligent re-pressing method for vacuum tube of super-high-speed maglev train

Abstract

The application discloses an intelligent re-pressurization method for a super-high-speed maglev train vacuum tube, and re-pressurization is divided into two stages. In the first stage, the gas flow state is supercritical flow state, and a negative incremental flow compensation method is mainly used to reduce the impact caused by air inflow and avoid damage of facilities in the tube caused by gas impact. In the second stage, the gas flow state is subcritical flow state, and an incremental flow compensation method is mainly used to compensate for the inflow loss caused by the change of the flow state, thereby improving the re-pressurization efficiency. Compared with a traditional re-pressurization system, the working efficiency can be improved by 22.78%.

Description

Technical Field

[0001] This invention relates to a control system for ultra-high-speed maglev trains, specifically to an intelligent repressurization system for train vacuum pipelines. Background Technology

[0002] When passengers transfer, goods are loaded and unloaded, or the transportation system is under maintenance, the ultra-high-speed low-vacuum pipeline maglev transportation system needs to restore the pressure inside the vacuum pipeline where the train is located from a low-vacuum state to atmospheric pressure. During the repressurization process, the pressure inside the train's pipeline is constantly changing, affecting the numerical changes in gas inflow rate and velocity. If the gas inflow rate and velocity are too high, it will generate a large airflow impact, leading to damage to the facilities inside the pipeline. If the gas inflow rate and velocity are too low, it will reduce the repressurization efficiency. If the repressurization system can compensate for the flow rate based on the real-time status data of the repressurization process, it can reduce airflow impact and improve repressurization efficiency. However, the relationship between gas flow rate, velocity, pipeline pressure, and airflow impact during the repressurization process is quite complex, making it difficult to accurately establish mechanical and control models, and making it difficult for traditional control methods to complete the repressurization work safely, stably, and quickly.

[0003] To solve this technical problem, industry professionals have conducted a lot of research, such as the publicly available technical solutions described below.

[0004] Patent application No. 201610587467X, entitled "Vacuum and Repressurization System for Depressurization and Repressurization Tests of Spacecraft Electronic Equipment":

[0005] The technical solution uses a pneumatic slide gate valve as the opening and closing element of the pressure-reinforcing system. Although the pneumatic slide gate valve has a fast opening and closing response speed under normal circumstances, its operation reliability is not high when there is a large pressure difference between the inside and outside of the pipeline. The opening response speed is not only affected by the ambient temperature, but the valve opening degree is also not adjustable.

[0006] Patent application number 201420339339X, entitled "Vacuum Heat Sink Container Warming and Repressurization System":

[0007] This technical solution uses a vacuum valve for flow control, but the control accuracy fluctuates greatly and cannot be accurately adjusted according to real-time status data. This may result in excessively high inflow gas flow, causing a large airflow impact that could damage the facilities inside the pipeline; or it may result in excessively low inflow gas flow, leading to reduced repressurization efficiency.

[0008] Patent application number 2020109939788, entitled "A Vacuum Decompression and Re-pressure Fatigue Testing System":

[0009] This technical solution uses a flow controller group connected to a pressure regulating valve group, adding a pipeline pressure adjustment component. The combined adjustment of pressure and flow increases the difficulty of pressure repressurization control, and improper adjustment can result in excessively high or low inflow gas flow, which is detrimental to the safety and efficiency of the pressure repressurization process. Furthermore, since the working pressure in many workplaces is uncontrollable and unadjustable, this method is not suitable for such scenarios and is limited to situations where the pressure is adjustable. Summary of the Invention

[0010] The technical problem solved by this invention is to provide an intelligent repressurization system for the vacuum pipeline of ultra-high-speed maglev trains that can ensure both high efficiency and safety in the repressurization process.

[0011] The technical solution adopted in this invention is an intelligent pressure-rebalancing method for vacuum pipelines of ultra-high-speed maglev trains. The required equipment includes an intelligent pressure-rebalancing controller, at least one pressure-rebalancing valve group, and in-pipe equipment sensors. Each pressure-rebalancing valve group includes, from front to back, a filter, an inlet pressure gauge, a valve, an outlet pressure gauge, and a flow meter. The detection signals from the inlet and outlet pressure gauges are transmitted to the intelligent pressure-rebalancing controller. The in-pipe equipment sensors include a flow velocity sensor and a pressure sensor. The detection signals from the flow velocity sensor and the pressure sensor are also transmitted to the intelligent pressure-rebalancing controller.

[0012] During the pressure recovery startup, only one pressure recovery valve group is opened. The pressure outside the pipeline is greater than the pressure inside the pipeline, and gas flows from outside the pipeline into the pipeline. The pressure recovery process is divided into two stages: the first stage is a supercritical flow state, and the second stage is a subcritical flow state. The inlet pressure gauge measures P1 as the inlet pressure, and the outlet pressure gauge measures P2 as the outlet pressure.

[0013] Inlet and outlet pressure ratio β IO The calculation formula is as follows:

[0014]

[0015] The critical air pressure ratio is β air =0.528, when β IO ≤0.528, identified as supercritical flow state, when β IO ≤0.528, identified as subcritical flow state;

[0016] The formula for calculating the gas flow rate in the first stage of the pressure recompression process is as follows:

[0017]

[0018] The formula for calculating the gas flow rate in the second stage of the pressure recompression is as follows:

[0019]

[0020] Where k = 1.4 is the adiabatic coefficient, R = 287.041 J / (kg·K) is the gas constant of air, T1 = 20° = 676 K is the inlet temperature, M = 28.963 g / mol is the molar mass of air, and A is the valve port area;

[0021] In the first stage, the intelligent pressure controller collects data from the main pressure valve group, the main flow meter, and the real-time flow velocity data in the pipeline to ensure that the flow velocity in the pipeline is within a safe range. It also calculates the reasonable gas inflow area using formula (2) and sends a command to the valve to adjust it to a reasonable opening value.

[0022] In the second stage, the gas flowing into the pipe is divided into three main flow states: turbulent flow, viscous flow, and molecular flow, as well as transitional states between turbulent-viscous flow and viscous-molecular flow.

[0023] The molecular current discrimination formula is

[0024] The formula for viscous flow discrimination is:

[0025] The viscous-molecular flow discrimination formula is:

[0026] D is the diameter of the vacuum pipe. This represents the average pressure of the gas.

[0027] The compensation flow rate is calculated using formula (2) for different flow states. The second stage is a complex nonlinear environment. The pressure compensation flow rate is a nonlinear variable. The flow control of the pressure system is completed by using a model-free, self-supervised deep reinforcement learning method through an intelligent pressure controller.

[0028] The beneficial effects of this invention are that the intelligent repressurization system uses a self-supervised deep reinforcement learning algorithm to achieve real-time flow compensation during the repressurization process, thereby reducing the impact of the inflowing gas on the pipeline facilities and improving the efficiency of the repressurization process. It also meets the needs of train maintenance and transfers, achieving vacuum repressurization of train pipelines. Attached Figure Description

[0029] Figure 1 This is a schematic diagram illustrating the principle of the intelligent repressurization system for vacuum pipelines in ultra-high-speed maglev trains according to the present invention.

[0030] The markings in the diagram are as follows: 1-Intelligent pressure controller, 2-Air source, 3-Filter, 5-Main inlet pressure gauge, 6-Main electric vacuum gate valve, 8-Main outlet pressure gauge, 9-Main flow meter, 10-Pipeline, 11-Compensation filter 1, 13-Compensation inlet pressure gauge 1, 14-Compensation electric vacuum gate valve 1, 16-Compensation outlet pressure gauge 1, 17-Compensation flow meter 1; 18-Compensation filter 2, 20-Compensation inlet pressure gauge 2, 21-Compensation electric vacuum gate valve 2, 23-Compensation outlet pressure gauge 2, 24-Compensation flow meter 2. Detailed Implementation

[0031] The intelligent pressure-repressurization method for the vacuum pipeline of the ultra-high-speed maglev train disclosed in this application requires an intelligent pressure-repressurization controller, at least one pressure-repressurization valve assembly, and equipment sensors within the pipeline. Each pressure-repressurization valve assembly, from front to back, includes a filter, an inlet pressure gauge, an electric vacuum gate valve, an outlet pressure gauge, and a flow meter. The detection signals from the inlet and outlet pressure gauges are transmitted to the intelligent pressure-repressurization controller. The equipment sensors within the vacuum pipeline 10 to be pressure-repressurized include a flow velocity sensor and a pressure sensor. The detection signals from the flow velocity sensor and the pressure sensor are also transmitted to the intelligent pressure-repressurization controller. The intelligent pressure-repressurization controller receives the detection signals, performs analysis, calculation, and modeling, and issues commands to adjust the opening degree of the vacuum gate valve.

[0032] like Figure 1 As shown, the system includes one main pressure regulating valve group and two parallel compensating pressure regulating valve groups. The main pressure regulating valve group includes a main filter 3, a main inlet pressure gauge 5, a main electric vacuum gate valve 6, a main outlet pressure gauge 8, and a main flow meter 9. The two compensating pressure regulating valve groups have the same structure as the main pressure regulating valve group. Compensating pressure regulating valve group one includes: compensating filter 11, compensating inlet pressure gauge 13, compensating electric vacuum gate valve 14, compensating outlet pressure gauge 16, and compensating flow meter 17. Compensating pressure regulating valve group two includes: compensating filter 2, compensating inlet pressure gauge 20, compensating electric vacuum gate valve 21, compensating outlet pressure gauge 23, and compensating flow meter 24. The pressure gauges in each pressure regulating valve group are connected to data sensors, which are used to transmit the detected pressure signals to the intelligent pressure regulating controller 1.

[0033] The vacuum pipeline repressurization process is divided into two stages. The first stage is... Supercritical flow state Assuming the gas inflow area remains constant (i.e., the valve opening remains constant), the gas flow rate is constant. However, excessive gas flow rate in this stage can lead to significant airflow impact within the pipeline, causing damage to the pipeline's facilities. In the first stage, the system performs negative flow increment compensation based on real-time status data within pipeline 10. This is achieved by reducing the opening of the main pressure regulating valve assembly to decrease the gas inflow rate, thereby reducing gas impact.

[0034] The second stage is Subcritical flow stateAssuming the gas inflow area remains constant (i.e., the valve opening remains constant), the gas flow rate gradually decreases as the pressure inside the pipeline increases. In the second stage, based on real-time status data within pipeline 10, flow rate increment compensation is performed. This is achieved by opening the compensation pressure-restoring valve assembly to increase the gas inflow area, thereby increasing the gas flow rate. Ultimately, this improves the efficiency of the pressure-restoring process.

[0035] The analysis and modeling of the intelligent pressure controller includes two aspects:

[0036] I. Gas Flow Rate Variation Analysis and Modeling

[0037] When the pressurization system is activated, air flows into the vacuum pipe due to the pressure difference between the inside and outside of the pipe until the pressure difference disappears. The gas flow pattern will change with the inlet-outlet pressure ratio. The inlet-outlet pressure ratio β IO The calculation formula is as follows:

[0038]

[0039] Where P1 represents import pressure and P2 represents export pressure.

[0040] The formula for calculating the gas flow rate of a multi-pressure system is as follows:

[0041] The critical air pressure ratio is β air =0.528, the repressurization process is divided into two stages according to the critical air pressure ratio, and the inlet and outlet pressure ratio β is... IO The case with a pressure ≤0.528 is defined as the first stage of the pressure complex. In this stage, the gas flow state is supercritical, and the gas flow rate of the pressure complex system is constant and unaffected by pressure changes. The inlet / outlet pressure ratio β... IO The case where the value is greater than 0.528 is defined as the second stage, which is the subcritical flow state. In this stage, the gas flow rate of the pressurized system is not a constant value, but rather varies with the pressure ratio β in the pipeline. IO It rises and falls.

[0042] The formula for calculating the gas flow rate in the first stage of the pressure recompression process is as follows:

[0043]

[0044] The formula for calculating the gas flow rate in the second stage of the pressure recompression is as follows:

[0045]

[0046] Where k = 1.4 is the adiabatic coefficient, R = 287.041 J / (kg·K) is the gas constant of air, T1 = 20° = 676 K is the inlet temperature, M = 28.963 g / mol is the molar mass of air, and A is the valve port area.

[0047] II. Gas Pressure Change Analysis and Modeling

[0048] During the repressurization process, the gas flowing into the pipeline exhibits three main flow states: turbulent flow, viscous flow, and molecular flow, as well as transitional states between turbulent-viscous flow and viscous-molecular flow. In the initial stage of the repressurization process, the large pressure difference between the inlet and outlet of the pipeline results in a high gas velocity. At this point, the inertial force of the gas flow causes significant changes in its flow field, leading to an unstable gas flow state. Once the pressure difference between the inlet and outlet decreases to a certain level, the gas flow forms flow layers with different velocities within the pipeline, at which point the gas flow state transitions to viscous flow.

[0049] The flow state discriminants for turbulent flow, viscous flow, and turbulent-viscous flow are given in equations (4), (5), and (6), respectively:

[0050]

[0051]

[0052]

[0053] Where η = Pa·s is the gas internal friction coefficient, and D is the diameter of the vacuum pipe.

[0054] When the mean free path of gas molecules in a pipe approaches the pipe's inner diameter to a certain extent, collisions between gas molecules become extremely rare; at this point, gas molecules only collide with the inner wall of the pipe. The gas in the pipe flows due to the pressure of the gas molecule density gradient. (Mean free path of gas molecules) The calculation formula is as follows:

[0055]

[0056] Where K is the Boltzmann constant, σ is the effective diameter of the gas molecule, P is the average pressure of the gas, and the time period is generally 20ms-50ms.

[0057] The Knudsen molecular flow, viscous flow, and viscous-molecular flow criterion are shown in equations (8), (9), and (10):

[0058]

[0059]

[0060]

[0061] Substitute the molecular mean free path After calculating formula (7), the discriminants for molecular flow, viscous flow, and viscous-molecular flow can be obtained respectively:

[0062]

[0063]

[0064]

[0065] The intelligent pressure regulating controller 1 also controls the opening and closing of the flow compensation valve assembly and its degree of opening based on real-time status data within the pipeline 10, thereby improving the efficiency of pressure regulating operations. The intelligent pressure regulating controller 1 autonomously decides the magnitude of flow compensation based on real-time monitoring data of the pipeline 10 and stores relevant operational data.

[0066] Specific Operating Philosophy Introduction

[0067] When the pressure regulating device is turned on, because the pressure outside the pressure regulating pipeline is greater than the pressure inside the pipeline, the gas will flow from outside the pipeline into the pipeline under the action of the pressure difference, and the pressure inside the pipeline will gradually increase as the pressure regulating process progresses.

[0068] In the first stage of supercritical flow, the main vacuum gate valve 6 is open, and gas flows from the gas source 2 into the main filter 3 for medium filtration, preventing impurities in the medium from flowing into the repressurization system and causing damage to the system devices and pipeline devices. The gas source is atmospheric air. Since the gas flow rate is constant at this time. In order to reduce the impact of gas on the facilities in the pipeline, when the flow velocity signal detected by the equipment sensor in the pipeline is greater than the safe range, the intelligent repressurization controller 1 collects data such as the real-time flow velocity in the various data sensors 4, the main flow meter 9 and the pipeline 10, and calculates the reasonable gas inflow area through formula (2), and sends a command to the vacuum gate valve 6 to adjust to the reasonable opening value. This can reduce the airflow impact generated by the gas flowing into the equipment in the pipeline 10 during the repressurization process and avoid damage to the facilities in the pipeline. However, if the gas flow rate and velocity drop too low, the repressurization efficiency will be greatly reduced. Therefore, the opening of the vacuum gate valve in this stage should be kept as large as possible under the premise of equipment safety. The change of flow velocity is a dynamic process, and signal collection, calculation and adjustment of opening are also a process that is constantly changing and adjusting.

[0069] In the subcritical flow state of the second stage, the gas flow rate decreases as the pressure difference between the inside and outside of the pipeline decreases. To accelerate the repressurization speed, the decrease in gas flow rate can be compensated by increasing the inflow area, i.e., opening the compensation valve group and adjusting its opening. Since the pipeline pressure changes in real time, the increase in gas flow rate should also change with the pipeline pressure. Moreover, the change in pipeline pressure will cause the gas flow state to evolve into four different states: turbulent-viscous flow, viscous flow, viscous-molecular flow, and molecular flow. The intelligent repressurization controller 1 collects the pressure signal in the pipeline 10 in real time and determines which fluid state it belongs to through formulas (11), (12), and (13). The repressurization process in this stage can be regarded as a complex nonlinear environment. The repressurization compensation flow rate is a nonlinear variable, and it is difficult to obtain an accurate variable value through the control model. In other research and application fields, this kind of complex nonlinear problem is suitable for solving using a model-free deep reinforcement learning method. Therefore, this technical solution adopts a self-supervised deep reinforcement learning method to complete the control work of the repressurization system in this stage. Under the premise of equipment safety, the flow rate should be kept as large as possible.

[0070] Summary of Solution Concepts

[0071] This method divides the repressurization process into two stages. In the first stage, the gas flow is in a supercritical state. This stage primarily employs a negative incremental flow compensation method to reduce the impact of air inflow, preventing damage to pipeline facilities caused by gas impact. In the second stage, the gas flow is in a subcritical state. This stage primarily uses an incremental flow compensation method to compensate for the inflow loss caused by the change in flow state, thereby improving the repressurization efficiency. Experimental data demonstrates that the intelligent repressurization system can improve efficiency by 22.78% compared to traditional repressurization systems.

Claims

1. An intelligent re-pressurization method for a super-high-speed maglev train in a vacuum tube, characterized in that: The required equipment includes an intelligent re-compression controller, at least one re-compression valve group and a pipeline equipment sensor; each re-compression valve group comprises, from front to back, a filter, an inlet pressure gauge, a valve, an outlet pressure gauge and a flow meter, and the detection signals of the inlet pressure gauge and the outlet pressure gauge are transmitted to the intelligent re-compression controller; the pipeline equipment sensor comprises an equipment flow rate sensor and an equipment pressure sensor, and the detection signals of the equipment flow rate sensor and the equipment pressure sensor are also transmitted to the intelligent re-compression controller; When the re-compression is started, only one re-compression valve group is opened, the pressure outside the pipeline is greater than the pressure inside the pipeline, and the gas flows from the outside of the pipeline into the pipeline, the re-compression process is divided into two stages, the first stage is a supercritical flow state, and the second stage is a subcritical flow state, P1 measured by the inlet pressure gauge is the inlet pressure, and P2 measured by the outlet pressure gauge is the outlet pressure, Import / export pressure ratio β IO The calculation formula is as follows: Air critical pressure ratio is β air = 0.528, when β IO ≤ 0.528, identified as supercritical flow state, when β IO > 0.528, identified as subcritical flow state; The gas flow rate calculation formula of the first stage of re-compression is as follows: The gas flow rate calculation formula of the second stage of re-compression is as follows: Wherein, k = 1.4 is the adiabatic coefficient, R = 287.041 J / (kg·K) is the gas constant of air, T1 = 20° = 676 K is the inlet temperature, M = 28.963 g / mol is the molar mass of air, and A is the valve port area; In the first stage, the intelligent re-compression controller collects data from the data sensors on the main re-compression valve group, the main flow meter data, and the real-time flow rate data in the pipeline to ensure that the flow rate in the pipeline is within a safe range, and calculates a reasonable gas inflow area through formula (2) and sends an instruction to the valve to adjust to a reasonable opening value; In the second stage, the inflowing gas in the pipeline is divided into three main flow states of turbulent flow, viscous flow and molecular flow, and transition states of turbulent flow-viscous flow and viscous flow-molecular flow; The molecular flow discrimination formula is The viscous flow criterion is The viscous-molecular flow discriminant formula is D is the vacuum pipe diameter, is the average pressure value of the gas; For different flow states, the compensation flow rate is calculated through formula (2), the second stage is a complex nonlinear environment, and the re-compression compensation flow rate is a nonlinear variable, so the intelligent re-compression controller uses a model-free self-supervised deep reinforcement learning method to complete the flow control work of the re-compression system.

2. The intelligent supercharging method for the vacuum tube of the super-speed maglev train according to claim 1, characterized in that: The valve on the re-compression valve group is a vacuum plug valve, and the vacuum plug valve is provided with a feedback signal for closed-loop monitoring of the actual opening of the valve.

3. The intelligent supercharging method for the vacuum tube of the super-high-speed maglev train according to claim 1, characterized in that: The vacuum plug valve is electrically or manually driven.

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