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

Abstract

The invention discloses a tunnel disease detection array control method and device, equipment, a medium and a product, and relates to the technical field of engineering detection.The tunnel disease detection array control method comprises the steps that tunnel parameters of a to-be-detected tunnel are obtained; determining target detection positions and target detection angles of a plurality of detection sensors according to the tunnel parameters; and based on the target detection position and the target detection angle, adjusting the positions and angles of the plurality of detection sensors, and performing disease detection on the to-be-detected tunnel through the plurality of adjusted detection sensors to obtain a tunnel disease detection result. According to the invention, tunnel disease detection based on dynamic position angle adjustment of the detection sensor is realized, the problem of low detection efficiency of an existing tunnel disease detection method is solved, and the detection efficiency and accuracy of tunnel disease detection are improved.

Description

Technical Field

[0001] The present application relates to the field of engineering detection technology, and in particular to a tunnel disease detection array control method, device, equipment, medium and product. Background Art

[0002] Due to the influence of tunnel terrain, geology, climatic conditions, and various factors during the design and construction process, the tunnel will have varying degrees of defects during the construction process and even during the use after completion. Camera arrays will be used to detect the existing defects in the tunnel.

[0003] However, this tunnel disease detection method requires that images captured by different cameras be stitched together into a complete tunnel cross-sectional image. Due to the structural complexity of the tunnel inner wall, the quality of images captured by different cameras is usually not stable, and it is difficult to achieve rapid stitching to meet the real-time requirements of tunnel disease detection, resulting in low efficiency of tunnel disease detection.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

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

[0006] To achieve the above-mentioned purpose, the present application proposes a tunnel disease detection array control method, which is applied to a tunnel detection platform, wherein the tunnel detection platform is equipped with a detection array, and the detection array includes a plurality of detection sensors, including: Obtain tunnel parameters of the tunnel to be detected; Determining target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters; Based on the target detection position and the target detection angle, the positions and angles of the plurality of detection sensors are adjusted, and the tunnel to be detected is subjected to disease detection through the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

[0007] In one embodiment, the step of determining the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters comprises: Determining a target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array; Based on the target detection axis, target detection positions and target detection angles of the plurality of detection sensors are determined.

[0008] In one 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: Based on the tunnel parameters, constructing a cross-sectional plane coordinate system of the tunnel to be inspected; According to the structural parameters of the detection array, obtaining the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system; The target detection axis of the detection array is determined according to the target detection position coordinates.

[0009] 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 includes: According to the structural parameters of the detection array, obtaining the field of view angles and spacing ranges of the plurality of detection sensors; Based on the target detection axis, calculation is performed according to the field of view angle and the spacing range to obtain the target detection positions and target detection angles of the plurality of detection sensors.

[0010] In one embodiment, the detection array further includes a plurality of distance measuring sensors, a plurality of electric push rods and a plurality of rotating motors, and the plurality of detection sensors are connected through 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 comprises: Adjusting the positions of the plurality of detection sensors to the target detection positions by means of the plurality of distance measuring sensors and the plurality of electric push rods; The angles of the plurality of detection sensors are adjusted to the target detection angle by the plurality of rotating motors.

[0011] In one embodiment, the step of performing disease detection on the tunnel to be detected by using the adjusted plurality of detection sensors to obtain tunnel disease detection results includes: Performing disease detection on the inner wall of the tunnel to be detected by using the adjusted detection sensors to obtain a plurality of disease detection images; Based on the target detection position and the target detection angle, the plurality of defect detection images are stitched together to obtain a three-dimensional view of tunnel defect detection; A tunnel disease detection result is obtained according to the tunnel disease detection three-dimensional view.

[0012] In addition, to achieve the above-mentioned purpose, the present application also proposes a tunnel disease detection array control device, wherein the tunnel disease detection array control device is configured with a detection array, and the detection array includes a plurality of detection sensors, including: A parameter acquisition module, used to acquire tunnel parameters of the tunnel to be detected; A position determination module, used to determine the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters; The detection adjustment module is used 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 tunnel disease detection results.

[0013] In addition, to achieve the above-mentioned purpose, the present application also proposes a tunnel disease detection array control device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the tunnel disease detection array control method described above.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the tunnel disease detection array control method described above are implemented.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the tunnel disease detection array control method as described above are implemented.

[0016] The present application provides a tunnel disease detection array control method, which first obtains the detailed parameters of the tunnel that needs disease detection, and provides basic data for the layout and adjustment of the subsequent detection sensors; then, the optimal position and angle of the detection sensor are determined based on the tunnel parameters, 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 position and angle of the detection sensor, it is ensured that the sensor can accurately cover the key areas of the inner wall of the tunnel, and the real-time feedback and dynamic adjustment of the sensor are used to further improve the efficiency and accuracy of the detection. The tunnel disease detection based on the dynamic position and angle adjustment of the detection sensor is realized, which 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

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

[0019] Figure 1 A schematic diagram of a flow chart provided for the first embodiment of the tunnel disease detection array control method of the present application; Figure 2 A schematic diagram of a flow chart provided for the second embodiment of the tunnel disease detection array control method of the present application; Figure 3 A schematic diagram of the structure of a detection component provided in the second embodiment of the tunnel disease detection array control method of the present application; Figure 4 A schematic diagram of a detection array structure provided for the second embodiment of the tunnel disease detection array control method of the present application; Figure 5 A schematic diagram of another detection array structure provided for the second embodiment of the tunnel disease detection array control method of the present application; Figure 6 This is a schematic diagram of the module structure of the tunnel disease detection array control device according to an embodiment of the present application; Figure 7 Schematic diagram of the device structure of the hardware operating environment involved in the tunnel disease detection array control method in the embodiment of the present application.

[0020] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0022] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0023] The main solution of the embodiment of the present application is: obtaining tunnel parameters of the tunnel to be inspected; determining the target detection position and target detection angle of several detection sensors according to the tunnel parameters; adjusting the positions and angles of the several detection sensors based on the target detection position and target detection angle, and performing disease detection on the tunnel to be inspected through the adjusted several detection sensors to obtain tunnel disease detection results.

[0024] The tunnel disease detection method of the prior art uses a camera array to collect image data of the inner wall of the tunnel, and merges the image data collected by different cameras into a complete tunnel inner wall image by image stitching. Usually, the position and angle of the camera array are relatively fixed and need to be adjusted manually. However, due to the structural complexity of the inner wall of the tunnel, the camera angle needs to be adjusted multiple times during the whole tunnel inspection to adapt to the changes in the tunnel environment. In addition, the image quality collected by different cameras is different, and the boundaries of different camera viewing angles cannot be accurately adjusted manually. The images of different cameras have different smoothness and continuity, making it difficult to achieve fast image stitching and present them to on-site inspection personnel in real time, resulting in low efficiency of tunnel disease detection.

[0025] This application first obtains the detailed parameters of the tunnel that needs to be inspected for defects, providing basic data for the layout and adjustment of subsequent detection sensors; then, the optimal position and angle of the detection sensor is determined based on the tunnel parameters, 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 position and angle of the detection sensor, it is ensured that the sensor can accurately cover the key areas of the inner wall of the tunnel, and the real-time feedback and dynamic adjustment of the sensor are used to further improve the efficiency and accuracy of the detection. Tunnel defect detection based on dynamic position and angle adjustment of the detection sensor is realized, which solves the problem of low detection efficiency of existing tunnel defect detection methods and improves the detection efficiency and accuracy of tunnel defect detection.

[0026] It should be noted that the execution subject of this embodiment may 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 capable of realizing the above functions, a tunnel disease detection array control device, etc. The following takes the tunnel disease detection array control device as an example to illustrate this embodiment and the following embodiments.

[0027] Based on this, the embodiment of the present application provides a tunnel disease detection array control method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the tunnel disease detection array control method of the present application.

[0028] In this embodiment, the tunnel disease detection array control method is applied to a tunnel detection platform, and the tunnel detection platform is equipped with a detection array, and the detection array includes a plurality of detection sensors, including steps S10 to S30: Step S10, obtaining tunnel parameters of the tunnel to be detected; It should be noted that the detection array is an array composed of multiple detection sensors, which are used to collect data on the inner wall of the tunnel. Usually, the detection sensors in the detection array will face different angles to collect data. The detection sensor is a device used to collect data on the inner wall of the tunnel, such as a camera, radar, ranging sensor, etc., which can obtain the distance of the inner wall of the tunnel and the tunnel detection data.

[0029] In addition, it should be noted that tunnel parameters refer to data related to the tunnel structure and environment, including geometric parameters (such as the tunnel's central axis, radius, inner wall curvature, length, cross-sectional shape, etc.) and environmental parameters (such as the tunnel's lighting level, etc.), which can be collected through instruments such as laser scanners and environmental sensors.

[0030] It is understandable that in order to provide detailed information about the tunnel, provide basic data for the layout and adjustment of subsequent detection sensors, obtain the tunnel parameters required for tunnel disease detection, and ensure that the detection sensors can be accurately configured according to the actual shape and environment of the tunnel.

[0031] Step S20, determining target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters; 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 area 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 avoid detection blind spots.

[0032] It is understandable that in order to ensure that the detection sensors can cover all areas of the tunnel inner wall that need to be inspected and can obtain image data with image quality that meets the requirements of real-time image stitching, the optimal detection position and detection angle of all detection sensors inside the tunnel are determined based on the tunnel parameters and the structural parameters of the detection array (such as sensor spacing and coverage range), so as to optimize the layout of the detection sensors, improve the detection efficiency and data quality, and provide accurate sensor configuration for subsequent disease detection.

[0033] Step S30, based on the target detection position and the target detection angle, the positions and angles of the plurality of detection sensors are adjusted, and the tunnel to be detected is subjected to disease detection by the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

[0034] It should be noted that the tunnel disease detection results refer to the results obtained after the tunnel disease detection, which can be presented in visual and textual form, and may include images of the tunnel inner wall, a three-dimensional model of the inner wall and existing diseases (such as the location, type and severity of the disease).

[0035] It is understandable that in order to achieve precise positioning and angle adjustment of sensors and ensure the accuracy and real-time nature of the detection results, the position and angle of these detection sensors are dynamically adjusted in combination with the feedback information of the sensors. The dynamically adjusted detection sensors are used to collect the apparent disease characteristic data and hidden disease characteristic data of the inner wall of the tunnel, and the diseases are identified through data processing and analysis technology, thus realizing automated and efficient tunnel disease detection. At the same time, detailed disease detection results are generated to provide a basis for tunnel maintenance.

[0036] In a feasible implementation manner, the step of determining the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters includes: Step S201, determining the target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array; It should be noted that the target detection axis is the basis of the detection array layout, which is used to ensure that the detection sensors in the detection array can accurately and completely cover the key areas of the tunnel inner wall that require disease detection.

[0037] It is understandable 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, curvature, cross-sectional shape) and the structural parameters of the detection array (such as sensor spacing, coverage range), the optimal axis position of the detection array can be determined and used as a reference point for the detection sensor, thereby improving detection efficiency and data quality and reducing detection blind spots.

[0038] Step S202: determining the target detection positions and target detection angles of the plurality of detection sensors based on the target detection axis.

[0039] It is understandable that in order to ensure that the detection sensors can adapt to the geometry and deformation of the tunnel and achieve efficient and accurate detection, the layout of the detection sensors is further optimized based on the target detection axis, and the optimal detection positions and angles of different detection sensors when collecting data are determined. By dynamically adjusting the position and angle of the sensors, the detection data collection errors caused by tunnel deformation are reduced.

[0040] In this implementation, first, the target detection axis of the detection array is determined based on the tunnel parameters and the structural parameters of the detection array, which can quickly determine the axis of the detection array and provide a basis for the layout of the detection sensor; based on the detection axis and tunnel parameters, the target detection position and angle of the sensor are optimized to ensure that it can adapt to the geometry and deformation of the tunnel, which not only improves the layout accuracy of the detection sensor, but also improves the detection efficiency and data quality through a dynamic adjustment mechanism.

[0041] In a feasible implementation manner, 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: Step S2011, constructing a cross-sectional plane coordinate system of the tunnel to be inspected based on the tunnel parameters; It should be noted that in the actual tunnel defect detection process, the equally spaced cross sections in the tunnel are usually used as the units of tunnel defect detection, and the defect detection of the entire tunnel will collect the detection data of all cross sections along the direction of the tunnel extension. 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 center of the tunnel can be used as the origin of the coordinate system.

[0042] It can be understood that in order to provide a clear geometric reference frame 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 tunnel parameters can simplify the calculation process and improve the layout accuracy.

[0043] Step S2012, 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; 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, field of view, 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 connecting the detection array to the tunnel diagnostic platform.

[0044] It can be understood that in order to determine the nearest detection position and location of each sensor in the detection array within the cross section, so as to acquire a set of images with consistent smoothness and continuity of the inner wall of the tunnel, the target detection position coordinates of each sensor are calculated based on the structural parameters of the detection array and the cross-sectional plane coordinate system, ensuring that the detection sensors can cover the key areas of the inner wall of the tunnel, providing specific position information for the determination of the target detection axis, and optimizing the sensor layout.

[0045] Step S2013, determining the target detection axis of the detection array according to the target detection position coordinates.

[0046] It should be noted that the target detection axis will change according to the actual deformation of the tunnel and the detection requirements, that is, when the structural parameters corresponding to adjacent cross-sections of the tunnel change, the target detection axis will also change dynamically.

[0047] 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 geometry 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 the curve to guide the dynamic adjustment of the sensor and disease detection.

[0048] In this implementation, the plane coordinate system of the tunnel cross section is first constructed to provide a unified reference frame for the sensor layout. Then, the target detection position coordinates of each sensor are determined based on the structural parameters of the detection array, and the sensor layout is optimized to ensure that the sensor can cover the key areas of the tunnel inner wall and reduce the detection blind area; finally, the target detection axis of the detection array is determined based on the target detection position coordinates of each sensor to adapt to the complex geometry of the tunnel and improve the accuracy and reliability of detection data acquisition.

[0049] In a feasible implementation manner, 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: Step S2021, obtaining the field of view angles and spacing ranges of the plurality of detection sensors according to the structural parameters of the detection array; It should be noted that the field of view refers to the angle of the spatial range 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 position between the detection sensors and the layout density of the detection array, and affects the accuracy of the detection data collection.

[0050] It can be understood that in order to provide necessary parameter support for the subsequent calculation of the target detection position and angle of the sensor, ensure the rationality of the sensor layout and the comprehensiveness of the detection, obtain the field of view angle and spacing range of each detection sensor according to the structural parameters of the detection array, so as to optimize the overall field of view angle and spacing range of the detection array, determine the optimal position and detection direction of each detection sensor, and ensure that the coverage areas between different detection sensors can be seamlessly connected.

[0051] Step S2022, based on the target detection axis, calculation is performed according to the field of view angle and the spacing range to obtain the target detection positions and target detection angles of the plurality of detection sensors.

[0052] It is understandable that in order to ensure that the sensor can accurately cover the key areas of the tunnel wall and adapt to the changes in the geometry of the tunnel and different cross-sections, based on the target detection axis, combined with the field of view angle and spacing range of the detection sensor, the optimal target detection position and angle of each detection sensor are calculated through mathematical modeling and optimization algorithms.

[0053] In this embodiment, the target detection axis is used as a reference, combined with the field of view and spacing range of the sensor, to calculate the target detection position and angle of each sensor as the parameters for adjusting the detection array spacing and sensor angle. Through the dynamic adjustment mechanism, it is possible to adapt to the dynamic changes of the tunnel, reduce detection errors, and improve the comprehensiveness and accuracy of detection.

[0054] This embodiment provides a tunnel disease detection array control method, which 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, the optimal position and angle of the detection sensor are determined based on the tunnel parameters, 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 position and angle of the detection sensor, it is ensured that the sensor can accurately cover the key areas of the inner wall of the tunnel, and the real-time feedback and dynamic adjustment of the sensor are used to further improve the efficiency and accuracy of the detection. Tunnel disease detection based on dynamic position and angle adjustment of the detection sensor is realized, which 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.

[0055] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can refer to the above introduction, and will not be repeated in the following. Figure 2 , Figure 2 This is a flow chart of the second embodiment of the tunnel disease detection array control method of the present application.

[0056] In this embodiment, the detection array further includes a plurality of distance measuring sensors, a plurality of electric push rods and a plurality of rotating motors. The plurality of detection sensors are connected through 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 comprises: Step S3011, adjusting the positions of the plurality of detection sensors to the target detection positions by using the plurality of distance measuring sensors and the plurality of electric push rods; 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 drive device used to adjust the position of the detection sensor, which can push or pull the sensor to the target position according to the feedback of the distance sensor.

[0057] It can be understood that in order to ensure that the detection sensor can accurately locate the target detection position, the distance between the detection sensor and the inner wall of the tunnel is measured in real time using a ranging sensor, and the position of each detection sensor is adjusted by an electric push rod to reach the target detection position, thereby ensuring that the distance between different sensors and the inner wall of the tunnel is consistent, so that the smoothness and continuity of the collected detection data can meet the real-time requirements of the detection.

[0058] For example, a PID (Proportion Integration Differentiation) controller or other closed-loop control algorithms can be used to combine feedback from multiple distance measuring sensors to optimize the adjustment strategy of the electric push rod, dynamically adjust the extension and retraction of the electric push rod, and ensure that the sensor position is distributed as the shape of the inner wall of the tunnel changes.

[0059] Step S3012: adjusting the angles of the plurality of detection sensors to the target detection angles by using the plurality of rotating motors.

[0060] It is understandable that in order to ensure that the detection sensor can cover the inner wall of the tunnel at the best angle and improve the comprehensiveness and accuracy of the detection, the angle of the detection sensor is adjusted by the rotary motor to achieve the target detection angle. The adjustment of the rotary motor can be determined by combining the target detection angle of the sensor and real-time feedback.

[0061] In a feasible implementation manner, the step of performing disease detection on the tunnel to be detected by using the adjusted plurality of detection sensors to obtain tunnel disease detection results includes: Step S3021, performing defect detection on the inner wall of the tunnel to be detected by using the adjusted detection sensors to obtain a plurality of defect detection images; It is understandable that in order to understand the disease condition of the inner wall of the tunnel, the inner wall of the tunnel is inspected for diseases using adjusted detection sensors (such as cameras, radars, etc.), and image data of the inner wall of the tunnel is collected for subsequent image stitching. Multiple detection sensors with adjusted positions and angles can accurately cover the inner wall of the tunnel, and can collect high-quality disease detection images for rapid image stitching.

[0062] Step S3022, based on the target detection position and the target detection angle, the plurality of defect detection images are stitched together to obtain a three-dimensional view of tunnel defect detection; It should be noted that, usually the defect detection image is a two-dimensional plane image. The target detection position and target detection angle can provide a geometric reference for the image stitching of the three-dimensional view. By extracting the feature points (such as corner points and edges) in the image and stitching multiple images together through a matching algorithm, the stitched image data can be converted into a three-dimensional model, and the defect distribution of the tunnel inner wall can be displayed through visualization means.

[0063] It can be understood that in order to provide intuitive visualization support for defect detection, multiple defect detection images are spliced ​​using target detection position and angle information to generate a three-dimensional view of tunnel defect detection on the inner wall of the tunnel. Through the three-dimensional view, the distribution of defects on the inner wall of the tunnel can be more intuitively displayed, which is convenient for subsequent analysis and repair.

[0064] Step S3023, obtaining a tunnel disease detection result according to the tunnel disease detection three-dimensional view.

[0065] It can be understood that based on the three-dimensional view of tunnel disease detection, image recognition technology can be used to identify the defective parts (such as cracks, leakage, peeling, etc.), mark the defect locations in the three-dimensional view, generate a disease detection report, realize visual disease detection and early warning, and provide support for tunnel on-site inspection personnel.

[0066] In this implementation, first, high-quality disease detection images are acquired using multiple adjusted detection sensors; then, based on the target detection position and angle, multiple disease detection images are spliced ​​to generate a tunnel disease detection three-dimensional view, and an intuitive three-dimensional view of the tunnel inner wall is generated through image stitching and three-dimensional modeling; finally, based on the tunnel disease detection three-dimensional view, the tunnel disease detection result is generated, realizing the automation of the entire process from image acquisition to disease identification, which not only improves the detection efficiency and accuracy, but also provides detailed and reliable detection reports for tunnel maintenance and repair, significantly improving the overall technical level of tunnel disease detection.

[0067] For example, Figure 3 As shown, Figure 3 A schematic diagram of the detection component structure 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, multiple ranging sensors and other fixed structures.

[0068] like Figure 4 As shown, Figure 4A schematic diagram of a detection array structure provided for the second embodiment of the tunnel disease detection array control method of the present application. The detection array is connected to the mechanical 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 hinges. When the electric push rod connecting the detection array to the mechanical arm is driven, it will drive the detection array as a whole to move in the vertical direction of the mechanical arm, thereby changing the detection position 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 mechanical arm, thereby changing the detection position of a single detection component. 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.

[0069] like Figure 5 As shown, Figure 5 Another schematic diagram of the detection array structure provided for the second embodiment of the tunnel disease detection array control method of the present application. The detection array is connected to the mechanical arm of the tunnel detection platform through an electric push rod, and the detection array includes three detection components and three electric push rods. When the electric push rod connecting the detection array to the mechanical arm is driven, it will drive the detection array as a whole to move in the vertical direction of the mechanical arm, thereby changing the detection position of all detection components, and 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 mechanical arm, thereby changing the detection position of a single detection component. When a rotating motor is provided in the detection component, the angle change of the single detection component can be driven by controlling the rotating motor.

[0070] When the position and angle of the detection component change, the camera, radar and other sensors in the detection component will also change the detection direction accordingly. At the same time, when the position and angle of each detection component change, multiple ranging sensors will provide real-time feedback on the distance between the current detection component and the inner wall of the tunnel, thereby adjusting the angle of the detection component in real time to keep the detection component facing the corresponding detection area on the inner wall of the tunnel for detection, thereby obtaining high-quality disease detection data and improving the efficiency of tunnel disease detection.

[0071] In this embodiment, the position and angle of the detection sensor are adjusted by combining the distance measuring sensor, the electric push rod and the rotating motor. The detection sensor can accurately locate and cover the key area of ​​the inner wall of the tunnel at the optimal angle, which not only improves the accuracy and comprehensiveness of the detection, but also adapts to the dynamic changes of the tunnel through real-time feedback and dynamic adjustment mechanism, reduces detection errors, and realizes efficient and accurate tunnel disease detection.

[0072] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the tunnel disease detection array control method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0073] This application also provides a tunnel disease detection array control device, please refer to Figure 6 The tunnel disease detection array control device is equipped with a detection array, and the detection array includes a plurality of detection sensors, including: A parameter acquisition module 10, used to acquire tunnel parameters of the tunnel to be detected; A position determination module 20, for determining target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters; The detection adjustment module 30 is used 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 tunnel disease detection results.

[0074] Optionally, the location determination module 20 is further configured to: Determining a target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array; Based on the target detection axis, target detection positions and target detection angles of the plurality of detection sensors are determined.

[0075] Optionally, the location determination module 20 is further configured to: Based on the tunnel parameters, constructing a cross-sectional plane coordinate system of the tunnel to be inspected; According to the structural parameters of the detection array, obtaining the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system; The target detection axis of the detection array is determined according to the target detection position coordinates.

[0076] Optionally, the location determination module 20 is further configured to: According to the structural parameters of the detection array, obtaining the field of view angles and spacing ranges of the plurality of detection sensors; Based on the target detection axis, calculation is performed according to the field of view angle and the spacing range to obtain the target detection positions and target detection angles of the plurality of detection sensors.

[0077] Optionally, the detection array further includes a plurality of distance measuring sensors, a plurality of electric push rods and a plurality of rotating motors, the plurality of detection sensors are connected through the electric push rods and / or the rotating motors, and the adjustment detection module 30 is further used for: Adjusting the positions of the plurality of detection sensors to the target detection positions by means of the plurality of distance measuring sensors and the plurality of electric push rods; The angles of the plurality of detection sensors are adjusted to the target detection angle by the plurality of rotating motors.

[0078] Optionally, the adjustment detection module 30 is further used for: Performing disease detection on the inner wall of the tunnel to be detected by using the adjusted detection sensors to obtain a plurality of disease detection images; Based on the target detection position and the target detection angle, the plurality of defect detection images are stitched together to obtain a three-dimensional view of tunnel defect detection; A tunnel disease detection result is obtained according to the tunnel disease detection three-dimensional view.

[0079] The tunnel disease detection array control device provided by the present application adopts the tunnel disease detection array control method in the above embodiment, which 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 the beneficial effects 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 above embodiment method, which will not be repeated here.

[0080] The present application provides a tunnel disease detection array control device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the tunnel disease detection array control method in the first embodiment described above.

[0081] Reference below Figure 7 , which shows a schematic diagram of the structure of a tunnel disease detection array control device suitable for implementing the embodiment of the present application. The tunnel disease detection array control device in the embodiment 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), vehicle-mounted terminals (such as vehicle-mounted 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 bring any limitation to the functions and scope of use of the embodiments of the present application.

[0082] like 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 can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. Various programs and data required for the operation of the tunnel disease detection array control device are also stored in the RAM 1004. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 may allow the tunnel disease detection array control device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a tunnel disease detection array control device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0083] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can 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 includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0084] The tunnel disease detection array control device provided by the present application adopts the tunnel disease detection array control method in the above embodiment, which 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 the beneficial effects of the tunnel disease detection array control method provided by the above embodiment, and the other technical features in the tunnel disease detection array control device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0085] It should be understood that the various parts 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 any one or more embodiments or examples in a suitable manner.

[0086] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0087] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the tunnel disease detection array control method in the above-mentioned embodiment.

[0088] The computer-readable storage medium provided in the present application may 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 may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that 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 may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0089] The computer-readable storage medium may be included in the tunnel disease detection array control device; or may exist independently without being assembled into the tunnel disease detection array control device.

[0090] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the tunnel disease detection array control device, the tunnel disease detection array control device: obtains tunnel parameters of the tunnel to be detected; determines the target detection positions and target detection angles of a plurality of detection sensors according to the tunnel parameters; adjusts the positions and angles of the plurality of detection sensors based on the target detection positions and target detection angles, and performs disease detection on the tunnel to be detected through the adjusted plurality of detection sensors to obtain tunnel disease detection results.

[0091] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 (e.g., via the Internet using an Internet service provider).

[0092] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0093] The modules involved in the embodiments of the present application may be implemented by software or hardware, wherein the name of the module does not limit the unit itself in some cases.

[0094] The readable storage medium provided in the present application is a computer-readable storage medium, which 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 the existing tunnel disease detection method. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the tunnel disease detection array control method provided in the above-mentioned embodiment, and will not be repeated here.

[0095] The present application also provides a computer program product, including a computer program, which implements the steps of the tunnel disease detection array control method as described above when executed by a processor.

[0096] The computer program product provided by the present application 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 computer program product provided by the present application are the same as the beneficial effects of the tunnel disease detection array control method provided by the above embodiment, which will not be repeated here.

[0097] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A tunnel disease detection array control method, characterized in that: The method is applied to a tunnel detection platform, wherein the tunnel detection platform is equipped with a detection array, and the detection array includes a plurality of detection sensors, including: Obtain tunnel parameters of the tunnel to be detected; Determining target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters; Based on the target detection position and the target detection angle, the positions and angles of the plurality of detection sensors are adjusted, and the tunnel to be detected is subjected to disease detection through the adjusted plurality of detection sensors to obtain a tunnel disease detection result.

2. The method according to claim 1, characterized in that: The step of determining the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters comprises: Determining a target detection axis of the detection array according to the tunnel parameters and the structural parameters of the detection array; Based on the target detection axis, target detection positions and target detection angles of the plurality of detection sensors are determined.

3. The method according to claim 2, characterized in that: 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 comprises: Based on the tunnel parameters, constructing a cross-sectional plane coordinate system of the tunnel to be inspected; According to the structural parameters of the detection array, obtaining the target detection position coordinates of the detection array corresponding to the cross-sectional plane coordinate system; The target detection axis of the detection array is determined according to the target detection position coordinates.

4. The method according to claim 2, characterized in that: 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: According to the structural parameters of the detection array, obtaining the field of view angles and spacing ranges of the plurality of detection sensors; Based on the target detection axis, calculation is performed according to the field of view angle and the spacing range to obtain the target detection positions and target detection angles of the plurality of detection sensors.

5. The method according to claim 1, characterized in that: The detection array further includes a plurality of distance measuring sensors, a plurality of electric push rods and a plurality of rotating motors. The plurality of detection sensors are connected through 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 comprises: Adjusting the positions of the plurality of detection sensors to the target detection positions by means of the plurality of distance measuring sensors and the plurality of electric push rods; The angles of the plurality of detection sensors are adjusted to the target detection angle by the plurality of rotating motors.

6. The method according to claim 1, characterized in that: The step of performing disease detection on the tunnel to be detected by using the adjusted plurality of detection sensors to obtain tunnel disease detection results comprises: Performing disease detection on the inner wall of the tunnel to be detected by using the adjusted detection sensors to obtain a plurality of disease detection images; Based on the target detection position and the target detection angle, the plurality of defect detection images are stitched together to obtain a three-dimensional view of tunnel defect detection; A tunnel disease detection result is obtained according to the tunnel disease detection three-dimensional view.

7. A tunnel disease detection array control device, characterized in that: The device is equipped with a detection array, which includes a number of detection sensors, including: A parameter acquisition module, used to acquire tunnel parameters of the tunnel to be detected; A position determination module, used to determine the target detection positions and target detection angles of the plurality of detection sensors according to the tunnel parameters; The detection adjustment module is used 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 tunnel disease detection results.

8. A tunnel disease detection array control device, characterized in that: The device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein 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 6.

9. 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. When the computer program is executed by a processor, the steps of the tunnel disease detection array control method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the tunnel disease detection array control method according to any one of claims 1 to 6 are implemented.

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