Tunnel high-speed train dynamic fire scene simulation and intelligent measurement and control experiment platform and application thereof

Abstract

The invention discloses a tunnel high-speed train dynamic fire scene simulation and intelligent measurement and control experiment platform and application thereof, and the platform modularly integrates a tunnel model, a train model, a high-speed meshing driving system, an optical dynamic tracking system, a multi-mode fire scene simulation system, a high-frequency acquisition system and a control cabinet. The tunnel model adopts a splicing structure to adapt to different experiment scenes; the train head adopts an arc-shaped structure to optimize aerodynamic performance; a gear rack-sliding rod transmission mode and a synchronous operation technology are innovatively adopted, and the dynamic flame form can be accurately captured; the multi-mode fire scene simulation system performs omnibearing simulation on fire disasters at different parts; the tank chain is used for long-distance dynamic energy transmission; the high-frequency acquisition system monitors fire multi-source characteristic parameters in real time; and the controller realizes automatic control of the experiment process. The dynamic high-precision experimental platform constructed by the invention can provide technical support for researching flame propagation, flue gas diffusion and toxic gas distribution, and has important significance for improving the fire prevention and control capability of the train.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel and urban rail transit safety, and more specifically, it is designed to provide a dynamic fire scene holographic simulation device, a measurement and control system, and a method for processing fire characteristic parameters for a train running at high speed in a tunnel, which are used for the research on the fire of a train running at different fire locations. Background Art

[0002] In recent years, with the development of society and cities, the subway industry has developed rapidly. However, there are many unsafe factors in fire safety, and these problems need to be studied and solved urgently. Among subway disasters, fire is a dangerous and harmful factor that is likely to occur, causes the greatest harm, and is difficult to control. This is because the subway system has a long and narrow space, strong sealing, and dense personnel. Once a fire accident occurs, it is extremely likely to cause serious consequences.

[0003] Subway system fires can be divided into train fires, station fires, and tunnel fires. When a subway train catches fire in a long tunnel section, it is difficult to evacuate and rescue personnel on the spot after being forced to stop in the tunnel. The foreign subway operation system stipulates that in case of emergencies such as fires, subway trains are generally not allowed to stop in the tunnel, but need to continue running until they enter the next station for evacuation and rescue; the current standard GB / T 33668-2017 "Subway Safety Evacuation Code" stipulates that when the train is in good condition and has not lost power, it should continue running to the front station for evacuation and rescue. Therefore, for actual subway tunnel train fires, when a train catches fire, it is often in a moving state.

[0004] However, at present, certain achievements have been made in the research on subway fires and fire smoke at home and abroad. There is relatively little research on the fire of a moving train in a tunnel section both internationally and in China. Some domestic tunnel fire experimental platforms can conduct low-speed moving fire simulations. Due to the complex operating conditions, it is not easy to supply gas to the burner, and oil pool fires are mostly used in experiments. However, the maximum operating speed of a subway train can reach 160 km / h, and it is difficult for an oil pool fire to remain stable at higher speeds. These experimental platforms cannot be used to study the fire characteristics of a train running at high speed in a tunnel. At the same time, the existing moving fire experimental platforms capture the flame morphology based on ground-fixed cameras, and it is impossible to stably capture and reproduce the high-definition flame morphology of a train running at high speed in a tunnel. In addition, most of the existing model experiments study the fire on the train roof, but there are fire hazard factors on the train roof, in the carriage, and under the car body. These experimental platforms cannot effectively simulate the fire scenarios of actual trains catching fire at different parts. Summary of the Invention

[0005] To solve the problems existing in the prior art, the present invention provides a dynamic fire scene simulation and intelligent measurement and control experimental platform for tunnel high-speed trains and its application, aiming to build an efficient, controllable and reproducible fire simulation and control platform to comprehensively evaluate the fire risk of high-speed trains, so as to provide data support and scientific support for fire prevention and control and emergency rescue of high-speed trains running in long tunnel sections, and also help researchers comprehensively evaluate the fire prevention and control effects when fires occur in different parts of the train, thereby improving the safety and emergency response capabilities of the subway system during actual operation.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A dynamic fire scene simulation and intelligent measurement and control experimental platform for tunnel high-speed trains of the present invention is characterized by including: a tunnel model, a train model, a high-speed meshing drive system, a multi-modal fire scene simulation system, an optical dynamic tracking system, a high-frequency acquisition system, and a control cabinet;

[0008] Sliding rods and racks are integrated on the bottom plate of the tunnel model to provide a running track for the train model; the train model runs on the track through the high-speed meshing drive system;

[0009] The multi-modal fire scene simulation system is used to simulate fire scenes in different parts of the train model;

[0010] The optical dynamic tracking system runs synchronously with the train model and is used to capture the dynamic flame morphology of the train model in real time;

[0011] The high-frequency acquisition system is used to record temperature, heat flux and gas concentration parameters in real time;

[0012] The control cabinet is used to control the operation of the train model and the optical dynamic tracking system, the fire intensity of the multi-modal fire scene simulation system, the shooting duration of the optical dynamic tracking system, and the start and stop of the high-frequency acquisition system.

[0013] The dynamic fire scene simulation and intelligent measurement and control experimental platform for tunnel high-speed trains of the present invention is also characterized in that the tunnel model and the train model are arranged as follows:

[0014] The tunnel model is fixed on the tunnel model support, the top plate of the tunnel model support serves as the bottom plate of the tunnel model, the tunnel model is composed of multiple standard section models spliced together, any standard section model is a U-shaped model composed of three aluminum alloy plates, a high-temperature resistant fireproof board is arranged inside the aluminum alloy plate, and high-temperature resistant glass is arranged on any side aluminum alloy plate;

[0015] A clamping groove is installed on the outer side of the top plate of the tunnel model support. Two sliding rods are fixed at the center of the top plate, and a rack is laid on the inner side of the top plate; Two tunnel model limiters are installed at both ends of the top plate of the tunnel model support; A first locator is installed on the starting side of the top plate of the tunnel model support where the train model runs.

[0016] The train model is divided into a straight-section body and an arc-section head; The train model is assembled by splicing aluminum alloy plates. The train model is fixed on the train model support flat plate through two support rods. A first sliding bearing is installed at the bottom of the train model support flat plate, and the first sliding bearing is arranged on the two sliding rods of the tunnel support top plate; A battery-powered identification light is arranged at the arc-section head of the train model.

[0017] Further, the high-speed meshing drive system includes: a first gear, a first drive motor, a first motor support frame, a first connecting plate, a first power line, a first control line, a first caterpillar track.

[0018] The first motor support frame is assembled by three aluminum alloy plates. The first drive motor is arranged on the inner bottom surface of the motor support frame, and the first drive motor is connected to the gear through a gear shaft; The gear meshes with the rack on the top plate of the tunnel model support.

[0019] The bottom surface of the motor support frame is connected to a second sliding bearing. The second sliding bearing is arranged on the two sliding rods of the tunnel support top plate and is behind the running direction of the first sliding bearing.

[0020] On the side of the motor support frame in the same running direction as the train model, it is connected to the support flat plate of the train model through a connecting plate. Thus, the train model is driven by the first drive motor to slide and run on the two sliding rods through the first sliding bearing and the second sliding bearing.

[0021] On the side of the motor support frame in the opposite running direction to the train model, it is connected to the first caterpillar track. The first caterpillar track is arranged in the clamping groove of the top plate of the tunnel model support; The power line and the control line are arranged inside the caterpillar track and are connected to the control cabinet, so as to provide power supply and control signals for the first drive motor.

[0022] Further, the multi-modal fire scene simulation system includes: a fire head, a solenoid valve, a solenoid valve power line, a flow meter, a first gas supply pipeline, a second gas supply pipeline, a third gas supply pipeline, a gas cylinder, a high-voltage arc igniter, a temperature probe.

[0023] The fire head includes: an inner layer gas supply component, an outer layer sleeve. The inner layer gas supply component includes: a gas supply head, a pneumatic joint.

[0024] The inside of the air supply head is provided with an air supply passage with air holes. The two ends of the air supply head are respectively threadedly connected to a pneumatic joint and the outer sleeve. And there is an annular gap between the air supply head and the outer sleeve for outer air supply.

[0025] The burner head is fixedly mounted on the train model by threaded connection. A high-voltage arc igniter and a temperature probe are arranged directly above the burner head. The gas cylinder is connected to the third gas supply pipeline through a pressure reducing valve. The third gas supply pipeline is connected to the inlet of a flowmeter. The outlet of the flowmeter is connected to the second gas supply pipeline. The second gas supply pipeline is arranged inside the drag chain and is connected to a solenoid valve. The solenoid valve is connected to the first gas supply pipeline. The first gas supply pipeline is connected to the pneumatic joint of the burner head.

[0026] The flowmeter controls the power of the fire source by regulating the mass flow of the gas passing through.

[0027] Further, the optical dynamic tracking system includes: an optical dynamic tracking system bracket, a motion camera, a first camera support flat plate, a second camera support flat plate, a synchronous tracking power system, two optical dynamic tracking system limiters, and a second positioner.

[0028] On the outer side of the top plate of the optical dynamic tracking system bracket, a mounting slot is installed. Two sliding rods are fixed at the center of the top plate. A rack is laid on the inner side of the top plate. Two optical dynamic tracking system limiters are installed at both ends of the top plate of the optical dynamic tracking system bracket. A second positioner is installed on the starting side of the operation of the motion camera on the top plate of the optical dynamic tracking system bracket.

[0029] The motion camera is fixed on the first camera support flat plate. The first camera support flat plate is connected to the second camera support flat plate through two threaded connecting rods. A third sliding bearing is installed at the bottom of the second camera support flat plate. The third sliding bearing is arranged on the two sliding rods of the top plate of the optical dynamic tracking system bracket.

[0030] Further, the synchronous tracking power system includes: a second gear, a second driving motor, a second motor support frame, a second connecting plate, a second power line, a second control line, and a second drag chain.

[0031] The second motor support frame is an aluminum alloy flat plate. The second driving motor is arranged on the inner bottom surface of the second motor support frame. And the second driving motor is connected to the second gear through a gear shaft. The second gear meshes with the rack on the optical dynamic tracking system bracket.

[0032] The bottom surface of the second motor support frame is connected to a fourth sliding bearing. The fourth sliding bearing is arranged on the two sliding rods of the top plate of the optical dynamic tracking system bracket and is behind the running direction of the third sliding bearing.

[0033] On one side of the sports camera in the same running direction, the second motor support frame is connected to the second support flat plate of the sports camera through a second connecting plate, so that the sports camera is driven by the second driving motor to slide on two sliding rods through a third sliding bearing and a fourth sliding bearing;

[0034] On the side of the sports camera opposite to the running direction, the second motor support frame is connected to the second drag chain. The second drag chain is arranged in the card slot of the top plate of the optical dynamic tracking system support; the second power line and the second control line are arranged inside the second drag chain and connected to the control cabinet, so as to provide power supply and control signals for the second driving motor.

[0035] Furthermore, the high-frequency acquisition system includes: a thermocouple, a heat flux meter, a high-speed acquisition device, and a water cooling device. The water cooling device includes: a water pump, a water tank, and a water pump power line;

[0036] The thermocouple and the heat flux meter are arranged on the top plate and the bottom plate of the train model. The wiring of the thermocouple and the heat flux meter is connected to the high-speed acquisition device; the water pump is fixed at the bottom of the water tank. The water inlet pipe of the heat flux meter is connected to the water outlet pipe of the water pump, and the water outlet pipe of the heat flux meter is inserted into the water tank; the power line provides power for the water pump; the high-speed acquisition device is powered by a battery.

[0037] The control system of the tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experiment platform based on the above has the following characteristics and is carried out according to the following steps:

[0038] Step 1: The control cabinet controls the first driving motor to drive the train model to move towards the first locator in a low-speed mode, and controls the second driving motor to drive the sports camera to move towards the second locator in a low-speed mode;

[0039] When the train model reaches the first locator, when the Hall sensor in the first locator detects a magnetic field change, the encoder pulse count value of the first driving motor is cleared, and the position of the train model when it reaches the first locator is set as the initial position x 0,train ;

[0040] When the sports camera reaches the second locator, when the Hall sensor in the second locator detects a magnetic field change, the encoder pulse count value of the second driving motor is cleared, and the position of the sports camera when it reaches the second locator is set as the initial position x 0,camera ;

[0041] Step 2: Set the experimental parameters, including: the length L of the tunnel model tunnel , the length L of the optical dynamic tracking system support trace , the mass flow rate m of the gas in the flowmeterset 、The running speed v of the train model set,train 、The running speed v of the synchronous camera set,camera 、The running displacement x of the train model set,train 、The running displacement x of the synchronous camera set,camera ;

[0042] Step Three: The control cabinet 20 starts the solenoid valve 10 and starts the flowmeter 12 to supply gas according to the set target mass flow rate m set Meanwhile, the control cabinet 20 triggers the high-voltage arc igniter to ignite the fire source, and synchronously starts the temperature probe to monitor the state of the fire source in real time;

[0043] Step Four: The flowmeter 12 collects the mass flow rate m real (t) at time t in the gas supply pipeline, and calculates the mass flow rate volatility at time t ; If is less than the set flow threshold, then execute Step Five, otherwise, use the PID control algorithm to adjust m real (t), and obtain the flow control value at time t using Equation (a) , so as to control the flowmeter 12 to adjust the mass flow rate of the gas it passes through, so that is less than the set flow threshold:

[0044] (a)

[0045] In Equation (a), is the proportionality coefficient, is the integral coefficient, is the differential coefficient;

[0046] Step Five: The control cabinet triggers the high-voltage arc igniter to ignite the fire source, and synchronously starts the temperature probe to monitor the state of the fire source in real time; The control cabinet starts the high-speed acquisition device for collecting data of the thermocouple and the heat flow meter;

[0047] Step Six: Synchronously control the operation of the train model and the moving camera;

[0048] Step Seven: When N train (t) = 0 and N camera (t) = 0, it indicates that the braking is completed. The control cabinet closes the solenoid valve, resets the mass flow rate in the flowmeter, and turns off the temperature probe, the high-speed acquisition device, and the water-cooling device.

[0049] The characteristics of a control system of the tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experimental platform based on the above also lie in that Step Six includes:

[0050] Step 6.1: Obtain the control frequency f of the first motor according to Equation (b)train to control the train model to run at the running speed v set,train :

[0051] (b)

[0052] In formula (b), m is the module of the gear in the train model, and Z is the number of teeth of the gear in the train model; N p is the number of pole pairs of the first motor;

[0053] Step 6.2: The control cabinet uses the high-precision encoder built in the drive motor to collect the pulse signal N train (t) of the rotation angle of the first motor at time t, so as to obtain the running speed of the train model at time t by using formula (c) :

[0054] (c)

[0055] In formula (c), is the fixed angle corresponding to the rotation of the motor gear for a single pulse;

[0056] Step 6.3: The control cabinet calculates the running speed error of the train model at time t ;

[0057] Step 6.4: If is less than the set speed threshold, then execute Step Five; otherwise, use the PID control algorithm to adjust to obtain the control frequency of the first motor at time t, so as to control the running speed of the train model at time t to be less than the set speed threshold;

[0058] Step 6.5: If L trace < L tunnel , then the control cabinet calculates the delay start time t delay =(L tunnel L trace ) / v train ; otherwise, let t delay =0; thus start the motion camera according to t delay ;

[0059] Step 6.6: The control cabinet calculates the running speed of the motion camera at time t; if is less than the set speed threshold, then execute Step 6.7; otherwise, adjust according to the PID control algorithm for to control to be less than the set speed threshold;

[0060] Step 6.7: The control cabinet calculates the actual displacement of the train model at time t and the actual displacement of the motion camera at time t by using equations (d) and (e) respectively : :

[0061] (d)

[0062] (e)

[0063] In equations (d) and (e), represents the single-pulse displacement, and ; N camera (t) is the pulse signal of the rotation angle of the second motor at time t

[0064] Step 6.8: When , the control cabinet controls the first drive motor to apply a reverse torque to decelerate and brake the train model. Otherwise, after assigning t + 1 to t, return to step 6.2 and execute sequentially;

[0065] When , the control cabinet controls the second drive motor to apply a reverse torque to decelerate and brake the motion camera. Otherwise, after assigning t + 1 to t, return to step 6.6 and execute sequentially

[0066] The feature of a method for processing fire characteristic parameters based on the above-mentioned control system of the present invention is that it is carried out according to the following steps

[0067] Step I: After obtaining the flame video sequence captured by the motion camera after braking completion and performing stability processing, convert it from the RGB color space to the grayscale space, and then use the threshold segmentation algorithm to perform binary processing on each frame of the flame image in the grayscale flame video sequence to obtain a binary flame video sequence

[0068] Step II: Stack the binary flame video sequence frame by frame, and count the frequency of the appearance of the flame at each pixel point, so as to construct a flame probability density matrix at the pixel point (x, y) , where is the binary value at the pixel point (x, y) in the t-th frame of the flame image, and N is the total number of frames

[0069] Step III: According to the calibration parameters of the motion camera, map the pixel point (x, y) to the pixel point (X real , Y real ) in the actual physical coordinate system , so as to construct the pixel point (X real , Yreal ) Flame probability density matrix at ; where ρ is the pixel resolution of the motion camera, and α is the spatial scale factor of the motion camera;

[0070] Step IV: Based on Extract the flame boundary and obtain the flame scale data, including: flame length L f , flame height H f ;

[0071] Step V: Use Equation (f) and Equation (g) to establish a dimensionless flame length model and a dimensionless flame height model respectively:

[0072] (f)

[0073] (g)

[0074] In Equation (f) and Equation (g), is the dimensionless heat release rate of the heat source, is the dimensionless running speed of the train model, is the diameter of the fire head, is the calorific value of the fuel of the heat source, is the initial ambient density, is the specific heat capacity at constant pressure, is the initial ambient temperature, is the acceleration due to gravity; is the flame length relationship; is the flame height relationship;

[0075] Step VI: According to the data collected by the thermocouples and heat flux meters on the top plate and bottom plate of the train model, draw a time series graph and calculate the average value of the stable section, so as to use the average value of the stable section of the thermocouple as the temperature value t of the train model f , and use the product of the average value of the stable section of the heat flux meter and the correction coefficient as the heat flux value q of the train model f ;

[0076] Step VII: Normalize the temperature value t f and the heat flux value q f respectively according to Equation (h) and Equation (i) to obtain the normalized temperature value and the normalized heat flux value :

[0077] (h)

[0078] (i)

[0079] In Equation (h) and Equation (i), represents the temperature rise on the top plate and bottom plate of the train model, and , represents the peak value of the temperature rise on the top plate and bottom plate of the train model, and , is the peak temperature on the top plate and bottom plate of the train model;

[0080] Step VIII: Establish a peak temperature rise model on the top plate and bottom plate of the train model according to Equation (j):

[0081] (j)

[0082] In Equation (j), is the peak temperature rise relational expression;

[0083] Establish a predicted temperature distribution model on the top plate and bottom plate of the train model according to Equation (k):

[0084] (k)

[0085] In Equation (k), is the temperature distribution relational expression; is the distance between the thermocouple position and the peak value of the temperature rise on the top plate and bottom plate of the train model; is the characteristic scale of the fire source, and ;

[0086] Step IX: Obtain a characterization model of the roof heat flux distribution of a running train fire according to Equation (l):

[0087] (l)

[0088] In Equation (l), is the heat flux distribution relational expression.

[0089] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0090] 1. The present invention proposes a tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experimental platform, which integrates multiple functional modules, such as a control cabinet, a high-frequency acquisition system, an optical dynamic tracking system, a multi-modal fire field simulation system, etc. According to the control steps, efficient collaborative work can be achieved among various parts, realizing effective research on the fire characteristics of high-speed running trains.

[0091] 2. The drag chain in the present invention is provided with a power bus, a control bus, and a gas supply pipeline, which can provide stable power supply, signal transmission, and gas transportation for multiple components in the system platform (such as drive motors, solenoid valves, fire heads, etc.), avoiding the winding interference and fuel leakage problems generated by the previous design methods in complex operating environments, and improving the stability and durability of the system.

[0092] 3. The design of the burner head in the present invention enables it to accurately simulate different fire scales by adjusting the gas flow rate, and can simulate different fire scenarios (fires on the train roof, in the carriage, and under the train) by adjusting the fixed position relative to the train model. At the same time, the design of the burner head in the fire source system can effectively prevent the fire source from extinguishing during high-speed operation, facilitating the decoupled study of the fire combustion characteristics of the train under high-speed operation.

[0093] 4. The system of the present invention adopts transmission methods such as gears and sliding bearings. The driving motor, through the meshing transmission method of gears and racks, can enable the train model and the synchronous camera to move smoothly and accurately in the tunnel. This transmission method effectively avoids the vibration or instability problems that may occur when directly driven by a traditional motor, ensuring the smooth and synchronous operation of the train model and the synchronous camera in a long tunnel section.

[0094] 5. An experimental platform for dynamic fire field simulation and intelligent measurement and control of high-speed trains in tunnels of the present invention includes two tracks. The train model and the moving camera can run in parallel on the two tracks to achieve synchronous shooting of the flame morphology. At the same time, based on the identification lights on the train model and the proposed flame video analysis and processing steps, a stable video of the flame morphology captured by the moving camera can be obtained, providing effective data support for the in-depth study of the fire characteristics of the running train.

[0095] 6. The working process of the system of the present invention tends to be automated. The control cabinet, as the core control unit of the entire fire simulation system, can be operated through the panel. By means of precise motion control, delay start mechanism, solenoid valve safety protection, etc. of the control cabinet, the safety, convenience, and repeatability of the experimental process are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 It is a schematic diagram of an experimental platform for dynamic fire field simulation and intelligent measurement and control of high-speed trains in tunnels;

[0097] Figure 2 It is a schematic diagram of the tunnel model structure;

[0098] Figure 3 It is a top view of the layout of the tunnel model bottom plate;

[0099] Figure 4 It is the front view and top view of the burner head;

[0100] Figure 5 It is a schematic diagram of the high-frequency acquisition system;

[0101] Figure 6 It is the control system of the experimental platform for dynamic fire field simulation and intelligent measurement and control of high-speed trains in tunnels;

[0102] Figure 7Step Six of the Control System for the Dynamic Fire Field Simulation and Intelligent Measurement and Control Experimental Platform of Tunnel High-Speed Trains

[0103] Labels in the figure: 1. Tunnel model; 2. Train model; 3. Support flat plate of the train model; 4. Identification lamp; 5. Driving motor; 6. Motor support frame; 7. Power line; 8. Control line; 9. Drag chain; 10. Solenoid valve; 11. Gas cylinder; 12. Flowmeter; 13. Burner head; 14. First gas supply pipeline; 15. Second gas supply pipeline; 16. Third gas supply pipeline; 17. Second support flat plate of the camera; 18. Moving camera; 19. First support flat plate of the camera; 20. Control cabinet; 21. Connecting plate; 22. Gear; 23. Sliding rod; 24. Card slot; 25. Rack; 26. High-speed acquisition device; 27. Water pump; 28. Water tank; 29. Limiter of the tunnel model; 30. Heat flux meter; 31. Thermocouple; 32. Aluminum alloy plate; 33. High-temperature resistant glass; 34. Support of the tunnel model; 35. Gas supply head; 36. Outer sleeve; 37. Gas supply head; 38. Pneumatic joint; 39. Gas supply path; 40. Circular air hole; 41. Limiter of the optical dynamic tracking system Detailed implementation method

[0104] In this embodiment, as Figure 1 shown, in order to make up for the deficiency of the experimental platform in simulating the fire of high-speed trains running in long tunnels, a high-efficiency, controllable and reproducible dynamic fire field simulation and intelligent measurement and control experimental platform for tunnel high-speed trains is designed to study the fire prevention of different parts of running trains. Specifically, the platform includes: tunnel model 1, train model 2, high-speed meshing drive system, multi-modal fire field simulation system, optical dynamic tracking system, high-frequency acquisition system, control cabinet 20;

[0105] As Figure 2 shown, the tunnel model 1 is fixed on the support 34 of the tunnel model. The top plate of the support 34 of the tunnel model serves as the bottom plate of the tunnel model 1. The tunnel model 1 is composed of multiple standard section models, which supports modular expansion of the length of the tunnel model within the required range to meet the simulation requirements of different section tunnels. Any standard section model is a U-shaped model composed of three aluminum alloy plates 32. A high-temperature resistant fireproof board is arranged inside the aluminum alloy plate 32, and high-temperature resistant glass 33 is arranged on any side aluminum alloy plate 32.

[0106] As Figure 3 shown, a card slot 24 is installed on the outer side of the top plate of the support 34 of the tunnel model. Two sliding rods 23 are fixed at the center of the top plate. A rack 25 is laid on the inner side of the top plate; Two limiters 29 of the tunnel model are installed at both ends of the top plate of the support 34 of the tunnel model; A first locator is installed on the top plate of the support 34 of the tunnel model on the starting side of the train model 2;

[0107] The train model 2 is divided into a straight-section body and an arc-section front end. The arc-section front end is used to stabilize the air flow. The train model 2 is assembled by aluminum alloy plates 32. The train model 2 is fixed on the train model support flat plate 3 through two support rods. A first sliding bearing is installed at the bottom of the train model support flat plate 3, and the first sliding bearing is arranged on two sliding rods 23 of the tunnel support roof plate 34. A battery-powered identification lamp 4 is arranged at the arc-section front end of the train model.

[0108] The high-speed meshing drive system includes: a first gear 22, a first drive motor 5, a first motor support frame 6, a first connecting plate 21, a first power line 7, a first control line 8, a first armored chain 9;

[0109] The first motor support frame 6 is assembled by three aluminum alloy plates 32. A first drive motor 5 is arranged on the inner bottom surface of the motor support frame 6, and the first drive motor 5 is connected to the gear 22 through a gear shaft. The gear 22 meshes with a rack 25 on the tunnel model support roof plate;

[0110] The bottom surface of the motor support frame 6 is connected to a second sliding bearing. The second sliding bearing is arranged on two sliding rods 23 of the tunnel support roof plate 34 and is behind the first sliding bearing in the running direction.

[0111] One side of the motor support frame 6 in the same running direction as the train model 2 is connected to the support flat plate 3 of the train model 2 through a connecting plate 21. Thus, the first drive motor 5 drives the train model 2 to slide and run on two sliding rods 23 through the first sliding bearing and the second sliding bearing;

[0112] The motor support frame 6 on the side of the train model 2 opposite to the running direction is connected to the first armored chain 9. The first armored chain 9 is arranged in a card slot 24 of the tunnel model support roof plate 34. The power line 7 and the control line 8 are arranged inside the armored chain 9 and are connected to the control cabinet 20, so as to provide power and control signals for the first drive motor 5.

[0113] The multi-modal fire scene simulation system includes: a fire head 13, a solenoid valve 10, a solenoid valve power line, a flow meter 12, a first gas supply pipeline 14, a second gas supply pipeline 15, a third gas supply pipeline 16, a gas cylinder 11, a high-voltage arc igniter, a temperature probe;

[0114] As Figure 4 shown, the fire head 13 includes: an inner layer gas supply component 35, an outer layer sleeve 36. The inner layer gas supply component 35 includes: a gas supply head 37, a pneumatic joint 38;

[0115] The gas supply head 37 is internally provided with a gas supply passage 39 with air holes 40. The two ends of the gas supply head 37 are respectively threadedly connected to the pneumatic connector 38 and the outer sleeve 36. And there is an annular gap between the gas supply head 37 and the outer sleeve 36 for outer layer gas supply. Because a gas supply passage 39 is designed inside the burner head and four circular air holes 40 are opened in the middle and lower part, while the fuel gas passes through the gas supply passage 39, it flows through the circular air holes 40 to the annular gap between the gas supply head 37 and the outer sleeve 36. Under the conditions of low power and high operating speed, the flame in the annular gap has a blocking effect on the inner layer flame of the gas supply passage 39, preventing the high-speed air flow from directly blowing out the flame, which is convenient for conducting in-depth research on the influence of the operating speed.

[0116] The burner head 13 is fixed on the train model 2 by threaded connection. A high-voltage arc igniter and a temperature probe are arranged directly above the burner head. The gas cylinder 11 is connected to the third gas supply pipeline 16 through a pressure reducing valve. The third gas supply pipeline 16 is connected to the inlet of the flowmeter 12. The outlet of the flowmeter 12 is connected to the second gas supply pipeline 15. The second gas supply pipeline 15 is arranged inside the drag chain 9 and is connected to the solenoid valve 10. The solenoid valve 10 is connected to the first gas supply pipeline 14. The first gas supply pipeline 14 is connected to the pneumatic connector of the burner head 13.

[0117] The flowmeter 12 controls the power of the fire source by adjusting the mass flow of the gas passing through.

[0118] The optical dynamic tracking system includes: an optical dynamic tracking system bracket, a motion camera 18, a first camera support flat plate 19, a second camera support flat plate 17, a synchronous tracking power system, two optical dynamic tracking system limiters, and a second positioner.

[0119] The outer side of the top plate of the optical dynamic tracking system bracket is provided with a card slot. Two sliding rods are fixed at the center of the top plate. A rack is laid on the inner side of the top plate. Two optical dynamic tracking system limiters are installed at both ends of the top plate of the optical dynamic tracking system bracket. A second positioner is installed on the starting side of the operation of the motion camera 18 on the top plate of the optical dynamic tracking system bracket. The length of the optical dynamic tracking system bracket can be shorter than the length of the tunnel model bracket because some experiments only need to take short-distance photos of the fire phenomenon, and at the same time, it can reduce the use and consumption of experimental bench construction materials. By setting the delayed start time of the motion camera 18 through the control cabinet 20, dynamic tracking shooting of the motion camera 18 can be realized under different bracket lengths.

[0120] The motion camera 18 is fixed on the first camera support flat plate 19. The first camera support flat plate 19 is connected to the second camera support flat plate 17 through two threaded connecting rods. The bottom of the second camera support flat plate 17 is provided with a third sliding bearing. The third sliding bearing is arranged on the two sliding rods of the top plate of the optical dynamic tracking system bracket.

[0121] The synchronous tracking power system includes: a second gear, a second drive motor, a second motor support frame, a second connecting plate, a second power line, a second control line, and a second drag chain;

[0122] The second motor support frame is an aluminum alloy flat plate. The second drive motor is arranged on the inner bottom surface of the second motor support frame, and the second drive motor is connected to the second gear through a gear shaft; the second gear meshes with the rack on the optical dynamic tracking system support;

[0123] The bottom of the second motor support frame is connected to a fourth sliding bearing. The fourth sliding bearing is arranged on two sliding rods on the top plate of the optical dynamic tracking system support and is behind the running direction of the third sliding bearing.

[0124] On the side of the second motor support frame in the same running direction as the motion camera 18, it is connected to the second support plate 17 of the motion camera 18 through a second connecting plate. Thus, the motion camera 18 is driven by the second drive motor to slide and run on the two sliding rods through the third sliding bearing and the fourth sliding bearing;

[0125] On the side of the second motor support frame opposite to the running direction of the motion camera 18, it is connected to the second drag chain. The second drag chain is arranged in the card slot on the top plate of the optical dynamic tracking system support; the second power line and the second control line are arranged inside the second drag chain and are connected to the control cabinet, thereby providing power supply and control signals for the second drive motor.

[0126] The braking of the high-speed meshing drive system and the optical dynamic tracking system is controlled by the built-in program of the console. When the train model 2 and the motion camera 18 run a set distance, they will brake and stop. When this program fails or malfunctions, the train model 2 and the motion camera 18 will be emergently braked and stopped again after passing through the tunnel model limiter 29 and the optical dynamic tracking system limiter 41, preventing them from rushing out of the experimental area. The tunnel model limiter 29 and the optical dynamic tracking system limiter 41 play a redundant protection role.

[0127] The high-frequency acquisition system includes: a thermocouple 31, a heat flux meter 30, a high-speed acquisition device 26, and a water cooling device. The water cooling device includes: a water pump 27, a water tank 28, and a water pump power line;

[0128] As Figure 5 shown, the thermocouple 31 and the heat flux meter 30 are arranged on the top plate and the bottom plate of the train model 2. The wiring of the thermocouple 31 and the heat flux meter 30 is connected to the high-speed acquisition device 26; the water pump 27 is fixed at the bottom of the water tank 28. The water inlet pipe of the heat flux meter 30 is connected to the water outlet pipe of the water pump 27, and the water outlet pipe of the heat flux meter 30 is inserted into the water tank 28; the power line 7 provides power for the water pump 27; the high-speed acquisition device 26 is powered by a battery. The water cooling device conducts circulating water cooling on the heat flux meter 30 to prevent the heat flux meter 30 from overheating and failing.

[0129] In this embodiment, as Figure 6 shown, a control system for a dynamic fire field simulation and intelligent measurement and control experimental platform of a tunnel high-speed train based on Claim 1 is characterized in that it is carried out according to the following steps:

[0130] Step 1: The control cabinet 20 controls the first drive motor 5 to drive the train model 2 to move towards the first locator in a low-speed mode, and controls the second drive motor to drive the motion camera 18 to move towards the second locator in a low-speed mode;

[0131] When the train model 2 reaches the first locator, when the Hall sensor in the first locator detects a magnetic field change, the encoder pulse count value of the first drive motor 5 is cleared, and the position when the train model 2 reaches the first locator is set as the initial position x 0,train ;

[0132] When the motion camera 18 reaches the second locator, when the Hall sensor in the second locator detects a magnetic field change, the encoder pulse count value of the second drive motor is cleared, and the position when the motion camera 18 reaches the second locator is set as the initial position x 0,camera .

[0133] Step 2: Set the experimental parameters, including: the length L of the tunnel model 1 tunnel , the length L of the optical dynamic tracking system bracket trace , the mass flow rate m of the gas in the flowmeter 12 set , the running speed v of the train model 1 set,train , the running speed v of the synchronous camera 18 set,camera , the running displacement x of the train model 1 set,train , the running displacement x of the synchronous camera 18 set,camera ;

[0134] Step 3: The control cabinet 20 starts the solenoid valve 10 and starts the flowmeter 12 to supply gas according to the set target mass flow rate m set , meanwhile, the control cabinet 20 triggers the high-voltage arc igniter to ignite the fire source, and synchronously starts the temperature probe to monitor the state of the fire source in real time.

[0135] Step 4: The flowmeter 12 collects the mass flow rate m real (t) in the gas supply pipeline at time t, and calculates the mass flow rate volatility at time t ; if is less than the set flow threshold, then execute Step 5, otherwise, use the PID control algorithm to adjust m real (t), and obtain the flow control value at time t using Equation (a) , so as to control the flowmeter 12 to adjust the mass flow rate of the gas introduced by itself, so that Less than the set flow threshold:

[0136] (a)

[0137] In formula (a), is the proportionality coefficient, is the integral coefficient, is the differential coefficient.

[0138] Step Five: The control cabinet 20 starts the high-speed acquisition device to collect the data of the thermocouple 31 and the heat flow meter 30;

[0139] Step Six: As Figure 7 shown, synchronously control the operation of the train model 1 and the motion camera 18:

[0140] Step 6.1: Obtain the control frequency f of the first motor 5 according to formula (b) train , to control the train model 1 to run at the running speed v set,train :

[0141] (b)

[0142] In formula (b), m is the module of the gear in the train model 1, Z is the number of teeth of the gear in the train model 1; N p is the number of pole pairs of the first motor 5.

[0143] Step 6.2: The control cabinet 20 uses the high-precision encoder built in the first motor 5 to collect the pulse signal N train (t) of the rotation angle of the first motor 5 at time t, so as to obtain the running speed of the train model 1 at time t by using formula (c) :

[0144] (c)

[0145] In formula (c), is the fixed angle corresponding to the rotation of the motor gear for a single pulse.

[0146] Step 6.3: The control cabinet 20 calculates the running speed error of the train model 1 at time t ;

[0147] Step 6.4: If is less than the set speed threshold, then execute Step Five, otherwise, use the PID control algorithm to adjust to obtain the control frequency of the first motor 5 at time t, so as to control the running speed of the train model 1 at time t to be less than the set speed threshold.

[0148] Step 6.5: If Ltrace <L tunnel , the control cabinet 20 calculates the delay start time t of the sports camera 18 delay =(L tunnel L trace ) / v train ; otherwise, let t delay =0; thus, start the sports camera 18 according to t delay .

[0149] Step 6.6: The control cabinet 20 calculates the running speed of the sports camera 18 at time t ; if is less than the set speed threshold, execute Step 6.7; otherwise, adjust according to the PID control algorithm for to control to be less than the set speed threshold.

[0150] Step 6.7: The control cabinet 20 calculates the actual displacement of the train model 1 at time t using equations (d) and (e) respectively and the actual displacement of the sports camera 18 at time t :

[0151] (d)

[0152] In equations (d) and (e), represents the single-pulse displacement, and ; N camera (t) is the pulse signal of the rotation angle of the second motor at time t.

[0153] Step 6.8: When , the control cabinet 20 controls the first drive motor 5 to apply a reverse torque, thereby decelerating and braking the train model 1; otherwise, assign t + 1 to t and then return to Step 6.2 to execute sequentially;

[0154] When , the control cabinet 20 controls the second drive motor to apply a reverse torque, thereby decelerating and braking the sports camera 18; otherwise, assign t + 1 to t and then return to Step 6.6 to execute sequentially.

[0155] Step Seven: After braking is completed, that is, N train (t)=0 and N cameraWhen (t) = 0, the control cabinet 20 closes the solenoid valve 10, resets the mass flow rate in the flowmeter 12 to zero, and turns off the temperature probe, high-speed acquisition device 26, and water cooling device. After data acquisition stops, it is encrypted and stored in a standardized format, and at the same time, a metadata file is generated to record the experimental parameters and equipment status. If the experiment is not terminated, the control cabinet 20 sends a reset command and starts to execute step one; if the experiment is terminated, the control cabinet 20 controls the test bench to power off, and at the same time generates a comprehensive report including the equipment operation log.

[0156] In this embodiment, a method for processing fire characteristic parameters based on a high-speed running train in a long tunnel section is applied to the above control system and is carried out according to the following steps:

[0157] Step I: Flame video dynamic stabilization:

[0158] Step 1.1 Through the interaction interface, select and frame the identification light area (ROI1) and its extended area (ROI2) in the first frame of the video for feature detection and dynamic tracking;

[0159] Step 1.2 Based on an improved ORB (Oriented FAST and Rotated BRIEF) feature point detection algorithm, perform feature detection on the selected identification light area (ROI1) in the first frame of the video and output the feature point set {p1, p2,..., p m};

[0160] Step 1.3 In the extended area (ROI2), use the optical flow method (Lucas-Kanade optical flow method) to track the identification light frame by frame according to the feature point set, and calculate the rigid motion parameters of the identification light between adjacent video frames (including translation vectors Δx, Δy and rotation angle θ);

[0161] Step 1.4 Construct an affine transformation matrix M, , and according to the inverse matrix of the affine transformation matrix Perform reverse affine transformation compensation on the video frame by frame to generate a stabilized flame video sequence, eliminating the picture jitter caused by the high-speed movement of the train model.

[0162] Step II: Flame feature parameter extraction:

[0163] Step 2.1 After obtaining the flame video sequence captured by the moving camera 18 after braking and performing stability processing, convert it from the RGB color space to the grayscale space, and then use the threshold segmentation algorithm to perform binary processing on each frame of the flame image in the grayscale flame video sequence to obtain a binary flame video sequence;

[0164] Step 2.2 Stack the binarized flame video sequences frame by frame, and count the frequency of the appearance of the flame at each pixel point, so as to construct the flame probability density matrix at the pixel point (x, y). , where is the binarized value at the pixel point (x, y) in the t-th frame of the flame image, and N is the total number of frames.

[0165] Step 2.3 According to the calibration parameters of the moving camera 18, map the pixel point (x, y) to the pixel point (X real , Y real ) in the actual physical coordinate system: , so as to construct the flame probability density matrix at the pixel point (X real , Y real ) in the actual physical coordinate system ; where ρ is the pixel resolution of the moving camera 18, and α is the spatial scale factor of the moving camera 18;

[0166] Step 2.4 Based on Extract the flame boundary and obtain the flame scale data, including: flame length L f , flame height H f .

[0167] Step III: Experimental data analysis and processing:

[0168] Step 3.1 According to the obtained flame scale data (flame length L f , flame height H f ), use equations (f) and (g) to establish a dimensionless flame length model and a dimensionless flame height model respectively:

[0169] (f)

[0170] (g)

[0171] In equations (f) and (g), is the dimensionless heat release rate of the heat source, is the dimensionless running speed of the train model, is the diameter of the fire head, is the calorific value of the fuel of the heat source, is the initial ambient density, is the specific heat capacity at constant pressure, is the initial ambient temperature, is the acceleration due to gravity.

[0172] Step 3.2: Based on the data collected by the thermocouples 31 and the heat flux meters 30 on the top plate and the bottom plate of the train model 2, plot a time series graph and calculate the average value of the stable section, so as to take the average value of the stable section of the thermocouple as the temperature value t of the train model 2 f , and take the product of the average value of the stable section of the heat flux meter and the correction coefficient as the heat flux value q of the train model 2 f ;

[0173] Step 3.3: Normalize the temperature value t f and the heat flux value q f respectively according to Equation (h) and Equation (i) to obtain the normalized temperature value and the normalized heat flux value :

[0174] (h)

[0175] (i)

[0176] In Equation (h) and Equation (i), represents the temperature rise on the top plate and the bottom plate of the train model 2, and , represents the peak value of the temperature rise on the top plate and the bottom plate of the train model 2, and , is the peak temperature on the top plate and the bottom plate of the train model 2.

[0177] Step 3.4: Establish a peak temperature rise model on the top plate and the bottom plate of the train model 2 according to Equation (j):

[0178] (j)

[0179] In Equation (j), is the peak temperature rise relational expression;

[0180] Establish a temperature distribution prediction model on the top plate and the bottom plate of the train model 2 according to Equation (k):

[0181] (k)

[0182] In Equation (k), is the temperature distribution relational expression; is the distance between the thermocouple position and the peak value of the temperature rise on the top plate and the bottom plate of the train model 2; is the characteristic scale of the fire source, and .

[0183] Step 3.5: Obtain the running train fire roof heat flux distribution characterization model according to Equation (l):

[0184] (l)

[0185] In formula (l), is the heat flux distribution relation.

[0186] Example 1: Simulation of roof fire.

[0187] Remove the top plate of the train model. Fix the fire head on the top plate of the train model by bolt connection and make it flush with the top plate of the train model. The outlet direction of the fire head faces the ceiling of the tunnel model. Install the high-frequency acquisition system, arrange thermocouples, heat flux meters, etc. on the top plate of the train model, and fix the high-speed acquisition device and water-cooling device inside the train model carriage. Connect the fire head to the gas supply pipeline, install the top plate of the train model on the train model, and set a high-voltage arc igniter and a temperature probe directly above the fire head on the top plate of the train model. Fix the motion camera on the first support plate of the camera of the optical dynamic tracking system, and adjust the height of the threaded connecting rod between the first support plate and the second support plate of the camera to adjust the shooting angle of the motion camera. Turn on the control cabinet, and conduct preliminary acquisition debugging on the high-frequency acquisition system and the optical dynamic tracking system to ensure that the two systems can effectively collect data. The control cabinet controls the train model to move towards the first locator direction and controls the motion camera to move towards the second locator direction to reset the train model and the motion camera. After the train model and the motion camera are reset, open the gas cylinder valve and the identification light of the train model, and then set the length of the tunnel model, the length of the optical dynamic tracking system bracket, the mass flow rate of the gas in the flow meter, the running speed of the train model and the motion camera, and the running displacement of the train model and the motion camera through the control cabinet. The control cabinet opens the solenoid valve, adjusts the mass flow rate of the gas introduced into the flow meter to the set value. At the same time, the control cabinet triggers the high-voltage arc igniter to start and ignite the fire source. After the mass flow rate of the gas introduced into the flow meter is stable, the control cabinet controls the train model and the motion camera to run synchronously according to the set parameters. After the train model and the motion camera run to the set running displacement of the train model and the motion camera, start braking and stop. The control cabinet closes the solenoid valve to stop the fuel gas supply at the fire head. At this time, the fire source goes out, and then immediately adjust and set the mass flow rate of the gas introduced into the flow meter to 0 to close the gas supply of the gas supply pipeline, and turn off the temperature probe, the high-speed acquisition device, and the water-cooling device. If the experiment is not over, wait until the temperature of the test bench drops to a lower temperature, reset the train model and the motion camera, and repeat the subsequent operations to conduct other working condition experiments. If the experiment is over, turn off the control cabinet, the identification light of the train model, the gas cylinder valve, etc.

[0188] Example 2: Simulation of underbody fire.

[0189] Remove the top plate of the train model, fix the glow plug to the bottom plate of the train model by bolt connection and make it flush with the bottom plate of the train model. The outlet direction of the glow plug faces the bottom plate of the tunnel model. Connect the glow plug to the gas supply pipeline, and set a high-voltage arc igniter and a temperature probe directly below the glow plug; Install the high-frequency acquisition system, arrange thermocouples, heat flux meters, etc. on the bottom plate of the train model, and fix the high-speed acquisition equipment and water-cooling equipment inside the train model carriage; Install the top plate of the train model on the train model to seal the train model; Fix the motion camera on the first support plate of the camera of the optical dynamic tracking system, and adjust the height of the threaded connecting rod between the first support plate of the camera and the second support plate of the camera to adjust the shooting angle of the motion camera; The control cabinet controls the train model to move towards the first locator and controls the motion camera to move towards the second locator to reset the train model and the motion camera; After the train model and the motion camera are reset, open the gas cylinder valve and the identification light of the train model, and then set the length of the tunnel model, the length of the optical dynamic tracking system bracket, the mass flow rate of the gas in the flowmeter, the running speed of the train model and the motion camera, and the running displacement of the train model and the motion camera through the control cabinet; The control cabinet opens the solenoid valve and adjusts the mass flow rate of the gas introduced into the flowmeter to the set value. At the same time, the control cabinet triggers the high-voltage arc igniter to start and ignite the fire source. After the mass flow rate of the gas introduced into the flowmeter is stable, the control cabinet controls the train model and the motion camera to run synchronously according to the set parameters. After the train model and the motion camera run to the set running displacement of the train model and the motion camera, start braking and stop; The control cabinet closes the solenoid valve to stop the fuel gas supply at the glow plug. At this time, the fire source goes out, and then immediately adjust and set the mass flow rate of the gas introduced into the flowmeter to 0 to close the gas supply of the gas supply pipeline, and turn off the temperature probe, high-speed acquisition equipment and water-cooling equipment; If the experiment is not over, wait for the temperature of the test bench to drop to a lower temperature, reset the train model and the motion camera, and repeat the subsequent operations to carry out other working condition experiments. If the experiment is over, turn off the control cabinet, the identification light of the train model, the gas cylinder valve, etc.

Claims

1. A dynamic fire field simulation and intelligent measurement and control experimental platform for tunnel high-speed trains, characterized in that, Including: Tunnel model (1), train model (2), high-speed meshing drive system, multi-modal fire scene simulation system, optical dynamic tracking system, high-frequency acquisition system, control cabinet (20); A sliding rod (23) and a rack (25) are integrated on the bottom plate of the tunnel model (1) to provide an operating track for the train model (2); the train model (2) runs on the track through a high-speed meshing drive system; The multi-modal fire scene simulation system is used to simulate fire scenes at different parts of the train model (2); The optical dynamic tracking system runs synchronously with the train model (2) and is used to capture the dynamic flame form of the train model (2) in real time; The high-frequency acquisition system is used to record temperature, heat flux and gas concentration parameters in real time; The control cabinet (20) is used to control the operation of the train model (2) and the optical dynamic tracking system, the fire intensity of the multi-modal fire scene simulation system, the shooting duration of the optical dynamic tracking system, and the start and stop of the high-frequency acquisition system.

2. The dynamic fire scene simulation and intelligent measurement and control experimental platform for tunnel high-speed trains according to claim 1, characterized in that, The tunnel model (1) and the train model (2) are arranged as follows: The tunnel model (1) is fixed on a tunnel model support (34), and the top plate of the tunnel model support (34) serves as the bottom plate of the tunnel model (1). The tunnel model (1) is spliced by multiple standard section models. Any standard section model is a U-shaped model composed of three aluminum alloy plates (32). A high-temperature fireproof board is provided inside the aluminum alloy plate (32), and high-temperature resistant glass (33) is provided on any side aluminum alloy plate (32); A card slot (24) is installed outside the top plate of the tunnel model support (34). Two sliding rods (23) are fixed at the center of the top plate, and a rack (25) is laid on the inner side of the top plate; Two tunnel model limiters (29) are installed at both ends of the top plate of the tunnel model support (34); A first locator is installed on the top plate of the tunnel model support (34) at the starting side of the train model (2) operation; The train model (2) is divided into a straight section body and an arc section head; The train model (2) is spliced by aluminum alloy plates (32). The train model (2) is fixed on a train model support flat plate (3) through two support rods. A first sliding bearing is installed at the bottom of the train model support flat plate (3), and the first sliding bearing is arranged on two sliding rods (23) of the tunnel support top plate (34); A battery-powered identification lamp (4) is provided at the arc section head of the train model.

3. The dynamic fire field simulation and intelligent measurement and control experimental platform for tunnel high-speed trains according to claim 2, characterized in that, The high-speed meshing drive system includes: a first gear (22), a first drive motor (5), a first motor support frame (6), a first connecting plate (21), a first power line (7), a first control line (8), a first armored chain (9); The first motor support frame (6) is assembled by three aluminum alloy plates (32). The first drive motor (5) is arranged on the inner bottom surface of the motor support frame (6), and the first drive motor (5) is connected to the gear (22) through a gear shaft; The gear (22) meshes with the rack (25) on the top plate of the tunnel model support; The bottom surface of the motor support frame (6) is connected to the second sliding bearing, and the second sliding bearing is arranged on two sliding rods (23) of the tunnel support roof (34) and is behind the operating direction of the first sliding bearing; One side of the motor support frame (6) in the same direction as the running direction of the train model (2) is connected to the support flat plate (3) of the train model (2) through a connecting plate (21), so that the train model (2) is driven by the first driving motor (5) to slide and run on the two sliding rods (23) through the first sliding bearing and the second sliding bearing; The motor support frame (6) on the side opposite to the running direction of the train model (2) is connected to the first drag chain (9), and the first drag chain (9) is arranged in the card slot (24) of the tunnel model support roof (34); the power line (7) and the control line (8) are arranged inside the drag chain (9) and are connected to the control cabinet (20), so as to provide power supply and control signals for the first driving motor (5).

4. The dynamic fire field simulation and intelligent measurement and control experimental platform for tunnel high-speed trains according to claim 3, wherein The multimodal fire scene simulation system includes: a fire head (13), an electromagnetic valve (10), an electromagnetic valve power supply line, a flow meter (12), a first gas supply pipeline (14), a second gas supply pipeline (15), a third gas supply pipeline (16), a gas cylinder (11), a high-voltage arc igniter, and a temperature probe; The fire head (13) includes: an inner layer gas supply member (35), an outer layer sleeve (36), and the inner layer gas supply member (35) includes: a gas supply head (37), a pneumatic joint (38); The inside of the gas supply head (37) is provided with a gas supply passage (39) with air holes (40), and both ends of the gas supply head (37) are respectively threadedly connected to the pneumatic joint (38) and the outer layer sleeve (36); and there is an annular gap between the gas supply head (37) and the outer layer sleeve (36) for outer layer gas supply; The fire head (13) is fixed on the train model (2) by threaded connection; a high-voltage arc igniter and a temperature probe are arranged directly above the fire head; the gas cylinder (11) is connected to the third gas supply pipeline (16) through a pressure reducing valve, the third gas supply pipeline (16) is connected to the inlet of the flow meter (12), the outlet of the flow meter (12) is connected to the second gas supply pipeline (15), the second gas supply pipeline (15) is arranged inside the drag chain (9) and is connected to the electromagnetic valve (10), the electromagnetic valve (10) is connected to the first gas supply pipeline (14), and the first gas supply pipeline (14) is connected to the pneumatic joint of the fire head (13); The flow meter (12) controls the power of the fire source by adjusting the mass flow of the gas introduced.

5. The tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experimental platform according to claim 4, wherein, The optical dynamic tracking system includes: an optical dynamic tracking system support frame, a motion camera (18), a first camera support flat plate (19), a second camera support flat plate (17), a synchronous tracking power system, two optical dynamic tracking system limiters, and a second positioner; A card slot is installed on the outer side of the top plate of the optical dynamic tracking system bracket. Two sliding rods are fixed at the center of the top plate, and a rack is laid on the inner side of the top plate; Two optical dynamic tracking system limiters are installed at both ends of the top plate of the optical dynamic tracking system bracket; A second positioner is installed on the top plate of the optical dynamic tracking system bracket on the starting side of the operation of the moving camera (18). The moving camera (18) is fixed on the first camera support flat plate (19). The first camera support flat plate (19) is connected to the second camera support flat plate (17) through two threaded connecting rods. A third sliding bearing is installed at the bottom of the second camera support flat plate (17). The third sliding bearing is arranged on the two sliding rods of the top plate of the optical dynamic tracking system bracket.

6. The tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experimental platform according to claim 5, characterized in that, The synchronous tracking power system includes: a second gear, a second driving motor, a second motor support frame, a second connecting plate, a second power line, a second control line, and a second tank chain. The second motor support frame is an aluminum alloy flat plate. The second driving motor is arranged on the inner bottom surface of the second motor support frame, and the second driving motor is connected to the second gear through a gear shaft; The second gear meshes with the rack on the optical dynamic tracking system bracket. The bottom surface of the second motor support frame is connected to a fourth sliding bearing. The fourth sliding bearing is arranged on the two sliding rods of the top plate of the optical dynamic tracking system bracket and is behind the running direction of the third sliding bearing. On the side of the second motor support frame in the same running direction as the moving camera (18), it is connected to the second support flat plate (17) of the moving camera (18) through a second connecting plate. Thus, the second driving motor drives the moving camera (18) to slide and run on the two sliding rods through the third sliding bearing and the fourth sliding bearing. On the side of the second motor support frame opposite to the running direction of the moving camera (18), it is connected to the second tank chain. The second tank chain is arranged in the card slot on the top plate of the optical dynamic tracking system bracket; The second power line and the second control line are arranged inside the second tank chain and are connected to the control cabinet to provide power and control signals for the second driving motor.

7. The dynamic fire scene simulation and intelligent measurement and control experimental platform for tunnel high-speed trains according to claim 6, characterized in that The high-frequency acquisition system includes: a thermocouple (31), a heat flux meter (30), a high-speed acquisition device (26), and a water cooling device. The water cooling device includes: a water pump (27), a water tank (28), and a water pump power line. The thermocouple (31) and the heat flux meter (30) are arranged on the top plate and the bottom plate of the train model (2). The wiring of the thermocouple (31) and the heat flux meter (30) is connected to the high-speed acquisition device (26); The water pump (27) is fixed at the bottom of the water tank (28). The water inlet pipe of the heat flux meter (30) is connected to the water outlet pipe of the water pump (27). The water outlet pipe of the heat flux meter (30) is inserted into the water tank (28); The power line (7) provides power for the water pump (27); The high-speed acquisition device (26) is powered by a battery.

8. A control system for the tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experiment platform according to claim 7, characterized in that, It is carried out according to the following steps: Step 1: The control cabinet (20) controls the first drive motor (5) to drive the train model (2) towards the first locator in the low-speed mode, and controls the second drive motor to drive the motion camera (18) towards the second locator in the low-speed mode; When the train model (2) reaches the first locator, when the Hall sensor in the first locator detects a magnetic field change, the encoder pulse count value of the first drive motor (5) is cleared, and the position when the train model (2) reaches the first locator is set as the initial position x 0,train ; When the action camera (18) reaches the second locator, when the Hall sensor in the second locator detects a magnetic field change, the encoder pulse count value of the second drive motor is cleared, and the position when the action camera (18) reaches the second locator is set as the initial position x 0,camera ; Step 2: Set the experimental parameters, including: the length L of the tunnel model (1) tunnel , the length L of the optical dynamic tracking system bracket trace , the mass flow rate m of the gas in the flowmeter (12) set , the running speed v of the train model (1) set,train , the running speed v of the synchronous camera (18) set,camera , the running displacement x of the train model (1) set,train , the running displacement x of the synchronous camera (18) set,camera ; Step 3: The control cabinet 20 activates the solenoid valve 10 and activates the flowmeter 12 to supply gas according to the set target mass flow rate m set Meanwhile, the control cabinet 20 triggers the high-voltage arc igniter to ignite the fire source, and simultaneously activates the temperature probe to monitor the state of the fire source in real time; Step Four: The flowmeter 12 collects the mass flow rate m real (t) at time t in the gas supply pipeline, and calculates the mass flow rate volatility at time t ; If is less than the set flow threshold, then execute Step Five; otherwise, use the PID control algorithm to adjust m real (t), and obtain the flow control value at time t using Equation (a) , thereby controlling the flowmeter 12 to adjust the mass flow rate of the gas introduced by itself so that is less than the set flow threshold: (a) In formula (a), is a proportionality coefficient, is an integral coefficient, is a differential coefficient; Step 5: The control cabinet (20) triggers the high-voltage arc igniter to ignite the fire source, and simultaneously starts the temperature probe to monitor the state of the fire source in real time; the control cabinet (20) starts the high-speed acquisition device for acquiring the data of the thermocouple (31) and the heat flux meter (30); Step 6: Synchronously control the operations of the train model (1) and the motion camera (18); Step Seven: When N train (t) = 0 and N camera (t) = 0, it indicates that the braking is completed. The control cabinet (20) closes the solenoid valve (10), resets the mass flow rate in the flowmeter (12) to zero, and turns off the temperature probe, the high-speed acquisition device (26), and the water cooling device.

9. A control system for the tunnel high-speed train dynamic fire field simulation and intelligent measurement and control experimental platform according to claim 8, characterized in that, The Step 6 includes: Step 6.1: Obtain the control frequency f of the first motor (5) according to formula (b) train , so as to control the train model (1) to run at the running speed v set,train : (b) In formula (b), m is the module of the gear in the train model (1), Z is the number of teeth of the gear in the train model (1); N p is the number of pole pairs of the first motor (5); Step 6.2: The control cabinet (20) uses the high-precision encoder built in the drive motor (5) to collect the pulse signal N of the rotation angle of the first motor (5) at time t train (t), and thus obtains the running speed of the train model (1) at time t by using Equation (c) : (c) In formula (c), is the fixed angle corresponding to the rotation of the motor gear for a single pulse; Step 6.3: The control cabinet (20) calculates the running speed error of the train model (1) at time t ; Step 6.4: If is less than the set speed threshold, then execute Step Five; otherwise, use the PID control algorithm to adjust it to obtain the control frequency of the first motor (5) at time t to control the running speed of the train model (1) at time t is less than the set speed threshold; Step 6.5: If L trace < L tunnel , then the control cabinet (20) calculates the delay start time t delay = (L tunnel L trace ) / v train ; otherwise, let t delay = 0; thus starting the action camera (18) according to t delay ; Step 6.6: The control cabinet (20) calculates the running speed of the action camera (18) at time t ; If is less than the set speed threshold, then step 6.7 is executed. Otherwise, adjust according to the PID control algorithm for to control is less than the set speed threshold; Step 6.7: The control cabinet (20) calculates the actual displacement of the train model (1) at time t by using Equation (d) and Equation (e) respectively and the actual displacement of the motion camera (18) at time t : (d) (e) In formulas (d) and (e), represents the single-pulse displacement, and ; N camera (t) is the pulse signal of the rotation angle of the second motor at time t; Step 6.8: When occurs, the control cabinet (20) controls the first drive motor (5) to apply a reverse torque, thereby decelerating and braking the train model (1). Otherwise, after assigning t + 1 to t, return to Step 6.2 and execute sequentially; When occurs, the control cabinet (20) controls the second drive motor to apply a reverse torque to decelerate and brake the action camera (18). Otherwise, after assigning t + 1 to t, return to step 6.6 and execute sequentially.

10. A method for processing fire characteristic parameters of the control system according to claim 7, characterized in that, It is carried out according to the following steps: Step I: After obtaining the flame video sequence captured by the motion camera (18) after braking completion and performing stability processing, convert it from the RGB color space to the grayscale space, so as to perform binary processing on each frame of flame image in the grayscale flame video sequence by using the threshold segmentation algorithm to obtain the binary flame video sequence; Step II: Stack the binary flame video sequences frame by frame, and count the frequency of the appearance of the flame at each pixel point, so as to construct the flame probability density matrix at the pixel point (x, y). , where is the binary value at the pixel point (x, y) in the t-th frame of the flame image, and N is the total number of frames. Step III: According to the calibration parameters of the action camera (18), map the pixel point (x, y) to the pixel point (X real , Y real ) in the actual physical coordinate system: , thereby constructing the flame probability density matrix at the pixel point (X real , Y real ) in the actual physical coordinate system ; where ρ is the pixel resolution of the action camera (18), and α is the spatial scale factor of the action camera (18). Step IV: Based on Extract the flame boundary and obtain the flame scale data, including: flame length L f , flame height H f ; Step V: Use Equation (f) and Equation (g) to establish the dimensionless flame length model and the dimensionless flame height model respectively: (f) (g) In equations (f) and (g), is the dimensionless heat release rate of the heat source, is the dimensionless running speed of the train model, is the diameter of the fire head, is the calorific value of the fuel of the heat source, is the initial ambient density, is the specific heat capacity at constant pressure, is the initial ambient temperature, is the acceleration due to gravity; is the flame length relationship; is the flame height relationship; Step VI: Based on the data collected by the thermocouples (31) and heat flux meters (30) on the top and bottom plates of the train model (2), plot a time series graph and calculate the average value of the stable section, so as to take the average value of the stable section of the thermocouple as the temperature value t of the train model (2). f Take the product of the average value of the stable section of the heat flux meter and the correction coefficient as the heat flux value q of the train model (2). f ; Step VII: Normalize the temperature value t f and the heat flux value q f respectively according to Equation (h) and Equation (i) to obtain the normalized temperature value and the normalized heat flux value : (h) (i) In formula (h) and formula (i), represents the temperature rise on the top plate and the bottom plate of the train model (2), and , represents the peak value of the temperature rise on the top plate and the bottom plate of the train model (2), and , is the peak temperature on the top plate and the bottom plate of the train model (2); Step VIII: Establish the peak temperature rise model on the top plate and bottom plate of the train model (2) according to Equation (j): (j) In formula (j), is the relationship formula for the peak temperature rise; Establish the temperature distribution prediction model on the top plate and bottom plate of the train model (2) according to Equation (k): (k) In formula (k), is the temperature distribution relation; is the distance between the thermocouple position and the peak temperature rise on the top and bottom plates of the train model (2); is the characteristic scale of the fire source, and ; Step IX: Obtain the running train fire roof heat flux distribution characterization model according to Equation (l): (l) In formula (l), is the heat flux distribution relation.

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