Method and system for anti-puncturing protection of automobile tire

Abstract

The invention relates to an anti-puncturing protection method and system for an automobile tire, and the method comprises the steps: Q1, obtaining the image data information of the ground in real time based on a vehicle-mounted camera, and obtaining the point cloud data information of the ground in real time based on a vehicle-mounted laser radar, state data information of the multiple sets of neodymium iron boron permanent magnet assemblies is obtained in real time based on the vehicle-mounted central controller; and Q2, based on the image data information of the ground and the point cloud data information of the ground, fusing the image and the point cloud of the ground by adopting a multi-point feature fusion algorithm based on a semi-variation function, and constructing a semi-variation fusion feature matrix of the image and the point cloud of the ground. According to the device, iron nails and other sharp iron products on the ground can be adsorbed through the multiple sets of neodymium iron boron permanent magnet assemblies, so that the safety of tires is guaranteed, the multiple sets of neodymium iron boron permanent magnet assemblies can be effectively controlled and adjusted, and the adsorption efficiency and the adsorption effect of the neodymium iron boron permanent magnet assemblies are improved.

Description

Technical Field

[0001] The invention relates to the technical field of automobile tire protection, and in particular to a method and system for automobile tire puncture protection. Background Art

[0002] Neodymium iron boron permanent magnet is a high-performance rare earth permanent magnet material, known for its high magnetic energy product and coercive force, which makes it widely used in modern industry and electronic technology. The neodymium iron boron permanent magnet assembly can maintain its magnetism for a long time, has high coercive force and high magnetic energy product, which makes it a "strong man" among magnetic materials. It has a wide range of applications, including but not limited to:

[0003] Motor field: NdFeB permanent magnet materials are particularly used in motors, occupying the largest application field of rare earth permanent magnet motors, accounting for about 70% of the total magnets. This material can significantly reduce the weight of the motor, improve the performance of the motor, realize the mechatronics of the product, and promote the new rare earth permanent magnet motor into a new stage of development. For example, the use of rare earth permanent magnet motors can significantly reduce the weight of the motor. For example, the weight of a 10kw ordinary generator is 220kg, while the weight of a rare earth permanent magnet motor is only 92kg. At the same time, high efficiency and energy saving are achieved, with an average power saving rate of up to 10%, and some special motors have an energy saving rate of up to 15%-20%. Electronic information products: NdFeB material is one of the important basic materials in electronic information products and is closely related to many electronic products. With the popularization of communication equipment such as computers, mobile phones, and car phones and the rapid development of energy-saving cars, the world's demand for high-performance rare earth permanent magnet materials has grown rapidly. Surface treatment technology: With the advancement of technology, the surface treatment technology of NdFeB has also been significantly improved. For example, the nano-chelated film non-plating treatment technology has excellent wear and corrosion resistance and adhesion, and can be widely used in sea-based wind power generation, permanent magnet high-speed motors, special motors, and electric vehicle motors. Energy saving and environmental protection: As a sunrise industry for energy saving and environmental protection, NdFeB is widely used in information technology, automobiles, nuclear magnetic resonance, wind power generation, motors and other fields. It is expected that the compound growth rate in the next 3-5 years will be around 20%, showing strong market potential and environmental protection value.

[0004] At the same time, the tires of vehicles may be punctured whether they are driving at high speed or reversing. How to remove sharp iron products such as iron nails on the ground during the driving of the car to ensure the safety of the vehicle tires has become an urgent problem to be solved. Summary of the invention

[0005] In view of the above problems, the present invention provides a method and system for protecting automobile tires from punctures, which can not only adsorb sharp iron products such as iron nails on the ground through multiple groups of NdFeB permanent magnet assemblies to ensure the safety of the tires, but also effectively control and adjust the multiple groups of NdFeB permanent magnet assemblies, thereby improving the adsorption efficiency and adsorption effect of the NdFeB permanent magnet assemblies.

[0006] In order to achieve the above-mentioned purpose and other related purposes, the technical solution provided by the present invention is as follows:

[0007] A method for protecting a vehicle tire from punctures, the method comprising:

[0008] Q1. When a vehicle is driving on the road, it obtains the image data information of the ground in real time based on the on-board camera, obtains the point cloud data information of the ground in real time based on the on-board laser radar, and obtains the status data information of multiple groups of NdFeB permanent magnet assemblies in real time based on the on-board central controller;

[0009] Q2. Based on the image data information of the ground and the point cloud data information of the ground, a multi-point feature fusion algorithm based on a semivariogram function is used to fuse the ground image and point cloud, and a semivariogram fusion feature matrix of the ground image and point cloud is constructed to obtain the semivariogram fusion feature matrix data information of the ground image and point cloud, and the semivariogram fusion feature matrix data information is input into a deep learning neural network model to identify the iron nails on the ground, and the distribution data information of the identified iron nails on the ground is obtained;

[0010] Q3. Based on the distribution data information of the iron nails on the ground after identification and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the status of the multiple groups of NdFeB permanent magnet assemblies is optimized by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain the optimized status data information of the NdFeB permanent magnet assembly;

[0011] Q4. Based on the state data information of the optimized NdFeB permanent magnet assembly, a vehicle tire puncture protection prediction function F is established, the vehicle tire puncture protection prediction value is characterized, and the vehicle tire puncture protection prediction value data information is obtained.

[0012] Furthermore, the method further comprises:

[0013] Q5. Based on the vehicle tire puncture protection estimated value data information, set a preset threshold value. If the vehicle tire puncture protection estimated value data information is less than the preset threshold value, the vehicle tire is at risk of puncture, and return to step Q3. If the vehicle tire puncture protection estimated value data information is greater than the preset threshold value, the vehicle tire is not at risk of puncture and drives normally.

[0014] Furthermore, the vehicle tire puncture protection prediction function F is:

[0015]

[0016] Among them, x is the state data information of the optimized NdFeB permanent magnet assembly, α 1 , α 2 and α 3 Estimates the weight factor for vehicle tire puncture protection.

[0017] Furthermore, the vehicle tire puncture protection estimation weight factor α 1 , α 2 and α 3 The constraints are:

[0018]

[0019] The status data information of the multiple groups of NdFeB permanent magnet assemblies is the on or off status of each group of NdFeB permanent magnet assemblies. If each group of NdFeB permanent magnet assemblies is on, the iron nails are adsorbed; if each group of NdFeB permanent magnet assemblies is off, the iron nails are not adsorbed.

[0020] Further, in step Q2, the multi-point feature fusion algorithm based on the semivariogram function is used to fuse the ground image and the point cloud, and the semivariogram fusion feature matrix of the ground image and the point cloud is constructed, including:

[0021] Q21. Based on the image data information of the ground, construct a ground pixel matrix to obtain ground pixel matrix data information; based on the ground point cloud data information, construct a ground point cloud feature point matrix to obtain ground point cloud feature point matrix data information;

[0022] Q22. Based on the ground point cloud feature point matrix data information and the ground pixel point matrix data information, establish the ground image and point cloud semivariogram function W,

[0023]

[0024] Among them, y is the ground point cloud feature point matrix data information, z is the ground pixel point matrix data information, β 1 , β 2 and β 3 It is the semi-variation characteristic factor of the ground image and point cloud, which characterizes the spatial correlation degree of the ground image and point cloud, and obtains the spatial correlation degree data information of the ground image and point cloud;

[0025] Q23. Based on the spatial correlation data information of the ground image and the point cloud, a semi-variation fusion function R of the ground image and the point cloud is established.

[0026]

[0027] Among them, h is the spatial correlation data information between the ground image and the point cloud, δ 1 and δ 2 is the fusion factor of the ground image and point cloud, the ground point cloud and image are fused, and the semi-variation fusion feature matrix of the ground image and point cloud is constructed to obtain the semi-variation fusion feature matrix data information of the ground image and point cloud.

[0028] Furthermore, the fusion factor δ of the ground image and point cloud is 1 and δ 2 for,

[0029]

[0030] The semi-variation characteristic factor β of the ground image and point cloud 1 , β 2 and β 3 The constraints are:

[0031] Among them, h is the data information of the spatial correlation degree between the ground image and the point cloud.

[0032] Further, in step Q3, the optimization of the states of the multiple groups of NdFeB permanent magnet assemblies by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate includes:

[0033] Q31. Based on the distribution data information of the identified nails on the ground and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the parameters of the sparrow population are initialized, the maximum number of iterations is determined, and the initialized sparrow population data information is obtained;

[0034] Q32. Based on the initialized sparrow population data information, establish the fitness value function G of the sparrow population individuals,

[0035]

[0036] Among them, r is the data information of the sparrow population after initialization, γ 1 , γ 2 and γ 3 The fitness determining factor of the sparrow population individuals is used to calculate the fitness values ​​of the sparrow population individuals and obtain the fitness value data information of the sparrow population individuals;

[0037] Q32. Based on the fitness value data information of the sparrow population individuals, establish a position update function H,

[0038]

[0039] Among them, g is the fitness value data information of the sparrow population individuals, η 1 , η 2 and η 3 For the adaptive learning rate of individual sparrow populations, the states of multiple groups of NdFeB permanent magnet assemblies are optimized to obtain the state data information of the optimized NdFeB permanent magnet assemblies.

[0040] Furthermore, the adaptive learning rate η of the sparrow population individuals 1 , η 2 and η 3 for,

[0041] Among them, g is the fitness value data information of the sparrow population individuals.

[0042] In order to achieve the above-mentioned purpose and other related purposes, the present invention also provides a system for implementing any one of the above-mentioned automobile tire puncture protection methods, the system comprising: a data acquisition module for acquiring image data information of the ground in real time based on a vehicle-mounted camera, acquiring point cloud data information of the ground in real time based on a vehicle-mounted laser radar, and acquiring status data information of multiple groups of NdFeB permanent magnet assemblies in real time based on a vehicle-mounted central controller;

[0043] A data fusion module is connected to the data acquisition module and is used to fuse the ground image and point cloud using a multi-point feature fusion algorithm based on a semivariogram function, and to construct a semivariogram fusion feature matrix of the ground image and point cloud to obtain data information of the semivariogram fusion feature matrix of the ground image and point cloud;

[0044] A multi-objective data optimization module is connected to the data fusion module and is used to optimize the states of multiple groups of NdFeB permanent magnet assemblies using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain state data information of the optimized NdFeB permanent magnet assemblies; a vehicle tire puncture protection estimation module is connected to the multi-objective data optimization module and is used to establish a vehicle tire puncture protection estimation function F, characterize the vehicle tire puncture protection estimation value, and obtain vehicle tire puncture protection estimation value data information.

[0045] Furthermore, the system also includes a data identification module, which is connected to the vehicle tire puncture protection estimation module and is used to set a preset threshold for the status data information of the optimized NdFeB permanent magnet assembly. The system also includes an execution module, which is connected to the data identification module and is used to control and adjust the opening or closing of multiple groups of NdFeB permanent magnet assemblies according to the status data information of the optimized NdFeB permanent magnet assembly.

[0046] The present invention has the following positive effects:

[0047] 1. The present invention fuses the ground image and point cloud by adopting a multi-point feature fusion algorithm based on a semi-variance function, constructs a semi-variance fusion feature matrix of the ground image and point cloud, and optimizes the state of multiple groups of NdFeB permanent magnet assemblies by combining a multi-objective sparrow search optimization algorithm based on an adaptive learning rate. It can not only accurately characterize the distribution of iron nails on the ground, thereby ensuring that the NdFeB permanent magnet assembly can accurately adsorb the iron nails on the ground, but also can adaptively adjust the state of multiple groups of NdFeB permanent magnet assemblies according to the distribution of the iron nails, thereby improving the working efficiency of the NdFeB permanent magnet assembly.

[0048] 2. The present invention characterizes the vehicle tire puncture protection prediction value by establishing a vehicle tire puncture protection prediction function F, and sets a preset threshold to judge the vehicle tire puncture protection prediction value data information, which not only further ensures the safety of the vehicle tires, but also the entire process can be optimized and adjusted according to changes in ground conditions, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0050] Figure 2 It is a flow chart of the multi-point feature fusion algorithm based on semivariogram of the present invention;

[0051] Figure 3 It is a flow chart of a multi-objective sparrow search optimization algorithm based on adaptive learning rate of the present invention;

[0052] Figure 4 It is a schematic diagram of the system framework of the present invention;

[0053] Figure 5 The figure is a schematic diagram of the distribution of multiple groups of NdFeB permanent magnet assemblies of the present invention.

[0054] Explanation of the numbers in the figure: 1-car chassis, 2-NdFeB permanent magnet assembly, 3-camera, 4-laser radar. DETAILED DESCRIPTION

[0055] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0056] Example 1: Figure 1 or Figure 5As shown, a method for protecting a vehicle tire from punctures comprises:

[0057] Q1. The vehicle is driving on the road, and the vehicle camera 3 obtains the ground image data information in real time, the vehicle laser radar 4 obtains the ground point cloud data information in real time, and the vehicle central controller obtains the status data information of multiple groups of NdFeB permanent magnet assemblies 2 in real time;

[0058] Q2. Based on the image data information of the ground and the point cloud data information of the ground, a multi-point feature fusion algorithm based on a semivariogram function is used to fuse the ground image and point cloud, and a semivariogram fusion feature matrix of the ground image and point cloud is constructed to obtain the semivariogram fusion feature matrix data information of the ground image and point cloud, and the semivariogram fusion feature matrix data information is input into a deep learning neural network model to identify the iron nails on the ground, and the distribution data information of the identified iron nails on the ground is obtained;

[0059] Q3. Based on the distribution data information of the iron nails on the ground after identification and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the status of the multiple groups of NdFeB permanent magnet assemblies is optimized by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain the optimized status data information of the NdFeB permanent magnet assembly;

[0060] Q4. Based on the state data information of the optimized NdFeB permanent magnet assembly, a vehicle tire puncture protection prediction function F is established, the vehicle tire puncture protection prediction value is characterized, and the vehicle tire puncture protection prediction value data information is obtained.

[0061] In this embodiment, the NdFeB permanent magnet assembly includes a NdFeB permanent magnet, an electromagnet and a magnetic-isolating box wrapped around the outside of the NdFeB permanent magnet and the electromagnet. The magnetic-isolating box is arranged on the chassis of the car. A switch door is provided at the bottom of the magnetic-isolating box, which is connected to the vehicle-mounted central controller. The magnetic-isolating box is used to isolate magnetism. When the magnetic-isolating box is in a closed state, the magnetism of the NdFeB permanent magnet and the electromagnet is isolated and adsorption cannot be performed. If the magnetic-isolating box is in an open state, the magnetism of the NdFeB permanent magnet and the electromagnet can work normally and adsorb the iron nails.

[0062] In this embodiment, the method further includes:

[0063] Q5. Based on the vehicle tire puncture protection estimated value data information, set a preset threshold value. If the vehicle tire puncture protection estimated value data information is less than the preset threshold value, the vehicle tire is at risk of puncture, and return to step Q3. If the vehicle tire puncture protection estimated value data information is greater than the preset threshold value, the vehicle tire is not at risk of puncture and drives normally.

[0064] In this embodiment, the vehicle tire puncture protection prediction function F is:

[0065]

[0066] Among them, x is the state data information of the optimized NdFeB permanent magnet assembly, α 1 , α 2 and α 3 Estimates the weight factor for vehicle tire puncture protection.

[0067] In this embodiment, the vehicle tire puncture protection estimation weight factor α 1 , α 2 and α 3 The constraints are:

[0068]

[0069] The status data information of the multiple groups of NdFeB permanent magnet assemblies is the on or off status of each group of NdFeB permanent magnet assemblies. If each group of NdFeB permanent magnet assemblies is on, the iron nails are adsorbed; if each group of NdFeB permanent magnet assemblies is off, the iron nails are not adsorbed.

[0070] In this embodiment, if Figure 2 As shown, in step Q2, the multi-point feature fusion algorithm based on the semivariogram function is used to fuse the ground image and the point cloud, and the semivariogram fusion feature matrix of the ground image and the point cloud is constructed, including:

[0071] Q21. Based on the image data information of the ground, construct a ground pixel matrix to obtain ground pixel matrix data information; based on the ground point cloud data information, construct a ground point cloud feature point matrix to obtain ground point cloud feature point matrix data information;

[0072] Q22. Based on the ground point cloud feature point matrix data information and the ground pixel point matrix data information, establish the ground image and point cloud semivariogram function W,

[0073]

[0074] Among them, y is the ground point cloud feature point matrix data information, z is the ground pixel point matrix data information, β 1 , β 2 and β 3 It is the semi-variation characteristic factor of the ground image and point cloud, which characterizes the spatial correlation degree of the ground image and point cloud, and obtains the spatial correlation degree data information of the ground image and point cloud;

[0075] Q23. Based on the spatial correlation data information of the ground image and the point cloud, a semi-variation fusion function R of the ground image and the point cloud is established.

[0076]

[0077] Among them, h is the spatial correlation data information between the ground image and the point cloud, δ 1 and δ 2 is the fusion factor of the ground image and point cloud, the ground point cloud and image are fused, and the semi-variation fusion feature matrix of the ground image and point cloud is constructed to obtain the semi-variation fusion feature matrix data information of the ground image and point cloud.

[0078] In this embodiment, the fusion factor δ of the ground image and the point cloud is 1 and δ 2 for,

[0079] The semi-variation characteristic factor β of the ground image and point cloud 1 , β 2 and β 3 The constraints are:

[0080] Among them, h is the data information of the spatial correlation degree between the ground image and the point cloud.

[0081] Embodiment 2: Based on the method for protecting automobile tires from punctures in Embodiment 1, the present invention is further illustrated and described below.

[0082] like Figure 1 or Figure 5 As shown, a method for protecting a vehicle tire from punctures comprises:

[0083] Q1. The vehicle is driving on the road, and the vehicle camera 3 obtains the ground image data information in real time, the vehicle laser radar 4 obtains the ground point cloud data information in real time, and the vehicle central controller obtains the status data information of multiple groups of NdFeB permanent magnet assemblies 2 in real time (wherein, multiple groups of NdFeB permanent magnet assemblies 2 are provided at the bottom of the vehicle chassis 1);

[0084] Q2. Based on the image data information of the ground and the point cloud data information of the ground, a multi-point feature fusion algorithm based on a semivariogram function is used to fuse the ground image and point cloud, and a semivariogram fusion feature matrix of the ground image and point cloud is constructed to obtain the semivariogram fusion feature matrix data information of the ground image and point cloud, and the semivariogram fusion feature matrix data information is input into a deep learning neural network model to identify the iron nails on the ground, and the distribution data information of the identified iron nails on the ground is obtained;

[0085] Q3. Based on the distribution data information of the iron nails on the ground after identification and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the status of the multiple groups of NdFeB permanent magnet assemblies is optimized by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain the optimized status data information of the NdFeB permanent magnet assembly;

[0086] Q4. Based on the state data information of the optimized NdFeB permanent magnet assembly, a vehicle tire puncture protection prediction function F is established, the vehicle tire puncture protection prediction value is characterized, and the vehicle tire puncture protection prediction value data information is obtained.

[0087] In this embodiment, if Figure 3 As shown, in step Q3, the optimization of the states of multiple groups of NdFeB permanent magnet assemblies by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate includes:

[0088] Q31. Based on the distribution data information of the identified nails on the ground and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the parameters of the sparrow population are initialized, the maximum number of iterations is determined, and the initialized sparrow population data information is obtained;

[0089] Q32. Based on the initialized sparrow population data information, establish the fitness value function G of the sparrow population individuals,

[0090]

[0091] Among them, r is the data information of the sparrow population after initialization, γ 1 , γ 2 and γ 3 The fitness determining factor of the sparrow population individuals is used to calculate the fitness values ​​of the sparrow population individuals and obtain the fitness value data information of the sparrow population individuals;

[0092] Q32. Based on the fitness value data information of the sparrow population individuals, establish a position update function H,

[0093]

[0094] Among them, g is the fitness value data information of the sparrow population individuals, η 1 , η 2 and η 3 For the adaptive learning rate of individual sparrow populations, the states of multiple groups of NdFeB permanent magnet assemblies are optimized to obtain the state data information of the optimized NdFeB permanent magnet assemblies.

[0095] In this embodiment, the adaptive learning rate η of the sparrow population individuals 1 , η 2 and η3 for,

[0096]

[0097] Among them, g is the fitness value data information of the sparrow population individuals.

[0098] In this embodiment, if Figure 4 As shown, the present invention provides a system for implementing any one of the above-mentioned methods for protecting automobile tires from puncture, the system comprising:

[0099] A data acquisition module is used to acquire the image data information of the ground in real time based on the vehicle-mounted camera, acquire the point cloud data information of the ground in real time based on the vehicle-mounted laser radar, and acquire the status data information of multiple groups of NdFeB permanent magnet assemblies in real time based on the vehicle-mounted central controller;

[0100] A data fusion module is connected to the data acquisition module and is used to fuse the ground image and point cloud using a multi-point feature fusion algorithm based on a semivariogram function, and to construct a semivariogram fusion feature matrix of the ground image and point cloud to obtain data information of the semivariogram fusion feature matrix of the ground image and point cloud;

[0101] A multi-objective data optimization module is connected to the data fusion module and is used to optimize the states of multiple groups of NdFeB permanent magnet assemblies using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain state data information of the optimized NdFeB permanent magnet assemblies; a vehicle tire puncture protection estimation module is connected to the multi-objective data optimization module and is used to establish a vehicle tire puncture protection estimation function F, characterize the vehicle tire puncture protection estimation value, and obtain vehicle tire puncture protection estimation value data information.

[0102] In this embodiment, the system also includes a data identification module, which is connected to the vehicle tire puncture protection estimation module and is used to set a preset threshold for the status data information of the optimized NdFeB permanent magnet assembly. The system also includes an execution module, which is connected to the data identification module and is used to control and adjust the opening or closing of multiple groups of NdFeB permanent magnet assemblies according to the status data information of the optimized NdFeB permanent magnet assembly.

[0103] In this embodiment, the present invention provides a computer-readable storage medium, on which is stored a computer program programmed or configured to execute any one of the above-mentioned methods for protecting automobile tires from puncture.

[0104] Any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).

[0105] In summary, the present invention can not only adsorb sharp iron products such as iron nails on the ground through multiple groups of NdFeB permanent magnet assemblies, thereby ensuring the safety of tires, but also can effectively control and adjust multiple groups of NdFeB permanent magnet assemblies, thereby improving the adsorption efficiency and adsorption effect of the NdFeB permanent magnet assemblies.

[0106] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for protecting automobile tires from punctures, characterized in that: The method comprises: Q1. When a vehicle is driving on the road, it obtains the image data information of the ground in real time based on the on-board camera, obtains the point cloud data information of the ground in real time based on the on-board laser radar, and obtains the status data information of multiple groups of NdFeB permanent magnet assemblies in real time based on the on-board central controller; Q2. Based on the image data information of the ground and the point cloud data information of the ground, a multi-point feature fusion algorithm based on a semivariogram function is used to fuse the ground image and point cloud, and a semivariogram fusion feature matrix of the ground image and point cloud is constructed to obtain the semivariogram fusion feature matrix data information of the ground image and point cloud, and the semivariogram fusion feature matrix data information is input into a deep learning neural network model to identify the iron nails on the ground, and the distribution data information of the identified iron nails on the ground is obtained; Q3. Based on the distribution data information of the iron nails on the ground after identification and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the status of the multiple groups of NdFeB permanent magnet assemblies is optimized by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain the optimized status data information of the NdFeB permanent magnet assembly; Q4. Based on the state data information of the optimized NdFeB permanent magnet assembly, a vehicle tire puncture protection prediction function F is established, the vehicle tire puncture protection prediction value is characterized, and the vehicle tire puncture protection prediction value data information is obtained.

2. The method for protecting automobile tires from punctures according to claim 1, characterized in that: The method further comprises: Q5. Based on the vehicle tire puncture protection estimated value data information, set a preset threshold value. If the vehicle tire puncture protection estimated value data information is less than the preset threshold value, the vehicle tire is at risk of puncture, and return to step Q3. If the vehicle tire puncture protection estimated value data information is greater than the preset threshold value, the vehicle tire is not at risk of puncture and drives normally.

3. The method for protecting automobile tires from punctures according to claim 1, characterized in that: The vehicle tire puncture protection prediction function F is: Among them, x is the state data information of the optimized NdFeB permanent magnet assembly, and α1, α2 and α3 are the estimated weight factors of vehicle tire puncture protection.

4. The method for protecting automobile tires from punctures according to claim 2, characterized in that: The constraints of the vehicle tire puncture protection estimation weight factors α1, α2 and α3 are: The status data information of the multiple groups of NdFeB permanent magnet assemblies is the on or off status of each group of NdFeB permanent magnet assemblies. If each group of NdFeB permanent magnet assemblies is on, the iron nails are adsorbed; if each group of NdFeB permanent magnet assemblies is off, the iron nails are not adsorbed.

5. The method for protecting automobile tires from punctures according to claim 1, characterized in that: In step Q2, the method of fusing the ground image and point cloud using a multi-point feature fusion algorithm based on a semivariogram function and constructing a semivariogram fusion feature matrix of the ground image and point cloud includes: Q21. Based on the image data information of the ground, construct a ground pixel matrix to obtain ground pixel matrix data information; based on the ground point cloud data information, construct a ground point cloud feature point matrix to obtain ground point cloud feature point matrix data information; Q22. Based on the ground point cloud feature point matrix data information and the ground pixel point matrix data information, establish the ground image and point cloud semivariogram function W, Among them, y is the ground point cloud feature point matrix data information, z is the ground pixel point matrix data information, β1, β2 and β3 are the semi-variation characteristic factors of the ground image and point cloud, which characterize the spatial correlation degree of the ground image and point cloud, and obtain the spatial correlation degree data information of the ground image and point cloud; Q23. Based on the spatial correlation data information of the ground image and the point cloud, a semi-variation fusion function R of the ground image and the point cloud is established. Among them, h is the data information of the spatial correlation degree between the ground image and the point cloud, δ1 and δ2 are the fusion factors of the ground image and the point cloud, the ground point cloud and the image are fused, and the semi-variation fusion feature matrix of the ground image and point cloud is constructed to obtain the semi-variation fusion feature matrix data information of the ground image and point cloud.

6. The method for protecting automobile tires from punctures according to claim 5, characterized in that: The fusion factors δ1 and δ2 of the ground image and point cloud are, The constraints of the semi-variation characteristic factors β1, β2 and β3 of the ground image and point cloud are: Among them, h is the data information of the spatial correlation degree between the ground image and the point cloud.

7. The method for protecting automobile tires from punctures according to claim 1, characterized in that: In step Q3, the optimization of the states of multiple groups of NdFeB permanent magnet assemblies by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate includes: Q31. Based on the distribution data information of the identified nails on the ground and the status data information of the multiple groups of NdFeB permanent magnet assemblies, the parameters of the sparrow population are initialized, the maximum number of iterations is determined, and the initialized sparrow population data information is obtained; Q32. Based on the initialized sparrow population data information, establish the fitness value function G of the sparrow population individuals, Among them, r is the data information of the sparrow population after initialization, γ1, γ2 and γ3 are the fitness determining factors of the sparrow population individuals, and the fitness values ​​of the sparrow population individuals are calculated to obtain the fitness value data information of the sparrow population individuals; Q32. Based on the fitness value data information of the sparrow population individuals, establish a position update function H, Among them, g is the fitness value data information of the individual sparrow population, η1, η2 and η3 are the adaptive learning rates of the individual sparrow population, and the states of multiple groups of NdFeB permanent magnet assemblies are optimized to obtain the state data information of the optimized NdFeB permanent magnet assemblies.

8. The method for protecting automobile tires from punctures according to claim 7, characterized in that: The adaptive learning rates η1, η2 and η3 of the sparrow population individuals are: Among them, g is the fitness value data information of the sparrow population individuals.

9. A system for implementing the method for protecting automobile tires from punctures according to any one of claims 1 to 8, characterized in that: The system comprises: A data acquisition module is used to acquire the image data information of the ground in real time based on the vehicle-mounted camera, to acquire the point cloud data information of the ground in real time based on the vehicle-mounted laser radar, and to acquire the status data information of multiple groups of NdFeB permanent magnet assemblies in real time based on the vehicle-mounted central controller; A data fusion module is connected to the data acquisition module and is used to fuse the ground image and point cloud using a multi-point feature fusion algorithm based on a semivariogram function, and to construct a semivariogram fusion feature matrix of the ground image and point cloud to obtain data information of the semivariogram fusion feature matrix of the ground image and point cloud; A multi-objective data optimization module is connected to the data fusion module and is used to optimize the states of multiple groups of NdFeB permanent magnet assemblies by using a multi-objective sparrow search optimization algorithm based on an adaptive learning rate to obtain state data information of the optimized NdFeB permanent magnet assemblies; The vehicle tire puncture protection estimation module is connected to the multi-objective data optimization module and is used to establish a vehicle tire puncture protection estimation function F, characterize the vehicle tire puncture protection estimation value, and obtain the vehicle tire puncture protection estimation value data information.

10. The system according to claim 9, characterized in that: The system also includes a data identification module, which is connected to the vehicle tire puncture protection estimation module and is used to set a preset threshold value for the status data information of the optimized NdFeB permanent magnet assembly. The system also includes an execution module, which is connected to the data identification module and is used to control and adjust the opening or closing of multiple groups of NdFeB permanent magnet assemblies according to the status data information of the optimized NdFeB permanent magnet assembly.

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