System for monitoring and controlling running attitude of maglev train in tunnel scene

Abstract

The invention discloses a maglev train operation attitude monitoring control system used in a tunnel scene, and the system comprises a sensor network which comprises an acousto-optic distance measuring sensor disposed on a tunnel variable cross-section wall and an inertial sensor disposed on a maglev train body, the data acquisition module is used for acquiring vehicle body transverse deflection data representing vehicle body transverse swinging and transverse deflection; the monitoring center is used for receiving the vehicle body transverse deflection data and comparing and analyzing the vehicle body transverse deflection data with a preset threshold value to obtain a vehicle body transverse deflection analysis result; and the control center receives the analysis result and adjusts the running speed and / or the power supply mode of the train based on the analysis result, so that the train recovers a stable posture. The acousto-optic distance measuring sensor, the inertial sensor and other sensors are arranged on the inner wall of the tunnel, the vehicle body and other positions, and the reliability, accuracy and environmental adaptability of monitoring are improved through a redundancy mechanism. And compared with a traditional mechanical adjustment method, the method for adjusting the running speed and / or the power supply mode of the maglev train has higher response speed and regulation and control precision.

Description

Technical Field

[0001] The present application relates to the technical field of aerodynamics in maglev train tunnels, and more specifically, to a maglev train running posture monitoring and control system for use in tunnel scenarios. Background Art

[0002] Since the maglev tunnel is relatively small in obstruction, when the maglev train runs at high speed in the tunnel, it is affected by the alternating aerodynamic load in the tunnel, and the car body often swings left and right. Especially when passing through the tunnel entrance, civil air defense door, intermediate air shaft, and cross wiring at the end of the station, the pressure wave will surge and fluctuate violently, leading to a series of aerodynamic problems. Since the maglev train adopts trackless contact technology, the lateral swing and dynamic displacement process of the train are more obvious under the action of violently fluctuating pressure waves. This aerodynamic effect will make the passengers in the car feel obvious discomfort of outward or inward inclination, and in severe cases, it may even endanger driving safety.

[0003] Patent CN101580071A discloses a railway locomotive vehicle running posture measurement system, which uses a high-speed camera to collect image sequences of the vehicle body and rails, and determines the displacement of the vehicle body by comparing the image sequences.

[0004] Patent CN115506836A discloses a system and method for measuring the relative displacement between a rail vehicle and a rail. The system uses a permanent magnet and a magnetoresistive sensor to achieve non-contact measurement of the displacement relationship between the vehicle body and the rail.

[0005] The above patent uses machine vision technology to measure the offset of rail trains, but its application scope is limited to rail railway systems. In addition, in the environment of insufficient light in the tunnel, the acquisition effect of the camera will be significantly affected, resulting in inaccurate measurement of the train offset. Moreover, its function is only to collect the offset data of the vehicle body, and no strategy is provided to restore the vehicle body to a stable state.

[0006] In order to reduce wheel-rail wear, maglev trains use trackless contact technology. However, due to the increase in running speed, the electromagnetic force of the front guide electromagnet will be significantly reduced due to the eddy current effect, which will affect its guiding performance. Although the maglev train body can restore stability through the combined action of the suspension frame and air spring, the drastic pressure fluctuations caused by the high-speed passage of the tunnel cross-section mutation area will still cause the body to have a large lateral swing and lateral deflection, affecting the riding comfort of passengers. Therefore, there is an urgent need for a monitoring and control system that can monitor the running posture of the train and quickly restore the train to stability. Summary of the invention

[0007] In response to at least one defect or improvement need in the prior art, the present application provides a maglev train running posture monitoring and control system for use in a tunnel scenario, which is used to achieve high-precision, high-reliability and high-environmental-adaptability monitoring and control of the maglev train running posture in a tunnel scenario, so that the train can quickly recover to a stable posture when it is unstable.

[0008] To achieve the above objectives, in a first aspect, the present application provides a maglev train running posture monitoring and control system for use in a tunnel scenario, comprising:

[0009] The sensor network includes an acoustic-optical distance measuring sensor arranged on the wall of the tunnel where the cross-section changes and an inertial sensor arranged on the body of the maglev train, which is used to obtain the body lateral swing data representing the lateral swing and lateral deflection of the body when the maglev train passes through the tunnel where the cross-section changes; the acoustic-optical distance measuring sensor includes a laser distance measuring sensor and an ultrasonic distance measuring sensor;

[0010] A monitoring center is used to receive the vehicle body lateral deflection data and compare and analyze it with a preset threshold value to obtain a vehicle body lateral deflection analysis result;

[0011] The control center is used to receive the analysis result of the lateral deflection of the vehicle body and adjust the running speed and / or power supply mode of the maglev train based on the analysis result to restore the train to a stable posture.

[0012] Further, the preset threshold value includes: vehicle body lateral yaw data representing the maximum allowable large-amplitude yaw posture, and vehicle body lateral yaw data representing the maximum allowable small-amplitude yaw posture;

[0013] The maximum allowable large amplitude yaw posture represents a critical state in which the probability of the maglev train overturning exceeds a preset probability threshold when the yaw amplitude of the posture exceeds the large amplitude critical state;

[0014] The maximum allowable small amplitude yaw posture represents that when the maglev train exceeds the small amplitude critical state attitude yaw amplitude, it just changes from not having to adjust the maglev train running speed and / or power supply mode to the critical state where the maglev train running speed and / or power supply mode needs to be adjusted.

[0015] Furthermore, the logic for making adjustments based on the analysis results includes:

[0016] If x0<x min , then the control center does not need to adjust the running speed and / or power supply mode of the maglev train;

[0017] If x min <x0<x max , the monitoring center sends out an early warning signal, and the control center adjusts the running speed and / or power supply mode of the maglev train to restore the train to a stable state;

[0018] If x0>x max , the monitoring center sends out an emergency warning signal, and the control center controls the emergency braking of the maglev train;

[0019] Wherein, x0 represents the vehicle lateral deflection data acquired in real time by the sensor network; x min Indicates the lateral yaw data of the vehicle body when the maximum allowable small yaw posture is present; x max It represents the lateral yaw data of the vehicle body when it represents the maximum allowable large yaw posture.

[0020] Furthermore, the laser distance measuring sensor and the ultrasonic distance measuring sensor are arranged on the wall of the tunnel where the cross section is changed at the same horizontal plane, and are both used to measure the distance between the maglev train body and the inner wall of the tunnel.

[0021] Further, the inertial sensor includes: a gyroscope sensor and / or an acceleration sensor;

[0022] The gyro sensor is arranged within a preset distance range near the center of gravity of the maglev train body, and is used to measure the angular velocity of the body to obtain the inclination angle of the body;

[0023] The acceleration sensor is arranged on the surface of the maglev train body and is used to measure the lateral acceleration of the body.

[0024] Furthermore, the sensor network also includes a magnetic sensor arranged on the guide track of the maglev train at the tunnel cross-section change location, for measuring the suspension height of the maglev train.

[0025] Furthermore, the sensor network also includes a pressure sensor arranged on the wall at the variable cross-section of the tunnel, for measuring the air pressure in the tunnel.

[0026] Furthermore, the control center is also used to continuously optimize the control instructions through machine learning according to the adjustment measures of the maglev train each time it passes through the tunnel with variable cross-section, automatically adjust the operating speed and / or power supply mode of the maglev train, and finally reach the best control strategy to enable the maglev train to pass through the tunnel with variable cross-section in a stable posture.

[0027] Further, adjusting the power supply mode to restore the train to a stable posture includes:

[0028] When the maglev train passes through the tunnel with variable cross-section, different currents are applied on both sides of the maglev train guide track, so that the suspension frames on both sides of the maglev train are subjected to different suspension forces, thereby balancing the centrifugal force generated by the car body, reducing lateral swing and lateral deflection, and allowing the train to restore a stable posture.

[0029] In a second aspect, the present application provides a maglev train running posture monitoring and control system for use in a tunnel scenario, comprising:

[0030] The sensor network includes an acoustic-optical distance measuring sensor arranged on a wall at a preset position of a tunnel curve section and an inertial sensor arranged on a maglev train body, for obtaining body lateral sway data representing lateral swing and lateral deflection of the body when the maglev train passes through the preset position of the tunnel curve section; the acoustic-optical distance measuring sensor includes a laser distance measuring sensor and an ultrasonic distance measuring sensor;

[0031] A monitoring center is used to receive the vehicle body lateral deflection data and compare and analyze it with a preset threshold value to obtain a vehicle body lateral deflection analysis result;

[0032] The control center is used to receive the analysis result of the lateral deflection of the vehicle body and adjust the running speed and / or power supply mode of the maglev train based on the analysis result to restore the train to a stable posture.

[0033] In general, the above technical solutions conceived by the present application can achieve the following beneficial effects compared with the prior art:

[0034] (1) The system of the present application is equipped with various sensors such as acoustic and optical ranging sensors and inertial sensors at multiple locations such as the inner wall of the tunnel and the car body, so as to realize comprehensive monitoring of the running posture of the maglev train. Compared with the traditional single sensor monitoring technology, the system can provide more accurate and redundant data, and improve the reliability, accuracy and environmental adaptability of monitoring through the redundancy mechanism. And the running posture control method of adjusting the running speed and / or power supply mode of the maglev train has a higher response speed and control accuracy than the traditional mechanical adjustment method. The present application is particularly suitable for situations where there is insufficient light and complex environment in the tunnel. Compared with the system that relies on optical monitoring, the present application can work stably under various environmental conditions by combining multiple sensors, thereby ensuring the accuracy of the monitoring data and the reliability of the system.

[0035] (2) The system of the present application uses machine learning algorithms to continuously improve and optimize control instructions, and can automatically adjust the power supply plan and operation strategy based on the monitoring data of each variable cross-section area, gradually achieving the best control effect. Compared with traditional static control methods, machine learning optimization enables the system to adapt to changes, thereby improving operating efficiency and passenger comfort.

[0036] (3) The system of the present application has a real-time warning function. When a large lateral swing or deflection of the vehicle body is detected, a warning signal can be sent in time, and emergency braking can be performed when necessary. Compared with the traditional post-processing method, the system can intervene in the early stage of the problem, significantly improving the safety of tunnel operation.

[0037] (4) The system of the present application can not only be used to monitor the impact of tunnel aerodynamics on the vehicle's running posture, but can also be extended to monitor the impact of tunnel line changes (for example, curved sections) on the vehicle's running posture, and has a wide range of application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 A core structure diagram of a maglev train running posture monitoring and control system for a tunnel scenario provided in an embodiment of the present application;

[0040] Figure 2 A schematic diagram of the operation of a maglev train passing through a tunnel with a variable cross-section provided in an embodiment of the present application;

[0041] Figure 3 A schematic diagram of the structure of a tunnel variable cross-section monitoring and control system provided in an embodiment of the present application;

[0042] Figure 4 A schematic diagram of the structure of a magnetic levitation vehicle monitoring and control system provided in an embodiment of the present application;

[0043] Figure 5 A schematic diagram of the installation of a tunnel variable cross-section sensor provided in an embodiment of the present application;

[0044] Figure 6 A schematic diagram of vehicle displacement monitoring provided in an embodiment of the present application;

[0045] Figure 7 This is a schematic diagram of the installation of the vehicle body sensor provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as they do not conflict with each other.

[0047] The terms "including" or "having" and any variations thereof in the specification, claims or drawings of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0048] As described in the background technology section of the specification, existing monitoring methods using machine vision technology can measure the offset of rail trains, but their application scope is limited to rail railway systems, and in the low-light environment of tunnels, the acquisition effect of the camera will be significantly affected, resulting in inaccurate measurement of the train offset. And its function is only to collect the offset data of the vehicle body, and no strategy is provided to restore the vehicle body to a stable state. In view of this, the present application proposes a maglev train running posture monitoring and control system for use in tunnel scenarios, which is used to achieve high-precision, high-reliability and high environmental adaptability monitoring and control of the running posture of maglev trains in tunnel scenarios, so that the train can quickly return to a stable posture when unstable.

[0049] refer to Figure 1 and Figure 2 An embodiment of the present application provides a maglev train running posture monitoring and control system for a tunnel scenario, which mainly includes a sensor network, a monitoring center and a control center.

[0050] The sensor network includes an acoustic and optical distance measuring sensor installed on the wall of the tunnel where the cross-section changes (the location where the inner diameter of the tunnel suddenly changes greatly) and an inertial sensor installed on the body of the maglev train, which is used to obtain the body lateral swing data representing the lateral swing and lateral deflection of the body when the maglev train passes through the tunnel where the cross-section changes. Figure 3 and Figure 4 The sensor network installed at the tunnel cross-section change is mainly used to monitor the vehicle body running posture at the tunnel cross-section change, while the sensor network installed on the maglev train body is mainly used to monitor the vehicle body running posture in the entire tunnel. The two types of sensor networks installed at different locations can be used independently without interfering with each other and can be installed according to needs.

[0051] Since the blockage ratios of the tunnel's variable cross-section areas are inconsistent, the pressure waves generated by the train passing through the tunnel's variable cross-section areas are different in size, and the degree of influence on the vehicle's running posture is also different. Therefore, this system is required to monitor the displacement of the train in different areas, and take the best measures between train deceleration and power supply changes in combination with train operation requirements and line power supply conditions to ensure the smooth operation of the train to the greatest extent.

[0052] The acoustic and optical distance measuring sensors include laser distance measuring sensors and ultrasonic distance measuring sensors, both of which are installed on the wall at the tunnel cross-section variable location and are used to measure the distance between the maglev train body and the inner wall of the tunnel.

[0053] The inertial sensor includes a gyroscope sensor and / or an acceleration sensor. The gyroscope sensor is arranged within a preset distance range near the center of gravity of the maglev train body to measure the angular velocity of the body to obtain the inclination angle of the body; the acceleration sensor is arranged on the surface of the maglev train body to measure the lateral acceleration of the body.

[0054] Preferably, the sensor network installed at the tunnel cross-section variable location may also include a magnetic sensor disposed on a guide track of the maglev train at the tunnel cross-section variable location, for measuring the suspension height of the maglev train.

[0055] The track of the maglev train (maglev train guide track) is not a traditional railroad, but a special track that uses magnetic force to suspend and guide. Specifically, the track of the maglev train includes a superconducting magnet installed at the bottom of the train car and a closed rectangular aluminum ring buried on the road track. When the train is moving, the superconducting magnet moves relative to the aluminum ring and induces a strong current in the aluminum ring, forming an extremely strong magnetic field. This magnetic field is in the opposite direction to the magnetic field generated by the superconducting magnet on the train, thereby generating a repulsive force that causes the train to suspend above the track.

[0056] Preferably, the sensor network installed at the tunnel cross-section variable location may also include a pressure sensor arranged on the wall at the tunnel cross-section variable location for measuring the air pressure in the tunnel.

[0057] The vehicle body running posture monitoring sensor needs to coordinate the collected data and combine the data collected by multiple sensors for comprehensive analysis and decision-making. This approach is to avoid over-reliance on a single sensor, thereby avoiding wrong decisions that may be caused by distorted data from a single sensor, and thus ensuring that the normal operation of the train is not affected.

[0058] There are not only variable cross-section areas in the maglev tunnel, but also curved sections. When the train passes through the curved section at high speed, the car body will generate centrifugal force, causing the car body to deflect laterally, which will also make the passengers in the car feel obvious discomfort of inclination or inclination, and may even endanger driving safety in severe cases. Therefore, preferably, the system of an embodiment of the present application can not only be used to monitor the influence of tunnel aerodynamics on the running posture of the car body, but also can be extended to monitor the influence of tunnel line changes (for example: curved sections) on the running posture of the car body, and has a wider range of application scenarios. When monitoring the influence of the curved section on the running posture of the car body, it is only necessary to change the sensor network originally set at the variable cross-section of the tunnel to be set on the wall at the preset cross-section position of the curved section of the tunnel or on the guide track of the maglev train. The system architecture design of other parts is similar to the system for monitoring the influence of the variable cross-section of the tunnel on the running posture of the car body, which will not be repeated here.

[0059] After the monitoring and control system collects relevant data through the data acquisition systems of various sensors, it can use the optical fiber communication network to transmit the collected data back to the ground distributed control system on the ground, thereby realizing real-time vehicle operation posture monitoring and control.

[0060] The ground distributed control system is divided into a control center and a monitoring center. The former is responsible for controlling the vehicle's running posture, and the latter is responsible for processing the collected data.

[0061] The monitoring center is used to receive the vehicle body lateral deflection data obtained by the sensor network and compare and analyze it with the preset threshold to obtain the vehicle body lateral deflection analysis results.

[0062] Specifically, the monitoring center is used to analyze, process and store the data collected by the data acquisition system, and transmit the relevant data to the control center based on the analysis results. When the sensor detects that the train has a large lateral swing and lateral deflection, it will send an early warning signal to the control center. The signals processed by the monitoring center are used by the control center to control the on-board transportation control system and traction power supply system.

[0063] The control center is used to receive the vehicle body lateral deflection analysis results obtained by the monitoring center, and adjust the running speed and / or power supply mode of the maglev train based on the analysis results to restore the train to a stable posture.

[0064] Specifically, the onboard operation control system of the control center controls the running speed of the train based on the control signal to achieve the purpose of reducing pressure fluctuations. The traction power supply system formulates a power supply plan for the train when passing through a variable cross-section, so that when the train passes through a variable cross-section, different currents are applied to the tracks on both sides, so that the suspension frames on both sides of the train are subjected to different magnetic attraction (suspension force), thereby balancing the centrifugal force generated by the car body and reducing lateral swing and lateral deflection (that is, a larger current is provided on the side with a larger displacement of the train, thereby generating a larger magnetic attraction, thereby attracting the suspension frame back to the normal position).

[0065] Preferably, when the onboard operation control and traction power supply system of the maglev train sends a control signal, the received signal will be continuously trained through machine learning, and finally the best control method will be formed. The system of the present application uses a machine learning algorithm to continuously improve and optimize the control instructions, and can automatically adjust the power supply plan and operation strategy according to the monitoring data of each tunnel cross-section area, and gradually achieve the best control effect. Compared with the traditional static control method, machine learning optimization enables the system to adapt to changes, thereby improving operating efficiency and passenger comfort.

[0066] In some embodiments, the monitoring and control system can integrate the vehicle-mounted communication equipment with the vehicle-mounted operation control system, the ground communication equipment with the control center server, to ensure seamless cooperation between the components. And because the time for the train to pass through the tunnel with a variable cross-section is short, the signal transmission speed between the components is required to be fast and without delay.

[0067] Each component of the monitoring and control system is powered by a power supply circuit, communicates through a communication circuit, and is connected to a data acquisition system for real-time data acquisition.

[0068] The monitoring and control system needs to deploy a fiber optic communication network inside the tunnel. The fiber optic communication network can be used in scenarios where the signal is weak or the interference is large in the tunnel. The collected data can be transmitted back to the monitoring center on the ground for data storage, data analysis, and signal warning.

[0069] The monitoring and control system can monitor the lateral posture of the maglev train in real time when it is running in the variable cross-section area of ​​the tunnel, and feedback position information through various redundant sensors to ensure that the train adjusts its speed before entering the variable cross-section area to reduce the impact of pressure fluctuations.

[0070] The logic of adjustment based on the analysis result is described in detail below with reference to a specific embodiment.

[0071] Laser displacement sensors (laser ranging sensors) are used to accurately measure the distance changes between the vehicle body and the tunnel wall, and monitor the lateral displacement and rolling posture of the vehicle body. Figure 5As shown in the figure, the laser displacement sensor can be arranged at a height of about 4 / 5 between the tunnel and the car body, and at least two groups of measuring points should be arranged along the axial direction of the tunnel. When the train passes through the variable cross-section area, at any time, the measured distance between the laser displacement sensor and the car body surface is set as L0; the small displacement allowed by the car body is set as L wmin (Extraversion) and L nmin (Inward tilt), this displacement indicates that the vehicle body has a slight lateral displacement, but it is within the allowable range. Set the maximum allowable displacement of the vehicle body to L wmax (Extraversion) and L nmax (Inward tilt), this displacement indicates that the train has flipped at a large angle, and the probability of overturning is high. When the car body passes through the tunnel cross-section area, it will be affected by the violent pressure wave, causing the car body to shift laterally and flip. For example, if the distance between the laser displacement sensor and the car body surface is L0 <L wmin , the monitoring and control system does not change the train running speed and power supply mode. If the distance between the laser displacement sensor and the vehicle body surface is L wmin <L0<L wmax , the monitoring center will generate an early warning signal, and the control center will adjust the train speed and power supply mode to restore the train to a stable state. If the distance between the laser displacement sensor and the surface of the vehicle is L0>L wmax , it means that there is a high probability that the train will overturn. At this time, the monitoring center will issue an emergency warning signal and the control center will control the train to emergency brake.

[0072] Ultrasonic sensors (i.e. ultrasonic ranging sensors) are used to measure the distance between the vehicle body and the tunnel wall. As an auxiliary to the laser displacement sensor, they can provide redundant measurement data. The role of the ultrasonic sensor is to provide redundant data for comparing the results of the laser displacement sensor. It is installed at the same level as the laser displacement sensor. Figure 5 In actual use, by comparing the displacement data collected by the laser displacement sensor and the ultrasonic sensor, a correct judgment can be made to avoid misjudgment due to loose sensors and other reasons. Similarly, the small displacement of the train during the ultrasonic sensor distance measurement can be set as L cwmin (Extraversion) and L cnmin (inward tilt), the maximum allowable displacement is L cwmax (Extraversion) and L cnmax (Inward tilt). The judgment logic for the lateral displacement of the vehicle body is the same as that of the laser displacement sensor, which will not be repeated here.

[0073] refer to Figure 5 and Figure 6, the magnetic sensor is set on the guide track of the maglev train at the tunnel cross-section, which can convert the magnetic property changes of the sensitive element caused by external factors (such as magnetic field, current) into electrical signals, which are used to monitor the suspension height and stability of the maglev train and ensure the normal operation of the train suspension system. When the car body undergoes the aforementioned small displacement, the distance between the suspension frame and the track is H wmin (Extraversion) and H nmin (Inclined), this height indicates that there is a certain distance between the train bogie and the track. On the outward tilt side, the magnetic attraction is weakened, and on the inward tilt side, the magnetic attraction is strengthened. When the car body is at the maximum allowable displacement mentioned above, the distance between the suspension frame and the track is H wmax (Extraversion) and H nmax (Inward tilt), this height indicates that the train bogie is about to touch the maglev train guide rail. The outward tilt side shows that the magnetic attraction is greatly weakened, that is, the attraction between the maglev train guide rail and the suspension frame is weakened, and the inward tilt side shows that the magnetic attraction is enhanced. Its mechanism of action is also to judge the height H0 of the suspension frame and the track, and then to feedback different signals to the monitoring center for early warning by comparing the set parameters.

[0074] refer to Figure 5 ,The pressure sensor is installed on the inner wall of the tunnel to measure the air pressure fluctuations in the tunnel and help analyze the impact of pressure waves on the running posture of the vehicle.

[0075] The gyroscope sensor can be installed near the center of gravity of the vehicle body to detect the rotational motion and angular velocity of the vehicle body and accurately monitor the lateral displacement and tilt angle of the vehicle body. Three gyroscope sensors need to be evenly arranged in each car along the axial direction to comprehensively judge the lateral displacement status of different positions in the tunnel of the vehicle body. Figure 6 and Figure 7 , when the train is slightly displaced, the inclination angle of the train body is θ min ; The maximum tilt angle θ allowed by the vehicle body max When the train is running in the tunnel, the inclination angle of the train body is assumed to be θ0 at any time.

[0076] When a maglev train is running in a tunnel, when the car body passes through a variable cross-section area or a curved section, the car body will be affected by the violent fluctuations of pressure waves and inertial acceleration, causing lateral displacement and flipping. At this time, if the car body tilt angle detected by the gyroscope sensor is θ0<θ min , the monitoring and control system does not change the train speed and power supply mode. If the vehicle body tilt angle detected by the gyro sensor is θ min <θ0<θ max , the monitoring center will generate an early warning signal, and the control center will adjust the train speed and power supply mode to restore the train to stability. If the body tilt angle detected by the gyro sensor is θ0>θ max, it means that the train may overturn. At this time, the monitoring center sends out an emergency warning signal and the control center controls the train to emergency brake.

[0077] refer to Figure 7 The acceleration sensor is installed on the surface of the car body to measure the acceleration change of the car body, especially the lateral acceleration, to assist in judging the dynamic behavior of the car body. Three acceleration sensors are evenly arranged on the surface of each car. The lateral acceleration of the train at any time is set as V0, and the acceleration when the train has a small lateral displacement is set as V min , the acceleration when the maximum displacement occurs is V max When V0 <V min , the monitoring and control system does not change the train running status; when V min <V0<V max When V0>V max When the data from the acceleration sensor and the gyroscope sensor are matched, the monitoring center will compare the data. When the data from the two sensors are consistent, an emergency warning signal will be issued and the control center will control the train to emergency brake.

[0078] When the sensor network is used for the first time, the displacement data of the maglev train when it runs smoothly in the tunnel should be collected and used as the baseline data.

[0079] The aforementioned L0, H0, θ0 and V0 are all the lateral swing data of the maglev train that characterize the lateral swing and lateral deflection of the car body when the maglev train passes through the tunnel with variable cross-section. wmin , L cwmin , H wmin ,θ min and V min are a series of parameters corresponding to the small body posture allowed by the vehicle body. Similarly, L wmax , L cwma , H wmax ,θ max and V max The processing logic of inclination and camber is similar, which will not be described here.

[0080] The system of the present application is equipped with various sensors such as acoustic and optical ranging sensors and inertial sensors at multiple locations such as the inner wall of the tunnel and the car body, realizing comprehensive monitoring of the running posture of the maglev train. Compared with the traditional single sensor monitoring technology, the system can provide more accurate and redundant data, and improve the reliability, accuracy and environmental adaptability of monitoring through the redundancy mechanism. And the running posture control method of adjusting the running speed and / or power supply mode of the maglev train has a higher response speed and control accuracy than the traditional mechanical adjustment method. The present application is particularly suitable for situations where there is insufficient light and complex environment in the tunnel. Compared with systems that rely on optical monitoring, the present application combines multiple sensors and can work stably under various environmental conditions, thereby ensuring the accuracy of the monitoring data and the reliability of the system.

[0081] This application improves the operating safety and riding comfort of the train by effectively solving the aerodynamic problems of the maglev train when running at high speed in the tunnel, and provides technical accumulation for the development of future high-speed maglev transportation systems. For new lines, this system can be used as a standard configuration in the tunnel design and construction of new maglev lines, thereby improving the stability and safety of line operation. For the upgrade and reconstruction of existing lines: the existing maglev lines can improve the operating quality and safety level of the existing lines by installing this monitoring and control system.

[0082] Since maglev trains use trackless contact technology, they are more susceptible to changes in tunnel cross-section and pressure fluctuations during operation, and the lateral swing and dynamic displacement process of the train are more obvious. This aerodynamic effect will make passengers in the car feel obvious discomfort of inclination or inclination, and in severe cases may even endanger driving safety. This application uses real-time monitoring and intelligent scheduling to make the operation of trains in tunnels smoother, reduce delays caused by faults or unstable postures, and improve the operating efficiency of trains. By regulating the running posture of maglev trains in tunnels, the vibration and noise of the car body caused by pressure fluctuations are reduced, which significantly improves the riding experience of passengers, attracts more people to choose maglev trains as a means of travel, and drives the revenue growth of related departments and enterprises.

[0083] The flowchart and / or block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and / or computer program product according to various embodiments of the present application. In this regard, each box in the flowchart and / or block diagram can represent a part of a module, program segment or code, and a part of the above-mentioned module, program segment or code includes one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. It should also be noted that each box in the block diagram or flowchart, and the combination of the boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0084] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present application. In particular, without departing from the spirit and teachings of the present application, the technical features described in the various embodiments and / or claims of the present application may be combined and / or combined in a variety of ways, and all of these combinations and / or combinations fall within the scope of the present application.

[0085] Although the present application has been shown and described with reference to specific exemplary embodiments of the present application, it should be understood by those skilled in the art that various changes in form and details may be made to the present application without departing from the spirit and scope of the present application as defined by the appended claims and their equivalents. Therefore, the scope of the present application should not be limited to the above-mentioned embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims.

Claims

1. A maglev train running posture monitoring and control system for tunnel scenarios, characterized in that: include: The sensor network includes an acoustic-optical distance measuring sensor arranged on the wall of the tunnel where the cross-section changes and an inertial sensor arranged on the body of the maglev train, which is used to obtain the body lateral swing data representing the lateral swing and lateral deflection of the body when the maglev train passes through the tunnel where the cross-section changes; the acoustic-optical distance measuring sensor includes a laser distance measuring sensor and an ultrasonic distance measuring sensor; A monitoring center is used to receive the vehicle body lateral deflection data and compare and analyze it with a preset threshold value to obtain a vehicle body lateral deflection analysis result; The control center is used to receive the analysis result of the lateral deflection of the vehicle body and adjust the running speed and / or power supply mode of the maglev train based on the analysis result to restore the train to a stable posture.

2. The maglev train running posture monitoring and control system according to claim 1, characterized in that: The preset threshold value includes: vehicle body lateral sway data representing the maximum allowable large-amplitude sway posture, and vehicle body lateral sway data representing the maximum allowable small-amplitude sway posture; The maximum allowable large amplitude yaw posture represents a critical state in which the probability of the maglev train overturning exceeds a preset probability threshold when the yaw amplitude of the posture exceeds the large amplitude critical state; The maximum allowable small amplitude yaw posture represents that when the maglev train exceeds the small amplitude critical state attitude yaw amplitude, it just changes from not having to adjust the maglev train running speed and / or power supply mode to the critical state where the maglev train running speed and / or power supply mode needs to be adjusted.

3. The maglev train running posture monitoring and control system according to claim 2, characterized in that: The logic for making adjustments based on the analysis results includes: If x0<x min , then the control center does not need to adjust the running speed and / or power supply mode of the maglev train; If x min <x0<x max , the monitoring center sends out an early warning signal, and the control center adjusts the running speed and / or power supply mode of the maglev train to restore the train to a stable state; If x0>x max , the monitoring center sends out an emergency warning signal, and the control center controls the emergency braking of the maglev train; Wherein, x0 represents the vehicle lateral deflection data acquired in real time by the sensor network; x min Indicates the lateral yaw data of the vehicle body when the maximum allowable small yaw posture is present; x max It represents the lateral yaw data of the vehicle body when it represents the maximum allowable large yaw posture.

4. The maglev train running posture monitoring and control system according to claim 1, characterized in that: The laser distance measuring sensor and the ultrasonic distance measuring sensor are arranged on the wall of the tunnel where the cross section is changed on the same horizontal plane, and are both used to measure the distance between the body of the maglev train and the inner wall of the tunnel.

5. The maglev train running posture monitoring and control system according to claim 4, characterized in that: The inertial sensor includes: a gyroscope sensor and / or an acceleration sensor; The gyro sensor is arranged within a preset distance range near the center of gravity of the maglev train body, and is used to measure the angular velocity of the body to obtain the inclination angle of the body; The acceleration sensor is arranged on the surface of the maglev train body and is used to measure the lateral acceleration of the body.

6. The maglev train running posture monitoring and control system according to claim 4, characterized in that: The sensor network also includes a magnetic sensor arranged on a guide track of the maglev train at a location where the tunnel has a variable cross-section, and is used to measure the suspension height of the maglev train.

7. The maglev train running posture monitoring and control system according to claim 4, characterized in that: The sensor network also includes a pressure sensor arranged on the wall at the tunnel cross-section variable position, which is used to measure the air pressure in the tunnel.

8. The maglev train running posture monitoring and control system according to claim 3, characterized in that: The control center is also used to continuously optimize the control instructions through machine learning according to the adjustment measures of the maglev train each time it passes through the tunnel with variable cross-section, automatically adjust the running speed and / or power supply mode of the maglev train, and finally reach the best control strategy to enable the maglev train to pass through the tunnel with variable cross-section in a stable posture.

9. The maglev train running posture monitoring and control system according to claim 1, characterized in that: Adjusting the power supply mode to restore the train to a stable posture includes: When the maglev train passes through the tunnel with variable cross-section, different currents are applied on both sides of the maglev train guide track, so that the suspension frames on both sides of the maglev train are subjected to different suspension forces, thereby balancing the centrifugal force generated by the car body, reducing lateral swing and lateral deflection, and allowing the train to restore a stable posture.

10. A maglev train running posture monitoring and control system for use in tunnel scenarios, characterized in that: include: The sensor network includes an acoustic-optical distance measuring sensor arranged on a wall at a preset position of a tunnel curve section and an inertial sensor arranged on a maglev train body, for obtaining body lateral sway data representing lateral swing and lateral deflection of the body when the maglev train passes through the preset position of the tunnel curve section; the acoustic-optical distance measuring sensor includes a laser distance measuring sensor and an ultrasonic distance measuring sensor; A monitoring center is used to receive the vehicle body lateral deflection data and compare and analyze it with a preset threshold value to obtain a vehicle body lateral deflection analysis result; The control center is used to receive the analysis result of the lateral deflection of the vehicle body and adjust the running speed and / or power supply mode of the maglev train based on the analysis result to restore the train to a stable posture.

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