Non-contact structure quality detection method and device for compacted snow runway

Abstract

The invention discloses a non-contact structure quality detection method and device for a compacted snow runway, and relates to the field of compacted snow runway radar detection, and the method comprises the steps: obtaining an overall radar image after the construction of the compacted snow runway is completed; the compacted snow runway comprises a plurality of compacted snow layers which are arranged in a stacked mode. Each compacted snow layer comprises natural snow and solid particles; the overall radar image comprises radar detection information of each compacted snow layer; acquiring an overall radar image of the compacted snow runway after use; and comparing the overall radar image after the construction of the compacted snow runway with the overall radar image after the use of the compacted snow runway to obtain the quality change condition after the use of the compacted snow runway. The ground penetrating radar can be used for judging the strength and the structure of the compacted snow runway surface.

Description

Technical Field

[0001] The present application relates to the field of radar detection of compacted snow runways, and in particular to a non-contact structural quality detection method and device for compacted snow runways. Background Art

[0002] Given the special geographical location of Antarctica, transportation between the Antarctic continent and other continents can only be achieved through sea and air transportation. However, sea transportation requires the help of icebreakers and has a limited time period (from November of the current year to March of the following year), and the limitations of the transportation cycle are obvious; there are no port infrastructure or coastal navigation facilities along the coast of the Antarctic continent, and the efficiency of material loading and unloading is low, which further restricts the efficiency of the implementation of scientific expedition missions. In contrast, air transportation has significant advantages such as short round-trip cycle, direct access to the destination, high delivery efficiency, and wide coverage. Therefore, the better transportation plan is to build a large airport in Antarctica to develop the Antarctic air transportation network. Compacted snow runways are the preferred choice for building large airports in Antarctica. At present, the quality inspection of compacted snow layers mainly relies on sampling mechanical loading experiments. The sample range is small, the inspection is not comprehensive enough, and there are certain defects in the quality judgment of the entire runway. Summary of the invention

[0003] The purpose of this application is to provide a non-contact structural quality detection method and device for a compacted snow runway, which can use ground penetrating radar to determine the strength and structure of the compacted snow runway surface.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a non-contact structural quality detection method for a compacted snow runway, comprising:

[0006] Acquire an overall radar image after the compacted snow runway is completed; the compacted snow runway includes a plurality of compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer;

[0007] Get the overall radar image of the compacted snow runway after use;

[0008] By comparing the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, the quality change of the compacted snow runway after use is obtained; the quality change of the compacted snow runway after use includes the quality change of each layer of compacted snow after construction is completed and after use.

[0009] In a second aspect, the present application provides a non-contact structural quality detection device for a compacted snow runway, comprising:

[0010] The first image acquisition module is used to acquire an overall radar image after the compacted snow runway is completed; the compacted snow runway includes a plurality of compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer;

[0011] A second image acquisition module is used to acquire an overall radar image of the compacted snow runway after use;

[0012] The comparison module is used to compare the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, so as to obtain the quality change of the compacted snow runway after use; the quality change of the compacted snow runway after use includes the quality change of each layer of compacted snow after construction and use.

[0013] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned non-contact structural quality detection method for a compacted snow runway.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned non-contact structural quality detection method for a compacted snow runway.

[0015] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned non-contact structural quality detection method for a compacted snow runway.

[0016] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0017] The present application provides a non-contact structural quality detection method and device for a compacted snow runway, which obtains an overall radar image after the compacted snow runway is built; the compacted snow runway includes multiple compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer; the overall radar image of the compacted snow runway after use is obtained; the overall radar image after the compacted snow runway is built is compared with the overall radar image after the compacted snow runway is used, and the quality change of the compacted snow runway after use is obtained. The present invention can use ground penetrating radar to judge the strength and structure of the compacted snow runway surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 This is a diagram of the application environment of a non-contact structural quality detection method for a compacted snow runway in one embodiment of the present application;

[0020] Figure 2 A schematic flow chart of a non-contact structural quality detection method for a compacted snow runway provided in one embodiment of the present application;

[0021] Figure 3 A schematic diagram of a technical route for a non-contact structural quality detection method for a compacted snow runway provided in one embodiment of the present application;

[0022] Figure 4 A schematic diagram of material layer tracking using ground penetrating radar provided in one embodiment of the present application;

[0023] Figure 5 A schematic diagram of the basis for selecting metal materials provided in one embodiment of the present application;

[0024] Figure 6 A schematic diagram of a ground penetrating radar detecting a compacted snow runway according to an embodiment of the present application;

[0025] Figure 7 A schematic diagram of functional modules of a non-contact structural quality detection device for a compacted snow runway provided in one embodiment of the present application;

[0026] Figure 8 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0028] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0029] The non-contact structural quality detection method of a compacted snow runway provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal communicates with the server through the network. The data storage system can store the data that the server needs to process. The data storage system can be set up separately, integrated on the server, or placed on the cloud or other servers. The terminal can send the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used to the server. After the server receives the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, the server compares the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, and obtains the quality change of the compacted snow runway after use. The server can feedback the obtained quality change of the compacted snow runway after use to the terminal. In addition, in some embodiments, the non-contact structural quality detection method of the compacted snow runway can also be implemented by the server or the terminal alone, such as the terminal can directly compare the quality change of the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, or the server can obtain the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used from the data storage system, and compare the quality change.

[0030] The terminals may be, but are not limited to, various desktop computers, laptops, smart phones, tablet computers, IoT devices and portable wearable devices. IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server may be implemented as an independent server or a server cluster consisting of multiple servers, or a cloud server.

[0031] In an exemplary embodiment, Figure 2 As shown, a non-contact structural quality detection method for a compacted snow runway is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server in is taken as an example to illustrate, including the following steps 101 to 103.

[0032] in:

[0033] Step 101, obtaining an overall radar image after the compacted snow runway is completed; the compacted snow runway includes a plurality of compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer.

[0034] Step 102, obtaining an overall radar image of the compacted snow runway after use.

[0035] Step 103, comparing the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, to obtain the quality change of the compacted snow runway after use. The quality change of the compacted snow runway after use includes the quality change of each compacted snow layer after construction and after use.

[0036] By implementing the above-mentioned steps 101 to 103, the present application uses a ground-penetrating radar to scan the runway during the use and maintenance of the runway, compares the scanning result with the radar image that records the structural morphology of the runway during the construction process, detects snow layer defects caused by the landing of the aircraft, and realizes non-contact structural detection and material layer tracking of the compacted snow runway.

[0037] In another exemplary embodiment of the present application, the corresponding basic principle can be inferred from the application effect of the existing compacted snow runway: the strength of the snow layer is greatly improved by artificially reducing the density of the snow layer, and a multi-layer / composite high-density snow layer is constructed through multi-stage and multi-phase construction. Among them, artificially significantly improving the strength of the snow layer is the core technology for building / renovating snow runways. Improving the mechanical strength of the snow layer is mainly achieved by reducing the porosity and increasing the unit density. For the construction process of the compacted snow runway: Figure 3 and Figure 4 As shown, there are two different construction methods. The first one is to spread natural snow of a preset thickness (for example, 20 cm) on the ice base surface and use mechanical compaction. After the natural snow is compacted, solid particles (for example, metal particles or semiconductor ceramic particles) of a preset thickness (for example, 5 cm) are spread and mechanical compaction is performed again. The compaction process of one layer of natural snow and one layer of solid particles is repeated. Finally, three layers of natural snow and two layers of solid particles can be set. The second one is to add solid particles during the snow decomposition process and use a mixing machine to mix them. Each preset thickness (for example, 15 cm) of natural snow is mixed with solid particles of a preset thickness (for example, 3 cm), and decomposition-sintering-compacting is performed. A total of 5 layers of mixed materials are set.

[0038] In this application, each layer of compacted snow includes natural snow and solid particles, and is not simply formed by compacting natural snow. Figure 5 As shown, the selection of solid granular materials for filling natural snow should ensure that the selected materials will not affect the usability of the compacted snow runway and can improve the extraction efficiency of the runway detection image by the ground penetrating radar. This involves the relationship between the Poisson's coefficient, heat transfer coefficient and electrical conductivity of the selected filling material and natural snow.

[0039] Poisson's ratio is a parameter that measures the ratio of lateral deformation to longitudinal deformation of a material when it is subjected to stress. The Poisson's ratio of compacted snow is relatively low, generally between 0.1 and 0.2. The internal structure of snow is composed of ice crystals and air, with low density and high porosity, which makes it more likely to be compressed when subjected to stress rather than to expand laterally. This low Poisson's ratio means that compacted snow is more susceptible to brittle failure when subjected to stress.

[0040] The Poisson's coefficient of semiconductor ceramic particles is generally low, ranging from about 0.2 to 0.25. For example, the Poisson's coefficients of common semiconductor ceramic materials such as zinc oxide (ZnO) and silicon carbide (SiC) are approximately 0.24 and 0.22, respectively. This indicates that semiconductor ceramics have small lateral deformation when subjected to axial stress and have a certain degree of brittleness. Mixing semiconductor ceramic particles into compacted snow may slightly change the Poisson's coefficient of the mixed material, but the overall change is not significant. Although semiconductor ceramic particles themselves are brittle, they can enhance the overall mechanical stability of compacted snow and improve the structural strength and durability of the mixed material.

[0041] Thermal conductivity is a measure of a material's ability to transfer heat. Compacted snow has a significantly lower thermal conductivity, typically between 0.05 and 0.5 W / (m·K). Snow's low thermal conductivity is mainly due to the large amount of air contained in its porous structure, which is a good thermal insulator. Therefore, snow provides good thermal insulation.

[0042] The heat transfer coefficient of semiconductor ceramic particles is between that of metals and insulators, typically between 10 and 50 W / (m·K). For example, the heat transfer coefficient of zinc oxide is about 20 W / (m·K), and that of silicon carbide is about 120 W / (m·K). Although these values ​​are lower than those of metals, they are significantly higher than the heat transfer coefficient of compacted snow. Introducing semiconductor ceramic particles into compacted snow can significantly increase the heat transfer coefficient of the mixed material and improve the transfer of heat in the snow. This is particularly critical for the application of GPR (Ground-Penetrating Radar), because a higher heat transfer coefficient can reduce the thermal attenuation of radar signals and improve the stability of signal propagation, thereby improving detection depth and accuracy.

[0043] Electrical conductivity is a parameter that measures the ability of a material to conduct electricity. The electrical conductivity of compacted snow is extremely low because ice and air are not good conductors of electricity. Low electrical conductivity makes compacted snow less reflective of ground penetrating radar signals, and the radar signal data extracted is not easy to accurately complete the quality evaluation of compacted snow runways.

[0044] The electrical conductivity of semiconductor ceramic particles is between that of conductors and insulators and can be adjusted by methods such as doping and heat treatment. For example, the electrical conductivity of pure zinc oxide is about 10 -5 S / m, while the conductivity of zinc oxide after doping can be increased to 10 -1 S / m. The conductivity of silicon carbide ranges from 10 -4 S / m to 10 -1 The S / m ratio varies, depending on its specific crystal structure and doping. By mixing semiconductor ceramic particles into compacted snow, the conductivity of the mixed material can be significantly improved, the reflection characteristics of the radar signal can be enhanced, and the signal strength and resolution can be improved, thereby improving the detection effect.

[0045] As an optional implementation, the solid particles in the compacted snow layer can be selected from semiconductor ceramic particles, which have mechanical and thermodynamic properties similar to those of snow, but whose electrical conductivity is quite different from that of snow. By mixing semiconductor ceramic particles into compacted snow, the physical properties of snow can be significantly improved, thereby improving the scanning effect of GPR. This innovative material has broad application prospects in the fields of polar exploration, construction engineering, and environmental protection, which will help promote technological progress and scientific research, and provide more reliable and efficient solutions for polar scientific expeditions and engineering construction. With the continuous advancement of science and technology, in-depth research on the physical properties of mixed materials of semiconductor ceramic particles and compacted snow will provide a more solid foundation for the development of new materials and the application of new technologies. By continuously optimizing the composition and characteristics of this mixed material, its performance and adaptability in various extreme environments can be further improved, providing better protection for human exploration and life in polar environments.

[0046] As another optional implementation, the solid particles in the compacted snow layer can be metal particles, which have mechanical and thermodynamic properties similar to those of snow, but have electrical conductivity that is significantly different from that of snow. For example, metal particles include aluminum (Al), with an electrical conductivity of 37.7×10 6 S / m, heat transfer coefficient (thermal conductivity): 205W / (m·K), Poisson coefficient: 0.33. Nickel (Ni), electrical conductivity: 14.3×10 6 S / m, heat transfer coefficient (thermal conductivity): 90W / (m·K), Poisson's coefficient: usually between 0.31 and 0.34. Zinc (Zn), electrical conductivity: 16.6×10 6 S / m, heat transfer coefficient (thermal conductivity) 116W / (m·K), Poisson's coefficient 0.25.

[0047] However, when comparing the compacted snow layer constructed by natural snow + metal particles with the compacted snow layer constructed by natural snow + semiconductor ceramic particles, the effect of adding semiconductor ceramic particles is better than adding metal particles.

[0048] During the construction process, quality assessment can be carried out after each layer of compacted snow (including natural snow and solid particles) is completed. During the last compaction of each layer of compacted snow, radar scanning and detection can be performed on the snow surface while compacting. Each layer of compacted snow material is marked and tracked on the radar image, so that the deformation of the same snow layer after each compaction can be compared and analyzed, and the thickness change of the snow layer, the snow surface settlement and the structural change of the snow layer can be determined, and the structural record of each snow layer can be completed. The radar data obtained from each scan is extracted and processed, and the porosity, flatness and uniformity of the runway are analyzed to complete the quality evaluation of the compacted snow runway.

[0049] Therefore, in the present application, before executing step 101 "obtaining an overall radar image after the compacted snow runway is completed", the non-contact structural quality detection method of the compacted snow runway further includes:

[0050] During the construction of the compacted snow runway, after each layer of compacted snow is completed, the compaction quality of the compacted snow layer is evaluated, so as to ensure the construction quality of the compacted snow runway. Specifically:

[0051] (1) Obtaining radar images of the surface of the compacted snow layer scanned by the ground penetrating radar after each compacted snow layer is completed during the construction of the compacted snow runway. Figure 6 shown.

[0052] (2) evaluating the compaction quality of the compacted snow layer according to the radar image of each compacted snow layer. Specifically, evaluating the structural distribution of the compacted snow layer, the density and strength of the compacted snow layer, and the moisture content of the compacted snow layer according to the radar image of each compacted snow layer. The structural distribution of the compacted snow layer includes whether the structure of the compacted snow layer is uniform and whether there is damage, voids, or ice layers in the compacted snow layer.

[0053] Ground-Penetrating Radar (GPR) is a non-destructive detection technology used to detect structures and objects under the ground. Its detection principle is to transmit high-frequency electromagnetic waves into the ground, which are reflected by various complex geological structures. The receiver receives the reflected echo and forms underground situation data.

[0054] The strength of the reflected signal mainly depends on the electrical difference between the upper and lower layers. The greater the electrical difference, the stronger the reflected signal. The penetration depth of the radar wave mainly depends on the conductivity and center frequency of the underground medium. The higher the conductivity, the smaller the penetration depth; the higher the center frequency, the smaller the penetration depth.

[0055] The propagation characteristics of electromagnetic waves depend on the electrical parameters of the medium. The electrical parameters of the medium mainly include conductivity σ and dielectric constant c. The former mainly affects the penetration (detection) depth of electromagnetic waves. When the conductivity is moderate, the latter determines the propagation speed of electromagnetic waves in the object. Different geological bodies (objects) have different electrical parameters. Therefore, echoes will be generated at the interface of geological bodies with different electrical properties.

[0056] Ground penetrating radar enables judgment of snow surface strength and structure

[0057] Ground penetrating radar can analyze the physical properties of the snow layer through the propagation and reflection characteristics of electromagnetic waves, and obtain the strength and structural distribution of the compacted snow runway.

[0058] Snow layer structure assessment: The construction of compacted snow runways is a multi-layered compaction process. There may be differences in density and moisture content between layers. GPR can detect these differences through changes in reflection signals. The profiles generated by GPR can identify the structure of each layer of the compacted snow runway and detect the thickness of the compacted snow layer. This helps to understand whether the structure of the snow runway is uniform, whether there are damage, voids, or ice layers, and helps to assess the layer distribution of the snow runway.

[0059] Snow density and strength assessment: Although GPR cannot directly measure the density or strength of snow, it can infer the density changes of snow by analyzing the propagation speed and reflection intensity of electromagnetic waves. Denser snow will cause the propagation speed of electromagnetic waves to slow down and the reflection signal to be stronger. Denser snow usually means stronger compaction, which can infer the strength of the runway.

[0060] Moisture content and ice detection: The moisture content and ice in the snow have a great impact on the reflection of electromagnetic waves. GPR can detect the possible existence of meltwater or ice in the snow. High moisture content will change the electrical properties of snow, causing the propagation speed of electromagnetic waves to slow down significantly, and the reflected signal will also change significantly. Areas with high moisture content may mean weaker structures, affecting the structure and strength of the runway, while the presence of ice may threaten the safety of the runway.

[0061] Long-term monitoring and maintenance: During use, the compacted snow runway may produce holes or layers due to the impact of the landing aircraft. These problems will reduce the load-bearing capacity and stability of the runway. GPR can be used for long-term monitoring of compacted snow runways. Through regular testing, the changes in the runway structure and strength can be understood, and repair measures can be taken before the damage becomes serious, helping managers to carry out effective maintenance and management. Figure 6 shown.

[0062] Material layer tracking (multi-layer pavement detection): radar detection is performed on each layer of snow pavement after compaction, and relevant radar image data is obtained and saved. The strength and structure of each layer of the pavement can be determined through radar data, and the snow surface settlement and the thickness change of the snow layer before and after compaction can be recorded. Through the recording of radar images, the structural changes of each layer of the snow pavement structure after each compaction can be tracked. After the compacted snow runway is put into use, the pavement structure changes of the compacted snow runway caused by aircraft landing, especially the structural changes of the deep snow layer, can be detected by radar and then compared with the radar image data of each layer of the snow pavement recorded during the runway construction process, so as to obtain a more intuitive and accurate structural change and quality detection of the compacted snow runway, and realize the material structure tracking of each layer of the compacted snow runway.

[0063] GPR can obtain the height changes and surface characteristics of the runway surface by continuously scanning it. By analyzing the uniformity and intensity changes of the surface reflection signal, it can identify uneven areas on the runway, such as potholes, bumps and cracks. High-precision GPR data can generate a three-dimensional model of the runway surface, helping engineers to make accurate flatness assessments and maintenance planning.

[0064] GPR obtains the electromagnetic reflection characteristics of each layer of the runway through multi-point and multi-depth scanning to evaluate the uniformity of the snow layer. The reflection signal of a uniform snow layer is relatively consistent, while an uneven snow layer will show significant differences in the reflection signal. By analyzing the changes in the reflection signal, it can be determined whether there is an uneven distribution inside the snow layer, such as ice, gaps, and impurities. This information is crucial for the quality control and long-term maintenance of the runway.

[0065] In summary, GPR uses the propagation and reflection characteristics of electromagnetic waves in the snow layer through non-destructive testing to help understand the structure and strength of compacted snow runways, providing reliable technical support for runway maintenance. Therefore, it can be used as a quality test for compacted snow runways in the construction of polar airport runways. However, the low electrical conductivity and low heat transfer coefficient of compacted snow will have a certain impact on the transmission and reflection of GPR signals. The compacted snow layer does not reflect radar signals well, and only using ground penetrating radar for detection may result in errors in the inspection results. Therefore, it is considered to mix some semiconductor ceramic particles in the compacted snow layer to increase the electrical characteristics of the compacted snow runway, so that the reflection signal obtained by the ground penetrating radar is clearer and more accurate, thereby improving the quality detection accuracy of the compacted snow runway.

[0066] In this application, semiconductor ceramic particles are mixed into the snow to enhance the reflection intensity of the runway material to electrical signals, the runway is scanned by ground penetrating radar to determine the strength and structure of the pavement, and the material layer tracking is achieved during the multiple compaction process of the snow runway to complete the quality inspection and evaluation.

[0067] The present application also provides an application scenario, which applies the above-mentioned non-contact structural quality detection method for compacted snow runways. Specifically: the non-contact structural quality detection method for compacted snow runways provided in this embodiment can be applied in the quality detection scenario of compacted snow runways. The scenario includes an image acquisition link, a quality detection link, and a detection result display link; the image acquisition link is used to collect radar images scanned by a ground-penetrating radar on the surface of the compacted snow layer after each layer of compacted snow is completed during the construction of the compacted snow runway, the overall radar image after the compacted snow runway is completed, and the overall radar image after the compacted snow runway is used; the quality detection link is used to perform non-contact structural quality detection of the compacted snow runway; the detection result display link is used to display the non-contact structural quality detection results. The non-contact structural quality detection method for compacted snow runways provided in the present application belongs to the quality detection link.

[0068] Based on the same inventive concept, the embodiment of the present application also provides a non-contact structural quality detection device for a compacted snow runway for implementing the non-contact structural quality detection method for a compacted snow runway involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more non-contact structural quality detection devices for compacted snow runways provided below can refer to the limitations of the non-contact structural quality detection method for compacted snow runways above, and will not be repeated here.

[0069] In an exemplary embodiment, Figure 7 As shown, a non-contact structure quality detection device for a compacted snow runway is provided, comprising:

[0070] The first image acquisition module M1 is used to acquire the overall radar image after the compacted snow runway is completed; the compacted snow runway includes a plurality of compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer.

[0071] The second image acquisition module M2 is used to acquire the overall radar image of the compacted snow runway after use.

[0072] The comparison module M3 is used to compare the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, and obtain the quality change of the compacted snow runway after use. The quality change of the compacted snow runway after use includes the quality change of each layer of compacted snow after construction and use.

[0073] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 8As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store non-contact structural quality detection result data of a compacted snow runway. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a non-contact structural quality detection method for a compacted snow runway is implemented.

[0074] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0075] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0076] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0077] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0078] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0079] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0080] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0081] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A non-contact structural quality detection method for a compacted snow runway, characterized in that: The non-contact structural quality detection method of the compacted snow runway comprises: Acquire an overall radar image after the compacted snow runway is completed; the compacted snow runway includes a plurality of compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer; Get the overall radar image of the compacted snow runway after use; By comparing the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, the quality change of the compacted snow runway after use is obtained; the quality change of the compacted snow runway after use includes the quality change of each layer of compacted snow after construction is completed and after use.

2. The non-contact structural quality detection method of a compacted snow runway according to claim 1, characterized in that: Before executing the step of "obtaining an overall radar image of the compacted snow runway after construction is completed", the non-contact structural quality detection method of the compacted snow runway further includes: During the construction of the compacted snow runway, after each compacted snow layer is completed, the compaction quality of the compacted snow layer is evaluated.

3. The non-contact structural quality detection method of a compacted snow runway according to claim 2, characterized in that: During the construction of the compacted snow runway, after each layer of compacted snow is completed, the compaction quality of the compacted snow layer is evaluated, specifically including: Acquire a radar image scanned by a ground penetrating radar on the surface of a compacted snow layer after each compacted snow layer is completed during the construction of the compacted snow runway; The compaction quality of each compacted snow layer is evaluated based on the radar image of the compacted snow layer.

4. The non-contact structural quality detection method of a compacted snow runway according to claim 3, characterized in that: The compaction quality of each compacted snow layer is evaluated based on the radar image of the compacted snow layer, specifically including: The structural distribution of the compacted snow layer, the density and strength of the compacted snow layer, and the moisture content of the compacted snow layer are evaluated based on the radar image of each compacted snow layer.

5. The non-contact structural quality detection method of a compacted snow runway according to claim 4, characterized in that: The structural distribution of the compacted snow layer includes whether the structure of the compacted snow layer is uniform and whether there is damage, voids or ice layers in the compacted snow layer.

6. The non-contact structural quality detection method of a compacted snow runway according to claim 1, characterized in that: The solid particle layer of the compacted snow layer is made of semiconductor ceramic particles or metal particles.

7. A non-contact structural quality detection device for a compacted snow runway, characterized in that: The non-contact structural quality detection device for the compacted snow runway comprises: The first image acquisition module is used to acquire an overall radar image after the compacted snow runway is completed; the compacted snow runway includes a plurality of compacted snow layers stacked in layers; each compacted snow layer includes natural snow and solid particles; the overall radar image includes radar detection information of each compacted snow layer; A second image acquisition module is used to acquire an overall radar image of the compacted snow runway after use; The comparison module is used to compare the overall radar image after the compacted snow runway is built and the overall radar image after the compacted snow runway is used, so as to obtain the quality change of the compacted snow runway after use; the quality change of the compacted snow runway after use includes the quality change of each layer of compacted snow after construction and use.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the non-contact structural quality detection method for a compacted snow runway as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the non-contact structural quality detection method for a compacted snow runway described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the non-contact structural quality detection method for a compacted snow runway described in any one of claims 1 to 6 is implemented.

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