A safety detection method of infrared polarization of cracks in urban underground space

Abstract

The present invention discloses a safety detection method of infrared polarization of cracks in urban underground space, which relates to the field of infrared polarization detection technology. It performs global infrared polarization detection on underground space areas, determines light detection signals, and builds a polarization decoding module based on the mapping relationship between the response of a metasurface and the polarization state of light. The light detection signal is incident on the metasurface for polarization debugging, and the polarization decoding module is combined to perform surface response conversion and photoelectric conversion imaging, and the detection polarization image is determined and transmitted to the back-end detection module, and recognition and feature determination based on pixel corner windows are performed to determine the characteristics of space cracks, and safety early warning management is performed on underground space areas. It is used to solve the technical problem that it is difficult to meet the high-accuracy and high-efficiency detection requirements of cracks in complex underground spaces in the prior art, and realize efficient and accurate detection and early warning management of underground space cracks.

Description

Technical Field

[0001] The invention relates to the technical field of infrared polarization detection, and in particular to a safe detection method for infrared polarization of cracks in urban underground spaces. Background Art

[0002] With the acceleration of urbanization, the development and utilization of underground space has become increasingly extensive, but the problem of underground cracks has also become prominent, posing a potential threat to the safety of urban infrastructure. In the existing technology, traditional crack detection methods mainly rely on manual inspections or simple visual inspections. These methods are not only time-consuming and labor-intensive, but also difficult to accurately capture the subtle features and changing trends of cracks. In addition, due to the complexity and concealment of the underground environment, traditional methods often find it difficult to achieve comprehensive and efficient detection of cracks.

[0003] In response to the above problems, infrared polarization detection technology has been gradually applied to the field of crack detection in recent years. However, the existing infrared polarization detection technology still has technical bottlenecks such as inaccurate feature recognition, which makes it difficult to meet the needs of high-precision and real-time monitoring of underground space cracks. Therefore, how to combine modern scientific and technological means to improve the detection efficiency and accuracy of underground space cracks has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present application provides a safe detection method of infrared polarization of cracks in urban underground spaces, which is used to solve the technical problem that the existing technology is difficult to meet the demand for high-accuracy and high-efficiency detection of cracks in complex underground spaces.

[0005] In view of the above problems, the present application provides a safe detection method of infrared polarization of cracks in urban underground spaces.

[0006] The present application provides a method for infrared polarization safety detection of cracks in urban underground spaces, the method comprising: for underground space areas, polarization calibration of infrared polarization detectors, execution of global infrared polarization detection, and determination of light detection signals; structural information of interactive metasurfaces, based on the mapping relationship between metasurface response and light polarization state, constructing a polarization decoding module, and establishing a connection between the polarization decoding module and the metasurface; the light detection signal is incident through the metasurface for polarization adjustment, surface response conversion and photoelectric conversion imaging are performed in combination with the polarization decoding module, and a detection polarization image is determined; the detection polarization image is transmitted to a back-end detection module, and recognition and feature determination based on a pixel corner window are performed to determine the characteristics of spatial cracks, wherein the determination is performed by mining the mapping relationship between light polarization state and geological characteristics, and the pixel corner window represents the polarization state trend change part; based on the characteristics of the spatial cracks, safety early warning management of the underground space area is performed.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The embodiment of the present application provides a safety detection method for infrared polarization of cracks in urban underground space. For the underground space area, polarization calibration is performed on the infrared polarization detector, and global infrared polarization detection is performed to determine the light detection signal; the structural information of the interactive metasurface is used, and the mapping relationship between the metasurface response and the light polarization state is used as a reference to construct a polarization decoding module, and a connection between the polarization decoding module and the metasurface is established; the light detection signal is incident through the metasurface for polarization adjustment, and the surface response conversion and photoelectric conversion imaging are performed in combination with the polarization decoding module, and the detection polarization image is determined and transmitted to the back-end detection module, and the pixel corner window-based recognition and feature judgment are performed to determine the spatial crack features, and the underground space area is managed for safety warning. It is used to solve the technical problem that it is difficult to meet the high-accuracy and high-efficiency detection requirements of cracks in complex underground spaces in the prior art, and to achieve efficient and accurate detection and early warning management of underground space cracks. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic flow chart of a method for infrared polarization safety detection of cracks in urban underground spaces is provided for this application;

[0010] Figure 2 A schematic diagram of the risk rating process of space crack characteristics in a safety detection method of infrared polarization of urban underground space cracks is provided for this application. DETAILED DESCRIPTION

[0011] The present application provides a safety detection method for infrared polarization of cracks in urban underground spaces, performs global infrared polarization detection on underground space areas, determines light detection signals, and constructs a polarization decoding module based on the mapping relationship between metasurface response and light polarization state. The light detection signal is incident on the metasurface for polarization adjustment, and surface response conversion and photoelectric conversion imaging are performed in combination with the polarization decoding module. The detection polarization image is determined and transmitted to a back-end detection module, and recognition and feature judgment based on pixel corner point windows are performed to determine the characteristics of spatial cracks. Safety early warning management is performed on underground space areas to solve the technical problem that the existing technology is difficult to meet the requirements of high-accuracy and high-efficiency detection of cracks in complex underground spaces.

[0012] Example: Figure 1 As shown, the present application provides a safe detection method of infrared polarization of cracks in urban underground spaces, the method comprising:

[0013] S1: For the underground space area, polarization calibration is performed on the infrared polarization detector, and full-area infrared polarization detection is performed to determine the light detection signal.

[0014] Specifically, polarization calibration is to adjust the parameters of the infrared polarization detector. During this process, a light source or standard sample with known polarization characteristics is required to calibrate the infrared polarization detector to ensure the accuracy of its measurement of the polarization state of the optical signal.

[0015] After polarization calibration is completed, full-area infrared polarization detection is performed, that is, the entire underground space area is detected. In the specific implementation process, during full-area detection, the infrared polarization detector will scan the underground space area point by point or surface by surface according to the preset scanning path or grid layout, and transmit and receive the light detection signal of each scanning point. These signals contain information about the temperature distribution of underground space objects, surface roughness, and polarization state changes caused by defects such as cracks.

[0016] S2: Based on the structural information of the interactive metasurface, a polarization decoding module is constructed based on the mapping relationship between the metasurface response and the light polarization state, and a connection between the polarization decoding module and the metasurface is established.

[0017] In the embodiment of the present application, the metasurface is a micro-nanostructure surface whose unique geometric shape and arrangement can precisely control the amplitude, phase and polarization state of light waves. In the present method, the structural information of the metasurface includes but is not limited to the shape, size, arrangement and material properties of its unit structure, which is the basis for constructing a polarization decoding module.

[0018] Then, the mapping relationship between the metasurface response and the polarization state of light is mined. Specifically, the metasurface will show different response characteristics to light waves in different polarization states, such as reflectivity, transmittance, phase delay, etc. By establishing a precise mapping relationship between the metasurface response and the polarization state of light, accurate decoding of the polarization state of light can be achieved. In this application, the metasurface is tested and data statistics mining is performed based on the test samples.

[0019] Then, based on the mapping relationship, a polarization decoding module is constructed, which analyzes the input infrared polarization signal according to the response characteristics of the metasurface and outputs the corresponding polarization state information. Then, a connection between the polarization decoding module and the metasurface is established to ensure that the polarization decoding module can receive and process the response signal of the metasurface in real time.

[0020] During the specific implementation process, the connection must use appropriate data transmission and interfaces to ensure the integrity and real-time performance of the signal. At the same time, the connection needs to be tested for stability and reliability to ensure that no failures or errors occur in actual applications. The construction of the polarization decoding module provides strong technical support for infrared polarization safety detection of underground space cracks.

[0021] Further, a polarization decoding module is constructed, and step S2 of the present application includes:

[0022] According to the structural information, the modulation characteristics of the selective transmittance are determined, wherein the amplitude and phase modulation of the light field by the meta-atom is used as the principle; and the polarization decoding module is constructed based on the modulation characteristics.

[0023] First, we focus on the structural information of metasurfaces, which is the basis for understanding their optical properties. Metasurfaces are composed of a series of micro-nanoscale structural units (i.e., metaatoms), which can precisely control the amplitude, phase, and polarization state of light fields through specific arrangements and combinations. In this method, by analyzing the structural information of metaatoms such as shape, size, material, and arrangement, the principle of selective transmittance modulation of light fields is revealed.

[0024] Next, based on the principle of amplitude and phase modulation of the light field by meta-atoms, specifically, meta-atoms control the amplitude of the light wave by changing the reflection and transmission coefficients of the light wave at the interface; at the same time, by introducing phase delay or phase mutation, the phase of the light wave is controlled. These modulation characteristics jointly determine the response characteristics of the metasurface to light waves in different polarization states, that is, its selective transmittance.

[0025] In the embodiment of the present application, the light polarization part is used as the light transmission requirement, that is, the subsequent analysis is only for the light polarization part, the remaining signal parts are intercepted, and only the effective signal part is analyzed and decided.

[0026] Then, based on the selective transmittance modulation characteristics of the metasurface, that is, based on the polarization part of the light, a polarization decoding module was constructed using sample training. After polarization transmission of the light detection signal, it analyzes and outputs the corresponding polarization state information based on the response characteristics of the metasurface to the light wave.

[0027] Furthermore, the polarization decoding module is constructed, and step S2 of the present application includes:

[0028] Interactive polarization decoding samples, wherein the polarization decoding samples include response samples with different polarization states determined based on the metasurface test - polarization state samples, and the metasurface response includes at least response intensity and phase distribution; according to the polarization decoding samples, a polarization decision tree is constructed and trained to convergence to determine the polarization decoding module.

[0029] In the embodiment of the present application, the polarization decoding sample is determined based on the metasurface test, and includes the response sample of the metasurface under different polarization states and the corresponding polarization state sample. Specifically, the polarization decoding sample consists of a series of response sample-polarization state sample pairs with different polarization states, wherein the response sample contains the key information such as the response intensity and phase distribution of the metasurface to light waves in different polarization states, and the polarization state sample records the corresponding polarization state of the light wave.

[0030] The metaplane encodes the polarization information of the optical detection signal as its characteristic vector, namely, response information, which at least includes response intensity and phase change, and needs to be decoded to determine its own polarization state.

[0031] A polarization decision tree is constructed based on polarization decoding samples, and supervised training is performed on this basis until convergence. Specifically, the polarization decision tree is a classification model based on a tree structure. According to the characteristics of the input sample, in this case, the response intensity and phase distribution of the metasurface, layer-by-layer classification is performed to finally determine the polarization state category to which the sample belongs. Exemplarily, a response data is randomly extracted according to the polarization encoding sample as the first classification node, and the response sample is divided into two groups, greater than or less than the response data, and then a response data is randomly extracted based on the polarization encoding sample, and then divided again on the basis of the division, and the above steps are repeated until the construction of the polarization classification tree is completed, and then the polarization classification tree is identified based on the polarization state sample.

[0032] Furthermore, the polarization decision tree is built into the polarization decoding module and trained until convergence according to the polarization decoding samples. During the training process, the parameters and structure of the decision tree are continuously adjusted to optimize the classification rules so that different polarization states can be more accurately identified according to the response characteristics of the metasurface. The standard for training convergence can be the stable improvement of evaluation indicators such as classification accuracy and recall rate, or reaching a preset number of training rounds.

[0033] When the polarization decision tree is trained to convergence, a polarization decoding module is obtained, so that the corresponding polarization state information can be quickly and accurately output according to the input metasurface response characteristics. The polarization decoding module provides an accurate and efficient decoding method based on the security detection logic of the present application.

[0034] S3: The light detection signal is incident on the metasurface for polarization adjustment, and the polarization decoding module is combined to perform surface response conversion and photoelectric conversion imaging to determine the detection polarization image.

[0035] In the embodiment of the present application, by combining the metasurface with the polarization decoding module, the light detection signal is polarized and converted, and finally the effective detection polarization image of the polarization part is determined. The data redundancy of security detection and identification is eliminated, which can effectively improve the detection accuracy and efficiency.

[0036] First, the light detection signal is guided to the metasurface as the information carrier to be processed. In this method, the metasurface is used as a key component for polarization adjustment. Through its unique structural design and material properties, the polarization state of the incident light detection signal can be precisely controlled and screened.

[0037] Next, the response information of the light detection signal after polarization adjustment of the metasurface is the coding characteristics that characterize the polarization state of the signal, namely the response intensity, phase change, etc., and then it is decoded to determine the specific polarization state of the signal. The polarization state is used to measure the characteristic information of the corresponding underground space position.

[0038] Then, in combination with the polarization decoding module, the response information is decoded, that is, the surface response characteristics are converted into corresponding polarization state information. And converted into digital signal form. Subsequently, these digital signals are sent to the photoelectric conversion imaging system for processing. The photoelectric conversion imaging system uses the principle of photoelectric effect to convert digital signals into visual image information. In this step, the polarization state information is presented in the form of intuitive and clear images through precise pixel mapping and color encoding technology.

[0039] Finally, after being processed by the photoelectric conversion imaging system, the present invention determines the detection polarization image representing the polarization state information, which provides an important basis for subsequent crack identification, classification and safety assessment.

[0040] S4: The detected polarization image is transmitted to the back-end detection module for identification and feature determination based on the pixel corner window to determine the spatial crack characteristics, wherein the determination is made by mining the mapping relationship between the light polarization state and the geological characteristics, and the pixel corner window represents the polarization state variation part.

[0041] Specifically, the detected polarization image is transmitted to a back-end detection module, which is responsible for receiving and analyzing image data from the front-end detection to achieve accurate identification and feature extraction of underground space cracks.

[0042] In the back-end detection module, the present invention adopts a recognition technology based on a pixel corner window. A pixel corner window is a local area used to locate feature points or edges in an image. In this method, the pixel corner window is used to characterize the polarization state trend, that is, those areas that reflect the existence of cracks or changes in crack characteristics. By setting a suitable window size and shape, the polarization state changes of the crack edge or internal structure can be accurately captured.

[0043] By traversing and searching the detected polarization image, all possible crack feature points or areas are found, that is, the boundaries with pixel transitions, including boundary pixels and edge pixels in the neighborhood area, so that complete image information can be represented and the effective image part can be retained for analysis to reduce the amount of data for image recognition judgment.

[0044] Preferably, in this process, the pixels in each window are analyzed one by one according to preset judgment criteria, such as corner point intensity, contrast, etc., to determine whether they belong to crack features.

[0045] Specifically, feature determination is performed based on the mapping relationship between the light polarization state and the geological characteristics. As an important reflection of the physical properties of underground space media, the light polarization state is closely related to the geological characteristics. By mining this mapping relationship, an in-depth understanding and accurate classification of crack characteristics can be achieved. In this method, the identified crack features are compared and analyzed one by one based on the known geological characteristics and polarization state data to determine their specific geological properties and crack types.

[0046] Finally, the characteristics of spatial cracks are determined. The characteristics not only include basic information such as the location, shape and size of the cracks, but also reflect the interaction between the cracks and the surrounding geological environment, providing an important basis for subsequent safety assessment and crack management.

[0047] Furthermore, the back-end detection module includes an image clipping block and a geological determination block, and the recognition based on the pixel corner window is performed. Step S4 of the present application includes:

[0048] The method further comprises: setting a window size, wherein the window size includes a central pixel and at least one group of neighboring pixels; traversing the detected polarization image, locating corner pixels based on the trend of pixels, wherein the corner pixels are pixels at the trend position; taking the corner pixels as the central pixels and combining the window size, determining an effective cropped image based on the detected polarization image.

[0049] In the embodiment of the present application, the window size is a rectangular or square area including a central pixel and at least one group of neighboring pixels, and its size and shape can be adjusted according to the actual application requirements. In the present method, the selection of the window size is intended to ensure that the crack characteristics can be fully captured while avoiding the introduction of excessive noise and redundant information. Specifically, the effective image part is cropped by the image cropping block, and the complete image information is retained on the basis of reducing the image data.

[0050] Then, each pixel in the detected polarization image is traversed, and the corner pixels are located based on the pixel trend. Corner pixels refer to pixel features, that is, pixels where the information measuring the polarization state changes. They are usually located at the edge of a crack or where the structure changes. By calculating the difference between each pixel and its neighboring pixels, including the direction and amount of change, it can be determined whether the pixel is a corner pixel. Exemplarily, a classic corner detection algorithm, such as Harris corner detection, can be used to automatically identify and locate corner pixels.

[0051] After locating the corner pixels, these corner pixels are used as the center pixels. Combined with the previously set window size, multiple pixel windows with the corner pixels as the center pixels are determined, and the spatial positions are spliced ​​to determine the effective cropped images based on the detected polarization image. Effective cropped images refer to those local image areas with a certain number of neighboring pixels centered on the corner pixels. These areas not only contain the key information of the crack characteristics, but also maintain relative integrity with the surrounding environment, providing a reliable data basis for subsequent feature extraction and crack identification.

[0052] In the specific implementation, by setting a reasonable window size and traversal strategy, it is ensured that each corner pixel can be accurately located and cropped. At the same time, in order to further improve the efficiency and accuracy of image processing, preferably, parallel processing technology and image preprocessing technology, such as image smoothing and denoising, can be used to optimize image quality and reduce computational complexity.

[0053] In summary, the accurate identification of the complete features of the underground space is achieved to determine the effective image information for subsequent analysis, which not only improves the accuracy and efficiency of crack identification, but also provides strong technical support for subsequent crack classification, safety assessment and management.

[0054] Further, to determine the characteristics of the spatial crack, step S4 of the present application includes:

[0055] The effective cropped image is traversed, combined with the geological determination block, and based on the mapping relationship between the light polarization state and the geological characteristics, pixel state characteristics are determined to determine the geological distribution image; based on the geological distribution image, the spatial fracture characteristics are identified and determined.

[0056] Specifically, based on the effective cropping of the image, the geological determination block is combined and the pixel state characteristics are determined according to the mapping relationship between the light polarization state and the geological characteristics. The geological determination block is constructed by sample-driven training until convergence based on the mapping relationship.

[0057] First, the effective cropped images are traversed, and each pixel in each cropped image is analyzed one by one to extract its light polarization state information. Then, the geological determination block identifies the geological features and determines whether it is a crack based on the mapping relationship, that is, the correspondence between different geological features, crack types, and light polarization states. During the traversal process, the geological features and crack types that match it are searched in the geological determination block based on the light polarization state information of each pixel.

[0058] When determining the pixel state characteristics, the mapping relationship between the light polarization state and the geological characteristics is mainly based on the mapping relationship obtained through a large amount of recorded data and geological statistical analysis, which reveals the intrinsic connection between the physical characteristics of the underground space medium and the light polarization state.

[0059] After determining the pixel state characteristics, the present invention obtains a geological distribution image. The geological distribution image is based on the effective clipping image and is obtained by coloring or encoding according to the geological characteristics and crack types of each pixel. It not only intuitively displays the geological distribution and crack characteristics of the underground space, but also provides an important basis for subsequent crack identification, classification and safety assessment.

[0060] Finally, based on the geological distribution image, the spatial crack characteristics are identified and determined to determine the location, shape, size, geological attributes and other information of the cracks. This not only improves the accuracy and efficiency of crack identification, but also provides a strong technical guarantee for the safety monitoring and management of underground space.

[0061] Further, after determining the spatial crack characteristics, step S4 of the present application includes:

[0062] Identify the spatial crack characteristics and locate the point cloud detection target, wherein the point cloud detection target is the fuzzy feature part, and is located based on the three-dimensional coordinates of the underground space area; for the point cloud detection target, perform point cloud infrared polarization detection in combination with the infrared polarization detector to determine the point cloud detection signal; perform polarization debugging and decoding judgment on the point cloud detection signal to compensate for the spatial crack characteristics.

[0063] In the embodiment of the present application, due to the full-area infrared polarization scanning method, it is impossible to take into account information such as detailed features, which may affect the subsequent detection accuracy of spatial cracks. In order to more accurately identify and locate the spatial crack characteristics, especially those fuzzy feature parts, the present invention combines three-dimensional coordinate positioning technology with infrared polarization detection technology to conduct in-depth detection and analysis of crack characteristics.

[0064] First, identifying spatial fracture features involves extracting and analyzing fracture information in geological distribution images to determine fracture location, shape, size, etc. In this process, special attention is paid to those fuzzy features, that is, those fracture features that are difficult to accurately identify due to complex geological conditions or limited detection conditions.

[0065] Then, in order to locate these fuzzy features, the 3D coordinate positioning technology constructs a 3D model of the underground space by measuring the 3D coordinates of each point in the underground space. On this basis, combined with the results of crack feature recognition, the fuzzy features can be accurately located at a specific location in the 3D model.

[0066] For the located point cloud detection target (i.e. the blurred feature part), point cloud infrared polarization detection is performed based on the infrared polarization detector. The sensitivity of polarized light to the physical properties of the medium can capture the changes in polarization state caused by crack features. By scanning the entire point cloud detection target area, the infrared polarization detector generates point cloud detection signals, which contain polarization information of crack features.

[0067] Subsequently, the present invention performs polarization debugging and decoding judgment on the point cloud detection signal. The specific detection and polarization analysis steps are the same as above. Finally, the spatial crack characteristics are compensated for the crack feature information after decoding judgment, aiming to correct the crack feature recognition deviation caused by detection condition limitations or data processing errors, thereby obtaining a more accurate crack feature recognition result.

[0068] In summary, the accurate identification and positioning of underground space crack characteristics is achieved. This method not only improves the accuracy and efficiency of crack identification, but also provides strong technical support for the safety monitoring and management of underground space.

[0069] S5: Based on the characteristics of the space cracks, safety warning management is performed on the underground space area.

[0070] Further, such as Figure 2 As shown, based on the spatial crack characteristics, before performing safety early warning management on the underground space area, step S5 of the present application includes:

[0071] For the underground space area, underground construction information is determined, wherein the underground construction information at least includes pipeline network distribution; critical risk characteristics based on spatial cracks are determined in combination with the underground construction information; based on the critical risk characteristics, a spatial safety evaluation map is constructed; and according to the spatial safety evaluation map, risk rating of the spatial crack characteristics is performed.

[0072] In the embodiment of the present application, in order to comprehensively evaluate the safety status of the underground space, the present invention not only focuses on the crack characteristics themselves, but also deeply combines the underground construction information, conducts a detailed analysis of the critical risks that may be caused by the cracks, and constructs a space safety evaluation map based on this, thereby realizing the risk rating of the crack characteristics.

[0073] First, for the underground space area, the underground construction information is determined. Underground construction information refers to the distribution and attribute information of various buildings, structures and pipelines in the underground space, which is the basis for underground space safety assessment. Their layout and status directly affect the safety and stability of the underground space.

[0074] Combined with underground construction information, critical risk characteristics based on space cracks are determined. Critical risk characteristics refer to those risk points that may cause damage or functional failure of underground construction facilities due to the existence of cracks. These characteristics not only take into account the location, shape and size of the cracks themselves, but also integrate factors such as the relative position relationship between the cracks and underground construction facilities, and the material and structural characteristics of the facilities. By deeply analyzing these factors and combining historical risk data mining, it is possible to accurately identify those crack characteristics that may pose a threat to underground space safety.

[0075] Based on the critical risk characteristics, a spatial safety evaluation map was constructed, which is a visualization tool that directly displays the safety status of underground space, integrating underground construction information, crack characteristics, and critical risk characteristics on one map. This map not only shows the specific location and form of crack characteristics, but also marks areas of different risk levels with different colors or symbols, providing an intuitive basis for subsequent risk rating.

[0076] Finally, based on the spatial safety evaluation map, the spatial crack characteristics were rated by taking into account multiple factors such as crack characteristics, underground construction information, and critical risk characteristics. The crack characteristics were divided into different risk levels.

[0077] Preferably, the risk rating adopts a combination of quantitative and qualitative methods, which not only takes into account the objective attributes of crack characteristics, but also incorporates expert experience and expertise, thereby ensuring the accuracy and reliability of the rating results.

[0078] In summary, by determining underground construction information, determining critical risk characteristics in combination with underground construction information, constructing a space safety evaluation map, and performing risk rating on space crack characteristics, the present invention achieves a comprehensive assessment and risk warning of underground space crack characteristics. This not only improves the scientificity and effectiveness of underground space safety management, but also provides strong support for the planning, construction, and operation and maintenance of underground space.

[0079] Furthermore, safety early warning management is performed on the underground space area. Step S5 of this application includes:

[0080] Interact with upper-level detection data of the underground space cracks, wherein the upper-level detection data is the spatial crack characteristics of the previous detection node; perform spatial mapping between the upper-level detection data and the spatial crack characteristics, calibrate and locate crack trend characteristics, wherein the crack trend characteristics are marked with underground space coordinates; generate dynamic early warning information based on space safety according to the crack trend characteristics in combination with the space safety evaluation map.

[0081] In the infrared polarization safety detection method for underground space cracks, in order to realize continuous monitoring and dynamic early warning of crack characteristics, the present invention introduces upper-level detection data, and spatially maps and calibrates it with the currently detected spatial crack characteristics, thereby accurately locating the trend characteristics of the cracks and generating dynamic early warning information based on space safety.

[0082] First, the upper detection data of underground space cracks are called. The upper detection data refers to the spatial crack feature data obtained from the previous detection node, that is, the previous detection. These data contain information such as the location, shape, size, and possible development trend of the cracks, and are an important reference for this detection. By obtaining the upper detection data, the present invention can realize continuous observation of crack characteristics, thereby more accurately grasping the development dynamics of the cracks.

[0083] Then, the upper detection data and the currently detected spatial crack features are spatially mapped. Spatial mapping refers to the process of aligning and matching the crack feature data at different locations in space. By accurately checking the position, shape, size and other information of the crack features, the crack trend characteristics can be identified, that is, the changes in the cracks from the upper detection node to the current time interval. It can intuitively display the evolution process of the cracks and provide strong support for subsequent analysis and early warning.

[0084] Then, through positioning, the corresponding underground space coordinates are assigned to the specific location of the crack trend characteristics in the underground space. These coordinate information not only helps to accurately describe the location of the crack, but also provides an important basis for the subsequent early warning information release and emergency response.

[0085] Finally, according to the crack trend characteristics and the space safety evaluation map, dynamic warning information based on space safety is generated, including a detailed description of the crack trend characteristics, possible safety risks, and corresponding preventive measures. By issuing dynamic warning information, the present invention can timely remind relevant personnel to pay attention to the changes in crack characteristics and take necessary measures to ensure the safety of underground space.

[0086] In summary, the continuous monitoring and dynamic early warning of underground space crack characteristics are realized. This method not only improves the real-time and accuracy of crack monitoring, but also provides strong technical support for the safety management of underground space.

[0087] The present application provides a method for safe detection of infrared polarization of cracks in urban underground spaces, which has the following technical effects:

[0088] 1. By introducing metasurfaces, the signals of infrared polarization detection are responded and decoded based on the polarization part to determine the image information based on polarization characteristics. By designing a polarization decoding module based on metasurfaces, collaborative processing is performed to retain polarization information that measures crack information, eliminate invalid information, and improve the efficiency and accuracy of subsequent analysis. For polarization state imaging, a corner point window method is used to crop images with pixel transitions to reduce image information and retain complete image information. Combined with metasurface response-light polarization state-geological characteristics for processing, the accuracy and efficiency of crack feature detection in underground space areas can be effectively improved.

[0089] 2. By constructing a spatial safety evaluation map, combining underground construction information with crack characteristics, and deeply analyzing factors such as the relative position relationship between cracks and underground facilities, the material and structural characteristics of the facilities, the critical risk characteristics based on spatial cracks are determined. The upper detection data is spatially mapped with the currently detected crack characteristics to achieve accurate calibration and positioning of crack trend characteristics. A comprehensive and systematic assessment of the safety risks that may be caused by cracks is achieved, the development dynamics of cracks are grasped, and abnormal conditions of cracks can be discovered in a timely manner, providing an important basis for the release of early warning information.

[0090] In summary, the accurate identification, comprehensive assessment, continuous observation and real-time early warning of underground space crack characteristics have been achieved, providing strong technical support and guarantee for the safe management of underground space.

[0091] Through the above-mentioned detailed description of a method for safe detection of urban underground space cracks by infrared polarization in this specification, those skilled in the art can clearly know the method for safe detection of urban underground space cracks by infrared polarization in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0092] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A safety detection method of infrared polarization of cracks in urban underground space, characterized in that: The method comprises: For underground space areas, polarization calibration is performed on infrared polarization detectors, full-area infrared polarization detection is performed, and light detection signals are determined; The structural information of the interactive metasurface is used to construct a polarization decoding module based on the mapping relationship between the metasurface response and the light polarization state, and a connection is established between the polarization decoding module and the metasurface; The light detection signal is incident on the metasurface for polarization adjustment, and the polarization decoding module is combined to perform surface response conversion and photoelectric conversion imaging to determine the detection polarization image; The detected polarization image is transmitted to the back-end detection module for identification and feature determination based on the pixel corner window to determine the spatial crack features, wherein the determination is made by mining the mapping relationship between the light polarization state and the geological features, and the pixel corner window represents the polarization state variation part; Based on the characteristics of the space cracks, safety warning management is performed on the underground space area.

2. A safety detection method for infrared polarization of cracks in urban underground space as claimed in claim 1, characterized in that: After determining the characteristics of the space crack, including: Identify the spatial crack features and locate a point cloud detection target, wherein the point cloud detection target is a fuzzy feature portion, based on the three-dimensional coordinates of the underground space area; For the point cloud detection target, point cloud infrared polarization detection is performed in combination with the infrared polarization detector to determine a point cloud detection signal; Polarization adjustment and decoding determination are performed on the point cloud detection signal, and the spatial crack characteristics are compensated.

3. The infrared polarization safety detection method for urban underground space cracks according to claim 1, characterized in that: Build a polarization decoding module, including: Determining modulation characteristics of selective permeability according to the structural information, wherein the modulation of the amplitude and phase of the light field by the meta-atom is used as a principle; The polarization decoding module is constructed based on the modulation characteristics.

4. A safe detection method of infrared polarization of cracks in urban underground space as claimed in claim 3, characterized in that: The polarization decoding module is constructed, including: Interactive polarization decoding samples, wherein the polarization decoding samples include response samples with different polarization states determined based on the metasurface test - polarization state samples, and the metasurface response includes at least response intensity and phase distribution; According to the polarization decoding samples, a polarization decision tree is constructed and trained until convergence, and the polarization decoding module is determined.

5. The infrared polarization safety detection method for urban underground space cracks according to claim 1, characterized in that: The back-end detection module includes an image clipping block and a geological determination block, and the recognition based on the pixel corner window includes: Setting a window size, wherein the window size includes a central pixel and at least one group of neighboring pixels; Traversing the detected polarization image, locating corner pixels based on the trend of pixels, wherein the corner pixels are pixels at the trend position; Taking the corner pixel as the center pixel and combining the window size, an effective cropped image based on the detected polarization image is determined.

6. A safe detection method of infrared polarization of cracks in urban underground space as claimed in claim 5, characterized in that: Determine the characteristics of space cracks, including: Traversing the effective cropped image, combining the geological determination block, determining pixel state characteristics based on the mapping relationship between light polarization state and geological characteristics, and determining a geological distribution image; According to the geological distribution image, the spatial fracture characteristics are identified and determined.

7. The infrared polarization safety detection method for urban underground space cracks according to claim 1, characterized in that: Based on the spatial crack characteristics, before performing safety early warning management on the underground space area, the steps include: Determining underground construction information for the underground space area, wherein the underground construction information at least includes pipe network distribution; Determining critical risk characteristics based on spatial cracks in combination with the underground construction information; Based on the critical risk characteristics, construct a space safety assessment map; According to the space safety assessment map, risk rating is performed on the space crack characteristics.

8. A safe detection method of infrared polarization of cracks in urban underground space as claimed in claim 7, characterized in that: Conduct safety early warning management on the underground space area, including: Interacting upper level detection data of the underground space cracks, wherein the upper level detection data is the space crack characteristics of the previous detection node; Performing spatial mapping between the upper detection data and the spatial crack features, and checking and locating the crack trend characteristics, wherein the crack trend characteristics are marked with underground spatial coordinates; According to the crack trend characteristics and in combination with the space safety evaluation map, dynamic early warning information based on space safety is generated.

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