Tunnel disease detection array control method, device, equipment, medium and product

Abstract

The present application discloses a tunnel disease detection array control method, device, equipment, medium and product, relating to the technical field of engineering detection. The tunnel disease detection array control method includes: obtaining tunnel parameters of a tunnel to be detected; determining target detection positions and target detection angles of a plurality of detection sensors according to the tunnel parameters; adjusting the positions and angles of the plurality of detection sensors based on the target detection positions and target detection angles, and performing disease detection on the tunnel to be detected by the adjusted plurality of detection sensors to obtain a tunnel disease detection result. The present application realizes tunnel disease detection based on dynamic position and angle adjustment of detection sensors, solves the problem of low detection efficiency of existing tunnel disease detection methods, and improves the detection efficiency and accuracy of tunnel disease detection.

Description

Technical Field

[0001] The present application relates to the technical field of engineering detection, and particularly to a method, device, equipment, medium and product for controlling a tunnel disease detection array. Background Art

[0002] Due to the influence of tunnel terrain, geology, climate conditions, and various factors during the design and construction processes, tunnels will have diseases to varying degrees during the construction process and even in the later use process. A camera array is used to detect the disease conditions existing in the tunnel.

[0003] However, this tunnel disease detection method requires stitching the images collected by different cameras into a complete cross-sectional image of the tunnel. Due to the complex structure of the tunnel inner wall, the image quality collected by different cameras is usually unstable, and it is difficult to achieve fast stitching to meet the real-time requirements of tunnel disease detection, resulting in low efficiency of tunnel disease detection.

[0004] The above content is only used to assist in understanding the technical solution of the present application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of the present application is to provide a method, device, equipment, medium and product for controlling a tunnel disease detection array, aiming to solve the technical problem of low detection efficiency of the existing tunnel disease detection method.

[0006] To achieve the above purpose, the present application proposes a method for controlling a tunnel disease detection array. The method is applied to a tunnel detection platform, and the tunnel detection platform is configured with a detection array. The detection array includes a plurality of detection sensors, and the method includes:

[0007] Obtain the tunnel parameters of the tunnel to be detected;

[0008] According to the tunnel parameters, determine the target detection positions and target detection angles of the plurality of detection sensors;

[0009] Based on the target detection positions and target detection angles, adjust the positions and angles of the plurality of detection sensors, and perform disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

[0010] In an embodiment, the step of determining the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters includes:

[0011] According to the tunnel parameters and the structural parameters of the detection array, determine the target detection axis of the detection array;

[0012] Based on the target detection axis center, determine the target detection positions and target detection angles of the plurality of detection sensors.

[0013] In one embodiment, the step of determining the target detection axis center of the detection array according to the tunnel parameters and the structural parameters of the detection array includes:

[0014] Based on the tunnel parameters, construct a cross-sectional plane coordinate system of the tunnel to be detected;

[0015] According to the structural parameters of the detection array, obtain the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system;

[0016] According to the target detection position coordinates, determine the target detection axis center of the detection array.

[0017] In one embodiment, the step of determining the target detection positions and target detection angles of the plurality of detection sensors based on the target detection axis center includes:

[0018] According to the structural parameters of the detection array, obtain the field of view angles and spacing ranges of the plurality of detection sensors;

[0019] Based on the target detection axis center, perform calculations according to the field of view angles and spacing ranges to obtain the target detection positions and target detection angles of the plurality of detection sensors.

[0020] In one embodiment, the detection array further includes a plurality of distance measurement sensors, a plurality of electric push rods, and a plurality of rotating motors, and the plurality of detection sensors are connected by the electric push rods and / or the rotating motors.

[0021] The step of adjusting the positions and angles of the plurality of detection sensors based on the target detection positions and target detection angles includes:

[0022] Adjust the positions of the plurality of detection sensors to the target detection positions through the plurality of distance measurement sensors and the plurality of electric push rods;

[0023] Adjust the angles of the plurality of detection sensors to the target detection angles through the plurality of rotating motors.

[0024] In one embodiment, the step of performing disease detection on the tunnel to be detected by the adjusted plurality of detection sensors to obtain a tunnel disease detection result includes:

[0025] Perform disease detection on the inner wall of the tunnel to be detected through the adjusted plurality of detection sensors to obtain a plurality of disease detection images;

[0026] Perform image stitching on the several disease detection images based on the target detection position and the target detection angle to obtain a three-dimensional view of tunnel disease detection;

[0027] Obtain the tunnel disease detection result according to the three-dimensional view of tunnel disease detection.

[0028] In addition, to achieve the above object, the present application also proposes a tunnel disease detection array control device, the tunnel disease detection array control device is configured with a detection array, the detection array includes a plurality of detection sensors, including:

[0029] A parameter acquisition module for acquiring tunnel parameters of a tunnel to be detected;

[0030] A position determination module for determining the target detection position and the target detection angle of the plurality of detection sensors according to the tunnel parameters;

[0031] An adjustment detection module for adjusting the positions and angles of the plurality of detection sensors based on the target detection position and the target detection angle, and performing disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

[0032] In addition, to achieve the above object, the present application also proposes a tunnel disease detection array control device, the device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program is configured to implement the steps of the tunnel disease detection array control method as described above.

[0033] In addition, to achieve the above object, the present application also proposes a storage medium, the storage medium is a computer-readable storage medium, a computer program is stored on the storage medium, and when the computer program is executed by a processor, it implements the steps of the tunnel disease detection array control method as described above.

[0034] In addition, to achieve the above object, the present application also provides a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, it implements the steps of the tunnel disease detection array control method as described above.

[0035] The present application provides a method for controlling a tunnel disease detection array. First, detailed parameters of the tunnel to be detected for diseases are obtained, providing basic data for the layout and adjustment of subsequent detection sensors. Then, based on the tunnel parameters, the optimal positions and angles of the detection sensors are determined, and the sensor layout is further optimized through a dynamic adjustment mechanism to adapt to the actual deformation of the tunnel. Finally, by adjusting the positions and angles of the detection sensors, it is ensured that the sensors can accurately cover the key areas of the inner wall of the tunnel. Utilizing the real-time feedback and dynamic adjustment of the sensors further improves the detection efficiency and accuracy. The tunnel disease detection based on the dynamic position and angle adjustment of the detection sensors is realized, solving the problem of low detection efficiency of the existing tunnel disease detection methods and improving the detection efficiency and accuracy of tunnel disease detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application and used together with the specification to explain the principles of the present application.

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a schematic flowchart provided for the first embodiment of the tunnel disease detection array control method of the present application;

[0039] Figure 2 It is a schematic flowchart provided for the second embodiment of the tunnel disease detection array control method of the present application;

[0040] Figure 3 It is a schematic structural diagram of a detection component provided for the second embodiment of the tunnel disease detection array control method of the present application;

[0041] Figure 4 It is a schematic structural diagram of a detection array provided for the second embodiment of the tunnel disease detection array control method of the present application;

[0042] Figure 5 It is another schematic structural diagram of a detection array provided for the second embodiment of the tunnel disease detection array control method of the present application;

[0043] Figure 6 It is a schematic module structure diagram of the tunnel disease detection array control device in the embodiments of the present application;

[0044] Figure 7 It is a schematic device structure diagram of the hardware operating environment involved in the tunnel disease detection array control method in the embodiments of the present application.

[0045] The realization of the purpose, functional features and advantages of this application will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific embodiments

[0046] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0047] To better understand the technical solutions of this application, the following will be described in detail in conjunction with the drawings of the specification and specific embodiments.

[0048] The main solution of the embodiment of this application is: obtaining tunnel parameters of a tunnel to be detected; determining target detection positions and target detection angles of a plurality of detection sensors according to the tunnel parameters; adjusting the positions and angles of the plurality of detection sensors based on the target detection positions and target detection angles, and performing disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

[0049] The existing tunnel disease detection method collects image data of the inner wall of the tunnel through a camera array, and combines the image data collected by different cameras into a complete image of the inner wall of the tunnel through image stitching. Usually, the positions and angles of the camera array are relatively fixed and need to be adjusted manually. Due to the structural complexity of the inner wall of the tunnel, the angles of the cameras need to be adjusted multiple times during the whole tunnel detection to adapt to the changes in the tunnel environment. Moreover, the image quality collected by different cameras is different, and it is impossible for humans to accurately adjust the boundaries of the perspectives of different cameras. The smoothness and continuity of different camera images are different, making it difficult to achieve fast image stitching and display it to on-site detection personnel in real time, resulting in low efficiency of tunnel disease detection.

[0050] This application first obtains the detailed parameters of the tunnel that needs disease detection, providing basic data for the layout and adjustment of subsequent detection sensors; then, based on the tunnel parameters, determines the optimal positions and angles of the detection sensors, and further optimizes the sensor layout through a dynamic adjustment mechanism to adapt to the actual deformation of the tunnel; finally, by adjusting the positions and angles of the detection sensors, ensures that the sensors can accurately cover the key areas of the inner wall of the tunnel, and uses the real-time feedback and dynamic adjustment of the sensors to further improve the detection efficiency and accuracy. It realizes tunnel disease detection based on the dynamic position and angle adjustment of detection sensors, solves the problem of low detection efficiency of the existing tunnel disease detection method, and improves the detection efficiency and accuracy of tunnel disease detection.

[0051] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a tunnel disease detection array control device, etc. that can implement the above functions. Hereinafter, taking the tunnel disease detection array control device as an example, this embodiment and the following embodiments will be described.

[0052] Based on this, the embodiment of the present application provides a tunnel disease detection array control method. Refer to Figure 1 , Figure 1 which is a schematic flowchart of the first embodiment of the tunnel disease detection array control method of the present application.

[0053] In this embodiment, the tunnel disease detection array control method is applied to a tunnel detection platform, and the tunnel detection platform is configured with a detection array. The detection array includes a plurality of detection sensors, and the method includes steps S10 to S30:

[0054] Step S10, obtaining tunnel parameters of the tunnel to be detected;

[0055] It should be noted that the detection array is an array composed of a plurality of detection sensors for collecting data on the inner wall of the tunnel. Usually, the detection sensors in the detection array will collect data at different angles. The detection sensor is a device for collecting data on the inner wall of the tunnel, such as a camera, a radar, a ranging sensor, etc., which can obtain the distance of the inner wall of the tunnel and tunnel detection data.

[0056] In addition, it should be noted that the tunnel parameters refer to data related to the tunnel structure and environment, including geometric parameters (such as the central axis, radius, inner wall radian, length, cross-sectional shape, etc. of the tunnel) and environmental parameters (such as the illumination level of the tunnel), which can be collected by instruments such as a laser scanner and an environmental sensor.

[0057] It can be understood that in order to provide detailed information about the tunnel and provide basic data for the layout and adjustment of subsequent detection sensors, the tunnel parameters of the tunnel to be detected for tunnel disease detection are obtained to ensure that the detection sensors can be accurately configured according to the actual shape and environment of the tunnel.

[0058] Step S20, determining the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters;

[0059] It should be noted that the target detection position refers to the optimal layout position of the detection sensor on the inner wall of the tunnel, which can ensure that the detection sensor can cover the key areas of the inner wall of the tunnel. The target detection angle refers to the optimal detection angle of different detection sensors relative to the inner wall of the tunnel, ensuring that the field of view of the entire detection array can cover the inner wall of the tunnel and avoiding detection blind spots.

[0060] It is understandable that, in order to ensure that the detection sensors can cover all areas to be detected on the inner wall of the tunnel and can obtain image data with image quality meeting the requirements of real-time image stitching, based on the tunnel parameters and the structural parameters of the detection array (such as sensor spacing, coverage range), the optimal detection positions and detection angles of all detection sensors inside the tunnel are determined to optimize the layout of the detection sensors, improve the detection efficiency and data quality, and provide accurate sensor configuration for subsequent disease detection.

[0061] Step S30: Based on the target detection position and target detection angle, adjust the positions and angles of the several detection sensors, and perform disease detection on the tunnel to be detected by the adjusted several detection sensors to obtain the tunnel disease detection result.

[0062] It should be noted that the tunnel disease detection result refers to the result obtained after disease detection of the tunnel, which can be presented in visual and text forms, and may include content such as the inner wall image of the tunnel, the three-dimensional model of the inner wall, and the existing diseases (such as disease positions, types, and severities).

[0063] It is understandable that, in order to achieve the precise positioning and angle adjustment of the sensors, ensure the accuracy and real-time nature of the detection results, combine the feedback information of the sensors, dynamically adjust the positions and angles of these detection sensors, use the dynamically adjusted detection sensors to collect the apparent disease feature data and hidden disease feature data of the inner wall of the tunnel, and identify diseases through data processing and analysis techniques, realizing automatic and efficient tunnel disease detection, and at the same time generating detailed disease detection results to provide a basis for tunnel maintenance.

[0064] In a feasible implementation manner, the step of determining the target detection position and target detection angle of the several detection sensors according to the tunnel parameters includes:

[0065] Step S201: Determine the target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array;

[0066] It should be noted that the target detection axis is the basis for the layout of the detection array, and is used to ensure that the detection sensors in the detection array can accurately and completely cover the key areas on the inner wall of the tunnel that need disease detection.

[0067] It can be understood that, in order to ensure that the detection sensors can accurately cover the key areas of the tunnel inner wall and provide a basis for adjusting the position and angle of the detection sensors, by combining the geometric parameters of the tunnel (such as radius, radian, cross-sectional shape) and the structural parameters of the detection array (such as sensor spacing, coverage range), the optimal axis position detected by the detection array can be determined, and this is used as the reference point for the detection sensors, improving the detection efficiency and data quality and reducing the detection blind area.

[0068] Step S202: Based on the target detection axis, determine the target detection positions and target detection angles of the several detection sensors.

[0069] It can be understood that, in order to ensure that the detection sensors can adapt to the geometric shape and deformation of the tunnel and achieve efficient and accurate detection, based on the target detection axis, further optimize the layout of the detection sensors, determine the optimal detection positions and angles of different detection sensors when collecting data, and reduce the detection data acquisition error caused by tunnel deformation by dynamically adjusting the position and angle of the sensors.

[0070] In this embodiment, first, according to the tunnel parameters and the structural parameters of the detection array, determine the target detection axis of the detection array, which can quickly determine the axis of the detection array and provide a basis for the layout of the detection sensors; according to the detection axis and the tunnel parameters, optimize the target detection positions and angles of the sensors to ensure that they can adapt to the geometric shape and deformation of the tunnel, not only improving the layout accuracy of the detection sensors, but also enhancing the detection efficiency and data quality through the dynamic adjustment mechanism.

[0071] In a feasible embodiment, the step of determining the target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array includes:

[0072] Step S2011: Based on the tunnel parameters, construct a cross-sectional plane coordinate system of the tunnel to be detected.

[0073] It should be noted that, in the actual process of tunnel disease detection, the cross-sections evenly distributed in the tunnel are usually used as the units for tunnel disease detection, and the disease detection of the entire tunnel will collect the detection data of all cross-sections along the extension direction of the tunnel. The cross-sectional plane coordinate system is a two-dimensional coordinate system used to describe the geometric relationship within the tunnel cross-section (section), and the tunnel center can be used as the origin of the coordinate system.

[0074] It can be understood that, in order to provide a clear geometric reference framework for the target detection axis of the detection array and ensure the accuracy and consistency of the sensor layout, constructing a cross-sectional plane coordinate system based on the tunnel parameters can simplify the calculation process and improve the layout accuracy.

[0075] Step S2012: Obtain the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system according to the structural parameters of the detection array;

[0076] It should be noted that the structural parameters of the detection array may include the physical characteristics of the detection array (such as the number of sensors, spacing, coverage range, field of view angle, etc.) and the layout method (such as linear arrangement, circular arrangement or grid arrangement). The target detection position coordinates refer to the nearest detection position coordinates of the detection array in the cross-sectional plane coordinate system, corresponding to the core position in the detection array, such as the support structure where the detection array is connected to the tunnel diagnosis platform.

[0077] It can be understood that in order to determine the nearest detection position and position of each sensor in the detection array to collect a set of images with consistent smoothness and continuity of the tunnel inner wall, according to the structural parameters of the detection array and the cross-sectional plane coordinate system, calculate the target detection position coordinates of each sensor to ensure that the detection sensors can cover the key areas of the tunnel inner wall, provide specific position information for the determination of the target detection axis, and optimize the sensor layout.

[0078] Step S2013: Determine the target detection axis of the detection array according to the target detection position coordinates.

[0079] It should be noted that the target detection axis will change according to the actual deformation situation and detection requirements of the tunnel, that is, when the structural parameters corresponding to adjacent cross-sections of the tunnel change, the target detection axis will also change dynamically.

[0080] It can be understood that in order to provide a clear geometric definition for the target detection axis and ensure that the overall layout of the detection array can adapt to the geometric shape of the tunnel, the target detection axis of the detection array can be determined by calculating the geometric center of the sensor position coordinates or fitting a curve to guide the dynamic adjustment of the sensor and disease detection.

[0081] In this embodiment, first, a plane coordinate system of the tunnel cross-section is constructed, providing a unified reference framework for sensor layout. Then, according to the structural parameters of the detection array, the target detection position coordinates of each sensor are determined, optimizing the sensor layout to ensure that the sensors can cover the key areas of the tunnel inner wall and reduce detection blind spots; finally, according to the target detection position coordinates of each sensor, the target detection axis of the detection array is determined to adapt to the complex geometric shape of the tunnel and improve the accuracy and reliability of detection data collection.

[0082] In a feasible embodiment, the step of determining the target detection positions and target detection angles of the plurality of detection sensors based on the target detection axis includes:

[0083] Step S2021: Obtain the field of view angles and spacing ranges of the plurality of detection sensors according to the structural parameters of the detection array.

[0084] It should be noted that the field of view angle refers to the angular range of the space that the detection sensor can detect, which determines the size of the area covered by the sensor and affects the detection range. The spacing range refers to the distance range between the detection sensors, which determines the relative positions of the detection sensors and the layout density of the detection array, and affects the accuracy of the detection data acquisition.

[0085] It can be understood that to provide the necessary parameter support for subsequent calculation of the target detection positions and angles of the sensors, ensure the rationality of the sensor layout and the comprehensiveness of the detection, according to the structural parameters of the detection array, obtain the field of view angles and spacing ranges of each detection sensor, so as to optimize the overall field of view angle and spacing range of the detection array, determine the optimal positions and detection directions of each detection sensor, and ensure that the coverage areas between different detection sensors can be seamlessly connected.

[0086] Step S2022: Based on the target detection axis, calculate according to the field of view angles and spacing ranges to obtain the target detection positions and target detection angles of the plurality of detection sensors.

[0087] It can be understood that in order to ensure that the sensors can accurately cover the key areas of the tunnel inner wall and adapt to the geometric shape of the tunnel and the changes in different cross-sections, based on the target detection axis, combined with the field of view angles and spacing ranges of the detection sensors, calculate the optimal target detection positions and angles of each detection sensor through mathematical modeling and optimization algorithms.

[0088] In this embodiment, taking the target detection axis as the reference, combined with the field of view angles and spacing ranges of the sensors, calculate the target detection positions and angles of each sensor as the parameters for adjusting the spacing of the detection array and the angles of the sensors. Through the dynamic adjustment mechanism, it can adapt to the dynamic changes of the tunnel, reduce the detection error, and improve the comprehensiveness and accuracy of the detection.

[0089] This embodiment provides a method for controlling a tunnel disease detection array. First, obtain the detailed parameters of the tunnel that needs disease detection, providing the basic data for the subsequent layout and adjustment of the detection sensors; then, determine the optimal positions and angles of the detection sensors based on the tunnel parameters, and further optimize the sensor layout through the dynamic adjustment mechanism to adapt to the actual deformation of the tunnel; finally, by adjusting the positions and angles of the detection sensors, ensure that the sensors can accurately cover the key areas of the tunnel inner wall, and utilize the real-time feedback and dynamic adjustment of the sensors to further improve the detection efficiency and accuracy. It realizes the tunnel disease detection based on the dynamic position and angle adjustment of the detection sensors, solves the problem of low detection efficiency of the existing tunnel disease detection methods, and improves the detection efficiency and accuracy of the tunnel disease detection.

[0090] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar content as that in the above first embodiment can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 2 , Figure 2 which is a schematic flowchart of the second embodiment of the tunnel disease detection array control method of the present application.

[0091] In this embodiment, the detection array further includes a plurality of distance sensors, a plurality of electric push rods, and a plurality of rotating motors. The plurality of detection sensors are connected by the electric push rods and / or the rotating motors.

[0092] The step of adjusting the positions and angles of the plurality of detection sensors based on the target detection position and the target detection angle includes:

[0093] Step S3011, adjusting the positions of the plurality of detection sensors to the target detection position through the plurality of distance sensors and the plurality of electric push rods;

[0094] It should be noted that the distance sensor is a sensor used to measure the distance between the detection sensor and the inner wall of the tunnel, and is used to provide real-time feedback for the position adjustment of the sensor. The electric push rod is an electric driving device used to adjust the position of the detection sensor, and can push or pull the sensor to the target position according to the feedback of the distance sensor.

[0095] It can be understood that in order to ensure that the detection sensor can be accurately positioned at the target detection position, the distance between the detection sensor and the inner wall of the tunnel is measured in real time by the distance sensor, and the position of each detection sensor is adjusted by the electric push rod to make it reach the target detection position, so as to ensure that the distances between different sensors and the inner wall of the tunnel are consistent, so that the smoothness and continuity of the collected detection data can meet the real-time requirements of detection.

[0096] Exemplarily, a PID (Proportion Integration Differentiation) controller or other closed-loop control algorithms can be used to optimize the adjustment strategy of the electric push rod by combining the feedback of multiple distance sensors, and dynamically adjust the telescopic length of the electric push rod to ensure that the sensor positions are distributed according to the shape change of the inner wall of the tunnel.

[0097] Step S3012, adjusting the angles of the plurality of detection sensors to the target detection angle through the plurality of rotating motors.

[0098] It is understandable that in order to ensure that the detection sensor can cover the inner wall of the tunnel at the optimal angle and improve the comprehensiveness and accuracy of detection, a rotating motor is used to adjust the angle of the detection sensor to reach the target detection angle. Among them, the adjustment of the rotating motor can be determined by combining the target detection angle of the sensor and the real-time feedback.

[0099] In a feasible implementation manner, the step of performing disease detection on the to-be-detected tunnel by the adjusted plurality of detection sensors to obtain a tunnel disease detection result includes:

[0100] Step S3021: Use the adjusted plurality of detection sensors to perform disease detection on the inner wall of the to-be-detected tunnel to obtain a plurality of disease detection images;

[0101] It is understandable that in order to understand the disease conditions of the inner wall of the tunnel, the adjusted detection sensors (such as cameras, radars, etc.) are used to perform disease detection on the inner wall of the tunnel, collect image data of the inner wall of the tunnel for subsequent image stitching. The multiple detection sensors that have been adjusted in position and angle can accurately cover the inner wall of the tunnel, and can collect high-quality disease detection images to achieve fast image stitching.

[0102] Step S3022: Based on the target detection position and the target detection angle, perform image stitching on the plurality of disease detection images to obtain a three-dimensional view of the tunnel disease detection;

[0103] It should be noted that usually the disease detection images are two-dimensional plane images. The target detection position and the target detection angle can provide a geometric reference for the image stitching of the three-dimensional view. Multiple images can be stitched together by extracting feature points (such as corner points, edges) in the images and using a matching algorithm. Then, the stitched image data is converted into a three-dimensional model, and the disease distribution on the inner wall of the tunnel is displayed through visualization means.

[0104] It is understandable that to provide intuitive visual support for disease detection, using the target detection position and angle information, multiple disease detection images are stitched together to generate a three-dimensional view of the tunnel disease detection on the inner wall of the tunnel. Through the three-dimensional view, the disease distribution on the inner wall of the tunnel can be more intuitively displayed, which is convenient for subsequent analysis and repair.

[0105] Step S3023: Obtain a tunnel disease detection result according to the three-dimensional view of the tunnel disease detection.

[0106] It is understandable that according to the three-dimensional view of the tunnel disease detection, the disease parts (such as cracks, leaks, spalling, etc.) can be identified through image recognition technology, and the disease positions are marked in the three-dimensional view to generate a disease detection report, realizing visual disease detection and early warning, and providing support for tunnel on-site detection personnel.

[0107] In this embodiment, first, a plurality of adjusted detection sensors are used to obtain high-quality disease detection images. Then, based on the target detection position and angle, a plurality of disease detection images are stitched to generate a three-dimensional view of tunnel disease detection. Through image stitching and three-dimensional modeling, an intuitive three-dimensional view of the tunnel inner wall is generated. Finally, according to the three-dimensional view of tunnel disease detection, a tunnel disease detection result is generated, realizing the full-process automation from image acquisition to disease recognition. This not only improves the detection efficiency and accuracy but also provides a detailed and reliable detection report for tunnel maintenance and repair, significantly enhancing the overall technical level of tunnel disease detection.

[0108] Exemplarily, as Figure 3 shown, Figure 3 FIG. is a schematic structural diagram of a detection component provided for the second embodiment of the tunnel disease detection array control method of the present application. Each detection component may include a camera, a binocular camera, a fill light, a ground penetrating radar, a rotating motor, a plurality of ranging sensors, and other fixed structures.

[0109] As Figure 4 shown, Figure 4 FIG. is a schematic structural diagram of a detection array provided for the second embodiment of the tunnel disease detection array control method of the present application. The detection array is connected to the robotic arm of the tunnel detection platform through an electric push rod. The detection array includes three detection components and two electric push rods. The three detection components are connected by a hinged manner. When the electric push rod connecting the detection array to the robotic arm is driven, it will drive the entire detection array to move in the vertical direction of the robotic arm, thereby changing the detection positions of all detection components. When the electric push rod in the detection array is driven, it will drive the detection components on both sides to move in the horizontal direction of the robotic arm, thereby changing the detection positions of individual detection components. When a rotating motor is provided in the detection component, the angle change of the detection component can be driven by controlling the rotating motor.

[0110] As Figure 5 shown, Figure 5 FIG. is another schematic structural diagram of a detection array provided for the second embodiment of the tunnel disease detection array control method of the present application. The detection array is connected to the robotic arm of the tunnel detection platform through an electric push rod. The detection array includes three detection components and three electric push rods. When the electric push rod connecting the detection array to the robotic arm is driven, it will drive the entire detection array to move in the vertical direction of the robotic arm, thereby changing the detection positions of all detection components. When the electric push rod in the detection array is driven, it will drive the detection components on both sides to move in the horizontal direction of the robotic arm, thereby changing the detection positions of individual detection components. When a rotating motor is provided in the detection component, the angle change of the individual detection component can be driven by controlling the rotating motor.

[0111] When the position and angle of the detection component change, sensors such as cameras and radars in the detection component will also change the detection direction accordingly. At the same time, when each detection component changes in position and angle, multiple ranging sensors therein will real-time feedback the distance between the current detection component and the tunnel inner wall, so as to real-time adjust the angle of the detection component to keep the detection component facing the corresponding detection area of the tunnel inner wall directly for detection, obtain high-quality disease detection data, and thus improve the efficiency of tunnel disease detection.

[0112] In this embodiment, the position and angle of the detection sensor are adjusted by combining the ranging sensor, the electric push rod and the rotating motor. The detection sensor can accurately locate and cover the key areas of the tunnel inner wall at the best angle, which not only improves the accuracy and comprehensiveness of the detection, but also adapts to the dynamic changes of the tunnel through the real-time feedback and dynamic adjustment mechanism, reduces the detection error, and realizes the efficient and accurate tunnel disease detection.

[0113] It should be noted that the above examples are only for understanding the present application and do not constitute a limitation on the tunnel disease detection array control method of the present application. Based on this technical concept, more forms of simple transformation are within the protection scope of the present application.

[0114] The present application also provides a tunnel disease detection array control device. Please refer to Figure 6 The tunnel disease detection array control device is configured with a detection array, and the detection array includes several detection sensors, including:

[0115] A parameter acquisition module 10, which is used to acquire the tunnel parameters of the tunnel to be detected;

[0116] A position determination module 20, which is used to determine the target detection positions and target detection angles of the several detection sensors according to the tunnel parameters;

[0117] An adjustment detection module 30, which is used to adjust the positions and angles of the several detection sensors based on the target detection positions and target detection angles, and perform disease detection on the tunnel to be detected through the adjusted several detection sensors to obtain a tunnel disease detection result.

[0118] Optionally, the position determination module 20 is further used for:

[0119] Determine the target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array;

[0120] Based on the target detection axis, determine the target detection positions and target detection angles of the several detection sensors.

[0121] Optionally, the position determination module 20 is further used for:

[0122] Based on the tunnel parameters, construct a cross-sectional plane coordinate system for the tunnel to be detected;

[0123] According to the structural parameters of the detection array, obtain the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system;

[0124] According to the target detection position coordinates, determine the target detection axis of the detection array.

[0125] Optionally, the position determination module 20 is further configured to:

[0126] According to the structural parameters of the detection array, obtain the field of view angles and spacing ranges of the several detection sensors;

[0127] Based on the target detection axis, calculate according to the field of view angles and spacing ranges to obtain the target detection positions and target detection angles of the several detection sensors.

[0128] Optionally, the detection array further includes several distance measurement sensors, several electric push rods, and several rotating motors. The several detection sensors are connected by the electric push rods and / or the rotating motors. The adjustment and detection module 30 is further configured to:

[0129] Adjust the positions of the several detection sensors to the target detection positions through the several distance measurement sensors and several electric push rods;

[0130] Adjust the angles of the several detection sensors to the target detection angles through the several rotating motors.

[0131] Optionally, the adjustment and detection module 30 is further configured to:

[0132] Perform disease detection on the inner wall of the tunnel to be detected through the adjusted several detection sensors to obtain several disease detection images;

[0133] Based on the target detection positions and target detection angles, perform image stitching on the several disease detection images to obtain a three-dimensional view of tunnel disease detection;

[0134] According to the three-dimensional view of tunnel disease detection, obtain the tunnel disease detection result.

[0135] The tunnel disease detection array control device provided by the present application adopts the tunnel disease detection array control method in the above embodiment, and can solve the technical problem of low detection efficiency of the existing tunnel disease detection method. Compared with the prior art, the beneficial effects of the tunnel disease detection array control device provided by the present application are the same as those of the tunnel disease detection array control method provided by the above embodiment, and other technical features in the tunnel disease detection array control device are the same as the features disclosed in the method of the above embodiment, which will not be elaborated here.

[0136] The present application provides a tunnel disease detection array control device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the tunnel disease detection array control method in the above first embodiment.

[0137] Reference is made below to Figure 7 , which shows a schematic structural diagram of a tunnel disease detection array control device suitable for implementing the embodiments of the present application. The tunnel disease detection array control device in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The tunnel disease detection array control device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present application.

[0138] As Figure 7As shown, the tunnel disease detection array control device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 into the random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the tunnel disease detection array control device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the tunnel disease detection array control device to communicate with other devices wirelessly or wiredly to exchange data. Although the tunnel disease detection array control device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be implemented or had alternatively.

[0139] Particularly, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart may be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiments disclosed in the present application are executed.

[0140] The tunnel disease detection array control device provided by the present application adopts the tunnel disease detection array control method in the above embodiment, and can solve the technical problem of low detection efficiency of the existing tunnel disease detection method. Compared with the prior art, the beneficial effects of the tunnel disease detection array control device provided by the present application are the same as those of the tunnel disease detection array control method provided by the above embodiment, and other technical features in the tunnel disease detection array control device are the same as those disclosed in the method of the previous embodiment, and will not be elaborated here.

[0141] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0142] As described above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all of them should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0143] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the tunnel disease detection array control method in the above embodiments.

[0144] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems, or devices, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM: Random Access Memory), read-only memory (ROM: Read Only Memory), erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0145] The above computer-readable storage medium can be included in the tunnel disease detection array control device; or it can exist separately without being assembled into the tunnel disease detection array control device.

[0146] The above computer-readable storage medium carries one or more programs, which, when executed by the tunnel disease detection array control device, cause the tunnel disease detection array control device to: obtain the tunnel parameters of the tunnel to be detected; determine the target detection positions and target detection angles of a plurality of detection sensors according to the tunnel parameters; based on the target detection positions and target detection angles, adjust the positions and angles of the plurality of detection sensors, and perform disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

[0147] Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by connecting through an Internet service provider using the Internet).

[0148] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0149] The modules involved in the embodiments of the present application may be implemented in software or in hardware. Wherein, the name of the module does not constitute a limitation on the unit itself in some cases.

[0150] The readable storage medium provided by this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned tunnel disease detection array control method, and can solve the technical problem of low detection efficiency of existing tunnel disease detection methods. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as those of the tunnel disease detection array control method provided by the above embodiment, and will not be elaborated here.

[0151] This application also provides a computer program product, including a computer program, and the steps of the above-mentioned tunnel disease detection array control method are realized when the computer program is executed by a processor.

[0152] The computer program product provided by this application can solve the technical problem of low detection efficiency of existing tunnel disease detection methods. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as those of the tunnel disease detection array control method provided by the above embodiment, and will not be elaborated here.

[0153] The above are only partial embodiments of this application, and do not limit the patent scope of this application accordingly. Any equivalent structural transformation made under the technical concept of this application by using the content of the specification and drawings of this application, or any direct / indirect application in other related technical fields, is included in the patent protection scope of this application.

Claims

1. A method for controlling a tunnel disease detection array, characterized in that The method is applied to a tunnel detection platform, which is configured with a detection array. The detection array includes a number of detection sensors, including: Obtain tunnel parameters of the tunnel to be detected; where the tunnel parameters are data related to the tunnel structure and environment, including geometric parameters and environmental parameters. The geometric parameters include the central axis, radius, inner wall radian, length, and cross-sectional shape of the tunnel, and the environmental parameters include the illumination level of the tunnel; Based on the tunnel parameters, determine the target detection positions and target detection angles of the number of detection sensors; the target detection position is the optimal layout position of the detection sensor on the inner wall of the tunnel; the target detection angle is the optimal detection angle of different detection sensors relative to the inner wall of the tunnel; specifically including: Based on the tunnel parameters and the structural parameters of the detection array, determine the target detection axis of the detection array; specifically including: based on the tunnel parameters, construct a cross-sectional plane coordinate system of the tunnel to be detected; according to the structural parameters of the detection array, obtain the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system; according to the target detection position coordinates, determine the target detection axis of the detection array; where the structural parameters of the detection array include physical characteristics and layout methods. The physical characteristics include the number of sensors, spacing, coverage range, and field of view angle, and the layout methods include linear arrangement, circular arrangement, or grid arrangement. The target detection position coordinates are the nearest detection position coordinates of the detection array in the cross-sectional plane coordinate system, corresponding to the core position in the detection array; Based on the target detection axis, determine the target detection positions and target detection angles of the number of detection sensors; specifically including: according to the structural parameters of the detection array, obtain the field of view angles and spacing ranges of the number of detection sensors; where the spacing range is the distance range between detection sensors; based on the target detection axis, according to the field of view angles and spacing ranges, calculate the target detection positions and target detection angles of the number of detection sensors through mathematical modeling and optimization algorithms; Based on the target detection positions and target detection angles, adjust the positions and angles of the number of detection sensors, and perform disease detection on the tunnel to be detected by the adjusted number of detection sensors to obtain a tunnel disease detection result; the step of performing disease detection on the tunnel to be detected by the adjusted number of detection sensors to obtain a tunnel disease detection result includes: performing disease detection on the inner wall of the tunnel to be detected by the adjusted number of detection sensors to obtain a number of disease detection images; based on the target detection positions and target detection angles, perform image stitching on the number of disease detection images to obtain a three-dimensional view of the tunnel disease detection; according to the three-dimensional view of the tunnel disease detection, obtain the tunnel disease detection result.

2. The method according to claim 1, wherein The detection array further includes a number of distance measurement sensors, a number of electric push rods, and a number of rotating motors. The number of detection sensors are connected by the electric push rods and / or the rotating motors, The step of adjusting the positions and angles of the plurality of detection sensors based on the target detection position and the target detection angle includes: Adjusting the positions of the plurality of detection sensors to the target detection position through the plurality of distance measurement sensors and the plurality of electric push rods; Adjusting the angles of the plurality of detection sensors to the target detection angle through the plurality of rotation motors.

3. A tunnel disease detection array control device, characterized in that, The device is configured with a detection array, and the detection array includes a plurality of detection sensors, including: A parameter acquisition module for acquiring tunnel parameters of a tunnel to be detected; wherein, the tunnel parameters are data related to the tunnel structure and environment, including geometric parameters and environmental parameters, the geometric parameters include the central axis, radius, inner wall radian, length, cross-sectional shape of the tunnel, and the environmental parameters include the illumination level of the tunnel; A position determination module for determining the target detection position and the target detection angle of the plurality of detection sensors according to the tunnel parameters; the target detection position is the optimal layout position of the detection sensor on the inner wall of the tunnel; the target detection angle is the optimal detection angle of different detection sensors relative to the inner wall of the tunnel; Wherein, the position determination module is further configured to: Determine the target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array; specifically including: constructing a cross-sectional plane coordinate system of the tunnel to be detected based on the tunnel parameters; obtaining the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system according to the structural parameters of the detection array; determining the target detection axis of the detection array according to the target detection position coordinates; wherein, the structural parameters of the detection array include physical characteristics and layout modes, the physical characteristics include the number of sensors, spacing, coverage range and field of view angle, the layout modes include linear arrangement, circular arrangement or grid arrangement, and the target detection position coordinates are the closest detection position coordinates of the detection array in the cross-sectional plane coordinate system, corresponding to the core position in the detection array; Determining the target detection position and the target detection angle of the plurality of detection sensors based on the target detection axis; Wherein, the position determination module is further configured to: Obtain the field of view angle and the spacing range of the plurality of detection sensors according to the structural parameters of the detection array; wherein, the spacing range is the distance range between the detection sensors; Based on the target detection axis, calculating the target detection position and the target detection angle of the plurality of detection sensors through mathematical modeling and optimization algorithms according to the field of view angle and the spacing range; An adjustment detection module, configured to adjust the positions and angles of the plurality of detection sensors based on the target detection position and the target detection angle, and perform disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain a tunnel disease detection result; the performing disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain a tunnel disease detection result includes: performing disease detection on the inner wall of the tunnel to be detected through the adjusted plurality of detection sensors to obtain a plurality of disease detection images; performing image stitching on the plurality of disease detection images based on the target detection position and the target detection angle to obtain a three-dimensional view of tunnel disease detection; and obtaining a tunnel disease detection result according to the three-dimensional view of tunnel disease detection.

4. A tunnel disease detection array control device, characterized in that The device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the computer program is configured to implement the steps of the tunnel disease detection array control method according to any one of claims 1 to 2.

5. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium, where the computer program, when executed by a processor, implements the steps of the tunnel disease detection array control method according to any one of claims 1 to 2.

6. A computer program product, characterized in that, The computer program product includes a computer program, where the computer program, when executed by a processor, implements the steps of the tunnel disease detection array control method according to any one of claims 1 to 2.

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