Infrared intelligent snow melting and deicing method and device for non-intrusive tunnel portal section

Abstract

The invention provides an infrared intelligent snow melting and deicing method and device for a non-intrusive tunnel portal section, and relates to the technical field of snow melting and deicing, and the method comprises the steps: constructing an image recognition model, training the image recognition model, and obtaining an image recognition network; tunnel portal section images are obtained in real time, the tunnel portal section images are recognized through an image recognition network, a snow accumulation and ice storage area is obtained, and the tunnel portal section images are obtained through cameras arranged on the two sides of a tunnel portal section road; acquiring sensing data of the accumulated snow ice storage area; and calculating the sensing data to obtain regulation and control data, and controlling an infrared spotlight to melt snow and remove ice through the regulation and control data. The tunnel portal section snow melting and deicing method solves the problems that an existing tunnel portal section snow melting and deicing method is low in efficiency, has large harm to the environment and is large in overhaul difficulty.

Description

Technical Field

[0001] The present invention relates to the technical field of snow melting and deicing, and in particular to a non-invasive tunnel portal section infrared intelligent snow melting and deicing method, device, equipment and a readable storage medium. Background Art

[0002] Different from snow and ice on the road, the tunnel entrance section has very short sunshine hours in winter due to environmental factors such as climate and altitude, which leads to severe snow and ice accumulation in winter. This is extremely detrimental to tunnel driving safety.

[0003] At present, the commonly used methods include artificial shaved ice, chemical ice melting, electric heating, etc. However, these methods have great limitations. Artificial shaved ice requires a lot of manpower and material resources, and has obvious lag in the effect of snow melting and ice removal; although chemical ice melting has a good effect of snow melting and ice removal, it is easy to cause chemical corrosion of the structure and has great harm to the environment; the electric heating method is extremely cumbersome when laying equipment and difficult to maintain. Therefore, snow melting and ice removal in the tunnel entrance section has become a thorny problem, and on-site personnel need an efficient, convenient, green and environmentally friendly method. Summary of the invention

[0004] The purpose of the present invention is to provide a non-invasive infrared intelligent snow melting and ice removal method and device for tunnel entrance section to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a non-invasive infrared intelligent snow melting and ice removal method for a tunnel entrance section, comprising:

[0006] Constructing an image recognition model, and training the image recognition model to obtain an image recognition network;

[0007] Acquire the tunnel entrance section image in real time, identify the tunnel entrance section image through an image recognition network, and obtain the snow and ice accumulation area, wherein the tunnel entrance section image is acquired through cameras arranged on both sides of the tunnel entrance section road;

[0008] Acquire sensor data of snow and ice accumulation areas, wherein the sensor data includes temperature data, humidity data, thickness data and friction data;

[0009] The sensing data is calculated to obtain control data, and the infrared spotlight is controlled by the control data to melt snow and remove ice. The control data includes the position status and actual thickness of each position in the snow and ice storage area.

[0010] In a second aspect, the present application also provides a non-invasive tunnel portal section infrared intelligent snow melting and ice removal device, comprising:

[0011] A model building module, used to build an image recognition model, train the image recognition model, and obtain an image recognition network;

[0012] A recognition module is used to obtain a tunnel entrance section image in real time, and recognize the tunnel entrance section image through an image recognition network to obtain a snow and ice accumulation area, wherein the tunnel entrance section image is obtained through cameras arranged on both sides of the tunnel entrance section road;

[0013] An acquisition module, used to acquire sensor data of the snow and ice accumulation area, wherein the sensor data includes temperature data, humidity data, thickness data and friction data;

[0014] The control module is used to calculate the sensor data to obtain control data, and control the infrared spotlights to melt snow and remove ice through the control data. The control data includes the position status and actual thickness of each position in the snow and ice storage area.

[0015] The beneficial effects of the present invention are as follows: through a non-invasive snow melting and de-icing method, there is no need to bury a heating device under the ground surface. Various sensors are pre-buried under the road surface of the tunnel entrance section and will not be damaged by the equipment on the ground. Cameras and infrared spotlights are pre-placed in the air and act on the ground surface. In addition, snow melting and de-icing are automatically completed by a system integrated with a preset model, realizing automatic and intelligent work all day long. The snow melting and de-icing process is safe, convenient and efficient. High-temperature and high-heat infrared rays are used for physical snow melting and de-icing, which will not produce additional harmful substances and achieve green environmental protection.

[0016] Other features and advantages of the present invention will be set forth in the following description, and in part will become apparent from the description, or may be understood by practicing embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a schematic diagram of the process of the non-invasive infrared intelligent snow melting and ice removal method for tunnel portal section described in an embodiment of the present invention;

[0019] Figure 2 It is a schematic diagram of the structure of the non-invasive tunnel entrance section infrared intelligent snow-melting and ice-removing equipment described in an embodiment of the present invention.

[0020] Markings in the figure: 800, non-invasive tunnel portal section infrared intelligent snow-melting and ice-removing equipment; 801, processor; 802, memory; 803, multimedia component; 804, I / O interface; 805, communication component. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0022] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0023] Embodiment 1:

[0024] This embodiment provides a non-invasive infrared intelligent snow-melting and ice-removing method for a tunnel entrance section.

[0025] See also Figure 1 , the figure shows that the method includes step S100, step S200, step S300, and step S400.

[0026] Step S100: constructing an image recognition model, and training the image recognition model to obtain an image recognition network;

[0027] The step S100 includes:

[0028] Collect multiple images of snow and ice at the tunnel entrance;

[0029] Marking the snow and ice layers in all the snow and ice images to obtain a snow and ice training set;

[0030] Build an image recognition model;

[0031] Based on the snow and ice training set, an image recognition model is trained through supervised learning to obtain an image recognition network, and the image recognition model adopts a YOLO network.

[0032] In this embodiment, the image recognition model is trained by a snow and ice training set in image format, and is tested by a test set in image format and video format, respectively, so that the image recognition network has good performance in real-time detection.

[0033] Step S200: acquiring a tunnel entrance section image in real time, identifying the tunnel entrance section image through an image recognition network, and obtaining a snow and ice accumulation area, wherein the tunnel entrance section image is acquired through cameras arranged on both sides of the tunnel entrance section road;

[0034] Step S300: Acquire sensor data of the snow and ice accumulation area, wherein the sensor data includes temperature data, humidity data, thickness data and friction data;

[0035] The step S300 includes:

[0036] A single temperature sensor, a single humidity sensor, a single thickness sensor and a single embedded friction sensor are used as a group of coordinated sensors;

[0037] The plurality of cooperative sensors are arranged under the surface of different measuring points of the road in the tunnel entrance section;

[0038] The temperature data at the measuring point is obtained through the temperature sensor, the humidity data at the measuring point is obtained through the humidity sensor, the thickness data of the snow or ice layer at the measuring point is obtained through the thickness sensor, and the friction data at the measuring point is obtained through the embedded friction sensor.

[0039] In this embodiment, the temperature sensor, the humidity sensor, the thickness sensor, and the embedded friction sensor are combined in parallel to form a group of multi-sensing cooperative sensors.

[0040] Step S400: Calculate the sensing data to obtain control data, and control the infrared spotlights to melt snow and remove ice according to the control data. The control data includes the position status and actual thickness of each position in the snow and ice accumulation area.

[0041] The step S400 includes:

[0042] defining a state function of a snow and ice accumulation area based on the temperature data, and calculating sensible enthalpy based on the temperature data;

[0043] The expression of the state function is:

[0044]

[0045] In the formula, β represents the state function, T represents the material temperature, which is obtained from the temperature data, and T melt represents the melting temperature, T solidrepresents the freezing point temperature, T melt =T solid =0℃, β=1, it indicates a normal state, and β=0, it indicates an ice and snow state.

[0046] The substance refers to ice, snow or water in the snow and ice storage area.

[0047] In thermodynamics, enthalpy is used to represent the energy state of a substance. The change in enthalpy caused by the temperature deviation from the reference temperature is called sensible enthalpy.

[0048] The expression of the sensible enthalpy is:

[0049]

[0050] In the formula, h represents sensible enthalpy, h ref represents the reference enthalpy at the reference temperature, T ref represents the reference temperature, T represents the material temperature, c p Represents specific heat at constant pressure.

[0051] constructing a two-dimensional heat conduction equation based on the temperature data and the sensible enthalpy;

[0052] In this embodiment, the two-dimensional heat conduction equation describes the energy change of water or ice in the plane of the snow and ice accumulation area.

[0053] The expression of the two-dimensional heat conduction equation is:

[0054]

[0055]

[0056] ΔH=βL

[0057] In the formula, represents partial derivative, ρ represents the density of water or ice, h represents sensible enthalpy, t represents time, T represents the temperature of the substance, λ represents the thermal conductivity of water or ice, S h It represents the source term, reflecting the release or absorption of latent heat of melting during the phase change of water ice. ΔH represents the latent heat of phase change. L represents the latent heat of melting. L = 334 kJ / kg. x and y represent the horizontal and vertical coordinates in the snow and ice storage area, respectively.

[0058] Based on the two-dimensional heat conduction equation and the state function, calculating the position state of each position in the snow and ice accumulation area, wherein the position state includes a normal state and an ice and snow state;

[0059] The two-dimensional heat conduction equation and the state function form a coupling equation to describe the dynamic changes between the material state (such as ice, snow or water) and the temperature distribution. By numerically solving the coupling equation, the temperature distribution of the material and its material state can be obtained at any time, that is, the position state of each location in the snow and ice accumulation area at each moment, among which water accumulation is a normal state.

[0060] Calculating the friction coefficient of the ice and snow state based on the friction data;

[0061] The calculation formula of the friction coefficient is:

[0062]

[0063] Where u is the friction coefficient, F friction represents the friction force, F nromal Represents the normal force applied to the embedded friction sensor.

[0064] identifying a specific state of ice and snow based on the friction coefficient, the specific state including an ice layer state and a snow accumulation state;

[0065] An actual thickness of the specific state is calculated based on the thickness data.

[0066] In this embodiment, the friction coefficient of ice is between 0.1 and 0.3, and the friction coefficient of snow is between 0.3 and 0.6. Therefore, u=0.3 is used as the threshold value. When u<0.3, the state is determined to be an ice layer, and when u≥0.3, the state is determined to be snow accumulation. Finally, according to the thickness data output by the sensor, the actual thickness of the specific state is obtained, where 5 cm is used as the threshold value. A thickness less than 5 cm is a thin layer, and vice versa.

[0067] Through the above steps, the state of the snow and ice accumulation area can be obtained, including a thin snow accumulation state, a thick snow accumulation state, a thin ice layer state, a thick ice layer state and a normal state.

[0068] The step S400 further includes:

[0069] Acquire the mass of ice and snow based on the actual thickness, and calculate the energy demand for snow melting and de-icing through the mass of ice and snow and the humidity data;

[0070] The calculation formula for the energy demand for snow melting and ice removal is:

[0071] Q=m×L f (H)

[0072] L f (H)=L f ×(1-k×(H / 100))

[0073] m=h'×A×ρ

[0074] Where Q represents the energy required for snow melting and ice removal, m represents the mass of snow or ice in kilograms, and L f (H) represents the humidity-adjusted latent heat of fusion, H represents humidity, obtained from humidity data, and L f It represents the melting latent heat of snow or ice. The melting latent heat of ice is 334000 J / kg, and the melting latent heat of snow is 200000 J / kg. k represents the empirical coefficient, which is 0.2. h' represents the actual thickness. A represents the heating area, in m 2 , ρ represents the density of water or ice, the density of ice is 917kg / m 3 , the density of snow is 150kg / m 3 .

[0075] Calculating the required power for snow melting and ice removal based on the energy demand;

[0076] The calculation formula of the required power is:

[0077]

[0078] Where P is the power required for snow melting and deicing, Q is the energy demand for snow melting and deicing, and t' is the heating time.

[0079] The direction and angle of the infrared spotlights are adjusted according to the position status of each position in the snow and ice storage area, the actual power of the infrared spotlights is adjusted according to the required power, and snow melting and ice removal are carried out based on the infrared spotlights. The infrared spotlights are set on both sides of the road in the tunnel entrance section.

[0080] In this embodiment, lower power can be used in thin snow and thin ice states, and the actual power is 50%-70% of the required power P. Thick snow and thick ice states require higher power, and the actual power is 100%-120% of the required power P.

[0081] In this embodiment, the camera is turned on to take pictures of the tunnel entrance section throughout the day, the snow and ice areas are identified through the image recognition network, and the specific status of each position in the snow and ice areas is analyzed, and the direction, angle and actual power of the infrared spotlight are adjusted to perform infrared snow melting and ice removal operations until the snow melting and ice removal are stopped when it is in a normal state, and the operation of the infrared spotlight is terminated. The entire process can be automatically operated, achieving a safe, convenient and efficient effect.

[0082] Moreover, the camera and infrared spotlight can be installed on any component and are easy to disassemble, making the equipment easy to install and maintain. At the same time, infrared snow melting and ice removal are used, and high-temperature and high-heat infrared rays are used for physical snow melting and ice removal. No additional harmful substances will be produced, and it can achieve green and environmental protection.

[0083] In the step S400, before controlling the infrared spotlights to melt snow and remove ice by the control data, the method further includes:

[0084] Set the weight parameters of sensor data;

[0085] Calculating the safety factor of the tunnel portal section based on the sensor data and the weight parameter;

[0086] The calculation formula of the safety factor is:

[0087]

[0088] Where S represents the safety factor, α represents the friction coefficient weight parameter, u represents the friction coefficient, β' represents the temperature weight parameter, T represents the material temperature, T0 represents the safety temperature threshold, γ represents the humidity weight parameter, H represents humidity, σ represents the thickness weight parameter, and D represents thickness.

[0089] Driving warning is performed based on the safety factor.

[0090] In this embodiment, the higher the safety factor, the higher the driving safety. When S>1, it is safe and suitable for driving. When 0<S≤1, it means that careful driving is required. When S≤0, it means that driving is unsafe and it is recommended to stop driving.

[0091] Embodiment 2:

[0092] This embodiment provides a non-invasive tunnel entrance section infrared intelligent snow melting and ice removal device, the device comprising:

[0093] A model building module, used to build an image recognition model, train the image recognition model, and obtain an image recognition network;

[0094] A recognition module is used to obtain a tunnel entrance section image in real time, and recognize the tunnel entrance section image through an image recognition network to obtain a snow and ice accumulation area, wherein the tunnel entrance section image is obtained through cameras arranged on both sides of the tunnel entrance section road;

[0095] An acquisition module, used to acquire sensor data of the snow and ice accumulation area, wherein the sensor data includes temperature data, humidity data, thickness data and friction data;

[0096] The control module is used to calculate the sensor data to obtain control data, and control the infrared spotlights to melt snow and remove ice through the control data. The control data includes the position status and actual thickness of each position in the snow and ice storage area.

[0097] The model building module comprises:

[0098] A collection unit, used for collecting multiple images of snow and ice accumulation at the tunnel entrance section;

[0099] A marking unit, used for marking the snow and ice layers in all the snow and ice images to obtain a snow and ice training set;

[0100] A first construction unit, used to construct an image recognition model;

[0101] The training unit is used to train the image recognition model through supervised learning based on the snow and ice training set to obtain an image recognition network, wherein the image recognition model adopts a YOLO network.

[0102] The acquisition module comprises:

[0103] A sensor composition unit for combining a single temperature sensor, a single humidity sensor, a single thickness sensor, and a single embedded friction sensor as a group of coordinated sensors;

[0104] A sensor setting unit, used to set a plurality of the cooperative sensors under the surface of different measuring points of the road in the tunnel entrance section;

[0105] The first acquisition unit is used to acquire temperature data at a measuring point through a temperature sensor, acquire humidity data at a measuring point through a humidity sensor, acquire thickness data of snow or ice at a measuring point through a thickness sensor, and acquire friction data at a measuring point through an embedded friction sensor.

[0106] The control module comprises:

[0107] A first calculation unit, configured to define a state function of a snow and ice accumulation area based on the temperature data, and calculate a sensible enthalpy based on the temperature data;

[0108] A second construction unit, configured to construct a two-dimensional heat conduction equation based on the temperature data and the sensible enthalpy;

[0109] A second calculation unit is used to calculate the position state of each position in the snow and ice storage area based on the two-dimensional heat conduction equation and the state function, wherein the position state includes a normal state and an ice and snow state;

[0110] A third calculation unit, configured to calculate the friction coefficient of the ice and snow state based on the friction data;

[0111] an identification unit, configured to identify a specific state of ice and snow based on the friction coefficient, wherein the specific state includes an ice layer state and a snow accumulation state;

[0112] A fourth calculation unit is used to calculate the actual thickness of the specific state based on the thickness data.

[0113] The control module further includes:

[0114] A second acquisition unit is used to acquire the mass of ice and snow based on the actual thickness, and calculate the energy demand for snow melting and de-icing through the mass of ice and snow and the humidity data;

[0115] a fifth calculation unit, configured to calculate the power required for snow melting and ice removal based on the energy demand;

[0116] The control unit is used to adjust the direction and angle of the infrared spotlight according to the position status of each position in the snow and ice storage area, adjust the actual power of the infrared spotlight according to the required power, and melt snow and de-ice based on the infrared spotlight. The infrared spotlights are set on both sides of the road in the tunnel entrance section.

[0117] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0118] Embodiment 3:

[0119] Corresponding to the above method embodiment, a non-invasive tunnel entrance section infrared intelligent snow-melting and ice-destroying equipment is also provided in this embodiment. The non-invasive tunnel entrance section infrared intelligent snow-melting and ice-destroying equipment described below and the non-invasive tunnel entrance section infrared intelligent snow-melting and ice-destroying method described above can be referred to each other.

[0120] Figure 2 FIG. 8 is a block diagram of a non-invasive tunnel portal infrared intelligent snow melting and ice removal device 800 according to an exemplary embodiment. Figure 2 As shown, the non-invasive tunnel entrance infrared intelligent snow melting and deicing device 800 may include: a processor 801, a memory 802. The non-invasive tunnel entrance infrared intelligent snow melting and deicing device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0121] The processor 801 is used to control the overall operation of the non-invasive tunnel entrance infrared intelligent snow melting and deicing device 800 to complete all or part of the steps in the above-mentioned non-invasive tunnel entrance infrared intelligent snow melting and deicing method. The memory 802 is used to store various types of data to support the operation of the non-invasive tunnel entrance infrared intelligent snow melting and deicing device 800, and these data may include, for example, instructions for any application or method operated on the non-invasive tunnel entrance infrared intelligent snow melting and deicing device 800, as well as application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the non-invasive tunnel entrance section infrared intelligent snow melting and ice removal equipment 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 can include: Wi-Fi module, Bluetooth module, NFC module.

[0122] In an exemplary embodiment, the non-invasive tunnel entrance infrared intelligent snow melting and ice removal equipment 800 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned non-invasive tunnel entrance infrared intelligent snow melting and ice removal method.

[0123] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned non-invasive tunnel entrance infrared intelligent snow melting and deicing method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions can be executed by the processor 801 of the non-invasive tunnel entrance infrared intelligent snow melting and deicing device 800 to complete the above-mentioned non-invasive tunnel entrance infrared intelligent snow melting and deicing method.

[0124] Embodiment 4:

[0125] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the non-invasive tunnel portal section infrared intelligent snow melting and ice removal method described above can be referenced to each other.

[0126] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the non-invasive infrared intelligent snow-melting and ice-removing method for a tunnel portal section of the above method embodiment.

[0127] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0128] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0129] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A non-invasive infrared intelligent snow-melting and ice-removing method for tunnel portals, characterized in that: include: Constructing an image recognition model, and training the image recognition model to obtain an image recognition network; Acquire the tunnel entrance section image in real time, identify the tunnel entrance section image through an image recognition network, and obtain the snow and ice accumulation area, wherein the tunnel entrance section image is acquired through cameras arranged on both sides of the tunnel entrance section road; Acquire sensor data of snow and ice accumulation areas, wherein the sensor data includes temperature data, humidity data, thickness data and friction data; The sensing data is calculated to obtain control data, and the infrared spotlight is controlled by the control data to melt snow and remove ice. The control data includes the position status and actual thickness of each position in the snow and ice storage area.

2. The non-invasive infrared intelligent snow-melting and ice-removing method for tunnel portal section according to claim 1 is characterized in that: Constructing an image recognition model and training the image recognition model to obtain an image recognition network, including: Collect multiple images of snow and ice at the tunnel entrance; Marking the snow and ice layers in all the snow and ice images to obtain a snow and ice training set; Build an image recognition model; Based on the snow and ice training set, an image recognition model is trained through supervised learning to obtain an image recognition network, and the image recognition model adopts a YOLO network.

3. The non-invasive infrared intelligent snow-melting and ice-removing method for tunnel portal section according to claim 1 is characterized in that: Acquire sensor data of snow and ice accumulation areas, including; A single temperature sensor, a single humidity sensor, a single thickness sensor and a single embedded friction sensor are used as a group of coordinated sensors; The plurality of cooperative sensors are arranged under the surface of different measuring points of the road in the tunnel entrance section; The temperature data at the measuring point is obtained through the temperature sensor, the humidity data at the measuring point is obtained through the humidity sensor, the thickness data of the snow or ice layer at the measuring point is obtained through the thickness sensor, and the friction data at the measuring point is obtained through the embedded friction sensor.

4. The non-invasive infrared intelligent snow melting and ice removal method for tunnel portal section according to claim 1 is characterized in that: Calculating the sensing data to obtain control data includes: defining a state function of a snow and ice accumulation area based on the temperature data, and calculating sensible enthalpy based on the temperature data; constructing a two-dimensional heat conduction equation based on the temperature data and the sensible enthalpy; Based on the two-dimensional heat conduction equation and the state function, calculating the position state of each position in the snow and ice accumulation area, wherein the position state includes a normal state and an ice and snow state; Calculating the friction coefficient of the ice and snow state based on the friction data; identifying a specific state of ice and snow based on the friction coefficient, the specific state including an ice layer state and a snow accumulation state; An actual thickness of the specific state is calculated based on the thickness data.

5. The non-invasive infrared intelligent snow-melting and ice-removing method for tunnel portal section according to claim 4 is characterized in that: Controlling the infrared spotlights to melt snow and remove ice through the control data includes: Acquire the mass of ice and snow based on the actual thickness, and calculate the energy demand for snow melting and de-icing through the mass of ice and snow and the humidity data; Calculating the required power for snow melting and ice removal based on the energy demand; The direction and angle of the infrared spotlights are adjusted according to the position status of each position in the snow and ice storage area, the actual power of the infrared spotlights is adjusted according to the required power, and snow melting and ice removal are carried out based on the infrared spotlights. The infrared spotlights are set on both sides of the road in the tunnel entrance section.

6. A non-invasive infrared intelligent snow-melting and ice-removing device for tunnel entrance section, characterized in that: include: A model building module, used to build an image recognition model, train the image recognition model, and obtain an image recognition network; A recognition module is used to obtain a tunnel entrance section image in real time, and recognize the tunnel entrance section image through an image recognition network to obtain a snow and ice accumulation area, wherein the tunnel entrance section image is obtained through cameras arranged on both sides of the tunnel entrance section road; An acquisition module, used to acquire sensor data of the snow and ice accumulation area, wherein the sensor data includes temperature data, humidity data, thickness data and friction data; The control module is used to calculate the sensor data to obtain control data, and control the infrared spotlights to melt snow and remove ice through the control data. The control data includes the position status and actual thickness of each position in the snow and ice storage area.

7. The non-invasive tunnel portal infrared intelligent snow melting and ice removal device according to claim 6 is characterized in that: The model building module comprises: A collection unit, used for collecting multiple images of snow and ice accumulation at the tunnel entrance section; A marking unit, used for marking the snow and ice layers in all the snow and ice images to obtain a snow and ice training set; A first construction unit, used to construct an image recognition model; The training unit is used to train the image recognition model through supervised learning based on the snow and ice training set to obtain an image recognition network, wherein the image recognition model adopts a YOLO network.

8. The non-invasive infrared intelligent snow-melting and ice-removing device for tunnel portal section according to claim 6 is characterized in that: The acquisition module comprises: A sensor composition unit for combining a single temperature sensor, a single humidity sensor, a single thickness sensor, and a single embedded friction sensor as a group of coordinated sensors; A sensor setting unit, used to set a plurality of the cooperative sensors under the surface of different measuring points of the road in the tunnel entrance section; The first acquisition unit is used to acquire temperature data at a measuring point through a temperature sensor, acquire humidity data at a measuring point through a humidity sensor, acquire thickness data of snow or ice at a measuring point through a thickness sensor, and acquire friction data at a measuring point through an embedded friction sensor.

9. The non-invasive tunnel portal infrared intelligent snow melting and ice removal device according to claim 6 is characterized in that: The control module comprises: A first calculation unit, configured to define a state function of a snow and ice accumulation area based on the temperature data, and calculate a sensible enthalpy based on the temperature data; A second construction unit, configured to construct a two-dimensional heat conduction equation based on the temperature data and the sensible enthalpy; A second calculation unit is used to calculate the position state of each position in the snow and ice storage area based on the two-dimensional heat conduction equation and the state function, wherein the position state includes a normal state and an ice and snow state; A third calculation unit, configured to calculate the friction coefficient of the ice and snow state based on the friction data; an identification unit, configured to identify a specific state of ice and snow based on the friction coefficient, wherein the specific state includes an ice layer state and a snow accumulation state; A fourth calculation unit is used to calculate the actual thickness of the specific state based on the thickness data.

10. The non-invasive tunnel portal infrared intelligent snow melting and ice removal device according to claim 9 is characterized in that: The control module further includes: A second acquisition unit is used to acquire the mass of ice and snow based on the actual thickness, and calculate the energy demand for snow melting and de-icing through the mass of ice and snow and the humidity data; a fifth calculation unit, configured to calculate the power required for snow melting and ice removal based on the energy demand; The control unit is used to adjust the direction and angle of the infrared spotlight according to the position status of each position in the snow and ice storage area, adjust the actual power of the infrared spotlight according to the required power, and melt snow and de-ice based on the infrared spotlight. The infrared spotlights are set on both sides of the road in the tunnel entrance section.

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