Electromechanical pipeline consistency detection method, device, equipment, medium and product

Abstract

The invention discloses an electromechanical pipeline consistency detection method and device, equipment, a medium and a product, and relates to the technical field of image data processing, and the method comprises the steps: obtaining a key frame containing a target electromechanical pipeline; based on the pose data of the consistency detection device, performing image analysis on the key frame to obtain a target boundary endpoint coordinate of a target boundary of the target electromechanical pipeline; obtaining a standard boundary matched with the target boundary in a pre-stored standard electromechanical pipeline model; comparing the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates to obtain a coordinate comparison result; the correction module is used for correcting the visual positioning coordinates and the visual pose data acquired by the imaging correction module to obtain imaging positioning coordinates and imaging pose data; based on the imaging positioning coordinates, the imaging pose data and the standard electromechanical pipeline model, a comparison image of the coordinate comparison result is output through the development correction module, and the electromechanical pipeline consistency detection efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of image data processing, and particularly to a method, device, equipment, medium and product for consistency detection of mechanical and electrical pipelines. Background Art

[0002] During the installation and construction of mechanical and electrical pipelines, it is usually necessary to detect the installation effect. Currently, the method for detecting installed mechanical and electrical pipelines is usually that inspectors enter the site to collect image data such as pictures or videos containing mechanical and electrical pipelines. Since it is impossible to use a standard mechanical and electrical pipeline model to perform consistency detection on mechanical and electrical pipelines at the installation site, inspectors need to take the collected image data to a place where the mechanical and electrical pipelines in the image data can be subjected to consistency detection in order to achieve the consistency detection of mechanical and electrical pipelines. If the detection result finds that there are problems with the installation of mechanical and electrical pipelines, the inspectors need to return to the installation site again to adjust the mechanical and electrical pipelines and perform the above-mentioned operation process of consistency detection again.

[0003] It can be seen that by using the above method to perform consistency detection on installed mechanical and electrical pipelines, it is necessary to consume a large amount of manpower and material resources, resulting in low efficiency of consistency detection of mechanical and electrical pipelines. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, equipment, medium and product for consistency detection of mechanical and electrical pipelines, which can improve the efficiency of consistency detection of mechanical and electrical pipelines.

[0005] To achieve the above purpose, this application provides the following solutions: In the first aspect, this application provides a method for consistency detection of mechanical and electrical pipelines. The method is applied to a consistency detection device for mechanical and electrical pipelines arranged on a safety helmet. The method for consistency detection of mechanical and electrical pipelines includes: Obtain key frames containing target mechanical and electrical pipelines from the collected real-scene video of mechanical and electrical pipelines; Based on the pose data of the consistency detection device, perform image analysis on the key frames through a pre-trained image analysis module to obtain the target boundary endpoint coordinates of the target boundary of the target mechanical and electrical pipelines; Obtain a standard boundary in a pre-stored standard mechanical and electrical pipeline model that matches the target boundary; Compare the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates through a pre-trained information comparison module to obtain a coordinate comparison result; Obtain the visual positioning coordinates and visual pose data through a pre-trained imaging correction module, and correct the obtained visual positioning coordinates and visual pose data to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data; wherein, the visual positioning coordinates correspond to the target boundary endpoint coordinates; Based on the imaging positioning coordinates, the imaging pose data, and the standard electromechanical pipeline model, output a comparison image of the coordinate comparison result through the imaging correction module.

[0006] Optionally, analyzing the key frame through a pre-trained image analysis module based on the pose data of the consistency detection device to obtain the target boundary endpoint coordinates of the target electromechanical pipeline specifically includes: Enhance the light effect of the key frame to obtain an enhanced key frame; Denoise the enhanced key frame to obtain an optimized key frame; Perform edge recognition on the optimized key frame, and the recognition result includes the target boundary of the target electromechanical pipeline; Detect the target distance from the consistency detection device to the target endpoint of the target boundary; Based on the target distance and the pose data of the consistency detection device, calculate the target boundary endpoint coordinates of the target endpoint; wherein, the pose data at least includes the current device coordinates, the current viewing height, the current viewing orientation, and the current viewing pitch value of the consistency detection device, and the current device coordinates are located in the device coordinate system.

[0007] Optionally, correcting the visual positioning coordinates and visual pose data obtained by the imaging correction module through the pre-trained imaging correction module to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data specifically includes: Determine the imaging vertical coordinate by subtracting the difference between the visual vertical coordinate of the visual positioning coordinates and the preset device positioning difference; Combine the target horizontal coordinate, the target vertical coordinate of the target boundary endpoint coordinates, and the imaging vertical coordinate to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates; Calculate the imaging viewing pitch value from the target horizontal coordinate, the target vertical coordinate, and the imaging vertical coordinate; Replace the visual viewing pitch value in the visual pose data with the imaging viewing pitch value to obtain the imaging pose data corresponding to the visual pose data.

[0008] Optionally, the specific way of pre-storing the standard electromechanical pipeline model includes: Import the standard mechanical and electrical pipeline model into the learning and storage module in the consistency detection device; Obtain the model origin coordinates of the standard mechanical and electrical pipeline model and the initial device origin coordinates of the consistency detection device; wherein, the model origin coordinates are located in the standard coordinate system, and the initial device origin coordinates are located in the device coordinate system; Determine the coordinate difference between the model origin coordinates and the initial device origin coordinates; Based on the coordinate difference, convert the model mechanical and electrical pipeline coordinates included in the standard mechanical and electrical pipeline model to the device coordinate system to obtain the standard mechanical and electrical pipeline coordinates; Determine the standard device positioning coordinates, viewing height, viewing orientation, and viewing pitch value corresponding to the standard mechanical and electrical pipeline model as the initial pose data of the consistency detection device; wherein, the initial pose data includes initial device positioning coordinates, initial viewing height, initial viewing orientation, and initial viewing pitch value.

[0009] Optionally, the image analysis module is trained through the learning and storage module, and the training method of the image analysis module specifically includes: Obtain a training image containing the standard mechanical and electrical pipeline model; Perform edge recognition on the training image through the image analysis module to obtain the initial boundary of the standard mechanical and electrical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary; Detect the current distance from the consistency detection device to the initial endpoint; Input the current distance and the initial pose data into the image analysis module to obtain the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module; Based on the first loss value between the initial boundary endpoint coordinates and the standard boundary endpoint coordinates, train the image analysis module to obtain a trained image analysis module; and based on the trained image analysis module, execute the steps from performing edge recognition on the training image through the image analysis module to obtain the initial boundary of the standard mechanical and electrical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary to obtaining the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module until the initial boundary endpoint coordinates output by the image analysis module match the standard boundary endpoint coordinates.

[0010] Optionally, the image display correction module is trained through the learning and storage module, and the training method of the image display correction module specifically includes: Obtain the initial visual positioning coordinates and visual viewing pitch value containing the standard mechanical and electrical pipeline model through the image display correction module; Input the initial visual positioning coordinates and the visual angle pitch value into the imaging correction module to obtain the corrected visual positioning coordinates and the corrected visual angle pitch value output by the imaging correction module; Based on the second loss value between the corrected visual positioning coordinates and the standard electromechanical pipeline coordinates, and the third loss value between the corrected visual angle pitch value and the initial visual angle pitch value, train the imaging correction module to obtain a trained imaging correction module; and based on the trained imaging correction module, execute the step of inputting the initial visual positioning coordinates and the visual angle pitch value into the imaging correction module to obtain the corrected visual positioning coordinates and the corrected visual angle pitch value output by the imaging correction module, until the corrected visual positioning coordinates coincide with the standard electromechanical pipeline coordinates, and the corrected visual angle pitch value coincides with the initial visual angle pitch value.

[0011] In a second aspect, the present application provides a consistency detection device for electromechanical pipelines. The consistency detection device for electromechanical pipelines is arranged on a safety helmet. The consistency detection device for electromechanical pipelines includes a video acquisition module, an image analysis module, a learning and storage module, an information comparison module, and an imaging correction module, where: The video acquisition module is configured to obtain a key frame containing a target electromechanical pipeline from the collected real-scene video of the electromechanical pipeline; The image analysis module is configured to perform image analysis on the key frame based on the pose data of the consistency detection device to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline; The learning and storage module is configured to obtain a standard boundary in the pre-stored standard electromechanical pipeline model that matches the target boundary; The information comparison module is configured to compare the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates to obtain a coordinate comparison result; The imaging correction module is configured to obtain visual positioning coordinates and visual pose data through the imaging correction module, and correct the obtained visual positioning coordinates and visual pose data to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data; where the visual positioning coordinates correspond to the target boundary endpoint coordinates; The imaging correction module is further configured to output a comparison image of the coordinate comparison result based on the imaging positioning coordinates, the imaging pose data, and the standard electromechanical pipeline model through the imaging correction module.

[0012] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the consistency detection method for the electromechanical pipeline described in any one of the above.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the consistency detection method for the electromechanical pipeline described in any one of the above are implemented.

[0014] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the consistency detection method for the electromechanical pipeline described in any one of the above are implemented.

[0015] According to the specific embodiments provided by the present application, the following technical effects are disclosed: The present application provides a consistency detection method, device, equipment, medium and product for electromechanical pipelines. A consistency detection device for electromechanical pipelines can be set on a safety helmet. An image analysis module, an information comparison module and an image display correction module that have been pre-trained can be embedded in the consistency detection device, so that the consistency detection device has the function of consistency detection at the installation site, thereby realizing the consistency detection of the actual electromechanical pipeline and the standard electromechanical pipeline model at the installation site of the electromechanical pipeline, and the consistency detection result can be obtained more conveniently and quickly, improving the efficiency of the consistency detection of the electromechanical pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a schematic structural diagram of a consistency detection device for an electromechanical pipeline provided in an embodiment of the present application; Figure 2 For Figure 1 It is an installation schematic diagram of the consistency detection device for the electromechanical pipeline in Figure 3 It is a schematic flowchart of a consistency detection method for an electromechanical pipeline in an embodiment of the present application; Figure 4 It is a schematic diagram of the functional modules of another consistency detection device for an electromechanical pipeline provided in an embodiment of the present application; Figure 5Schematic structural diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0018] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0019] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0020] The consistency detection method for electromechanical pipelines provided by the embodiments of the present application can be applied to, for example, Figure 1 and Figure 2 the consistency detection device for electromechanical pipelines disposed on a safety helmet as shown. Figure 1 Schematic structural diagram of a consistency detection device for electromechanical pipelines provided by an embodiment of the present application; Figure 2 For Figure 1 the installation schematic diagram of the consistency detection device for electromechanical pipelines in, including: 1 - video acquisition module, 2 - image analysis module, 3 - synchronous positioning module, 4 - information comparison module, 5 - learning and storage module, 6 - image display correction module, 7 - ring, A - safety helmet. The consistency detection device can be installed on the A - safety helmet, and the acquisition direction of the 1 - video acquisition module is the same as the visual direction of the wearer of the A - safety helmet.

[0021] The 1 - video acquisition module can be an image acquisition device such as a camera or a webcam. The 1 - video acquisition module can be substantially parallel to the human face. The 3 - synchronous positioning module can be in the same plane as the center of the human forehead between the eyebrows. The main function of the 1 - video acquisition module is to acquire video images in the same direction as the line of sight, convert key frames, and transmit the key frames to the 2 - image analysis module.

[0022] The 2 - image analysis module is located above the 1 - video acquisition module on the left side, in the shape of a rectangular block, and is connected to the device main body through the 1 - video acquisition module. The main function is to identify the boundaries of electromechanical pipelines in the key frame pictures, and at the same time accumulate boundary recognition data through the 5 - learning and storage module to achieve autonomous recognition.

[0023] The 3 - Synchronous Positioning Module is located between the right 1 - Video Acquisition Module and the left 1 - Video Acquisition Module, above the 6 - Image Correction Module, and is directly connected to the device main body. It is in the shape of a rectangular block. Its main function is to synchronize the real - world position with the position of the built - in model. It has a built - in gyroscope to determine the device's orientation angle of view, and transmits the positioning and angle - of - view data to the 5 - Learning and Storage Module.

[0024] The 4 - Information Comparison Module is located above the right 1 - Video Acquisition Module. It is in the shape of a rectangular block and is connected to the device main body through the 1 - Video Acquisition Module. Its main function is to obtain the position information and angle - of - view information based on the 5 - Learning and Storage Module, extract the electromechanical pipeline boundary information with the same direction and the same angle at the same position in the built - in model, compare the coincidence degree between the electromechanical pipeline boundary from the 2 - Image Analysis Module and the electromechanical pipeline boundary extracted from the built - in model, and at the same time, accumulate and iterate the coincidence - degree comparison data through the 5 - Learning and Storage Module to achieve autonomous comparison.

[0025] The 5 - Learning and Storage Module is located above the 3 - Synchronous Positioning Module. It is in the shape of a rectangular block and is connected to the device main body through the 3 - Synchronous Positioning Module. Its main functions are to store the built - in model, identify the electromechanical pipeline boundary based on the 2 - Image Analysis Module, compare the electromechanical pipeline boundary based on the 4 - Information Comparison Module, correct the electromechanical pipeline boundary based on the 6 - Image Correction Module, and perform data accumulation and iterative learning.

[0026] The 6 - Image Correction Module is located between the 1 - Video Acquisition Modules. It is in the shape of a rectangular plate and consists of a middle transparent imaging layer and front and rear protective transparent lenses. It is connected to the device main body through a rotatable rod. Its main function is to correct the distance difference between the 1 - Video Acquisition Module and the visual line of sight. During this period, it performs line coloring and then imaging display according to the electromechanical pipeline boundary comparison situation of the 4 - Information Comparison Module, and at the same time, accumulates and iterates the perspective - difference correction data through the 5 - Learning and Storage Module to achieve autonomous correction.

[0027] The 7 - Ring is located in the middle of the device. It is in the shape of a ring. Its main functions are to fix each component module of the device as a device - bearing structure, and at the same time, enable the device to be sleeved on a safety helmet.

[0028] In an exemplary embodiment, as Figure 3 shown, a flow schematic diagram of a method for detecting the consistency of electromechanical pipelines is provided, including the following steps 301 to step 306. Among them: Step 301: Obtain key frames containing the target electromechanical pipeline from the collected real - scene video of the electromechanical pipeline.

[0029] In the embodiment of the present application, a key frame can be intercepted from the real - scene video of the electromechanical pipeline every preset time period (for example, 0.1 second). It is also possible to identify the real - scene video of the electromechanical pipeline and determine the frame image containing the target electromechanical pipeline as the key frame.

[0030] Step 302: Based on the pose data of the consistency detection device, perform image analysis on the key frame through a pre-trained image analysis module to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline.

[0031] In the embodiment of the present application, the pose data may include at least the current device coordinates, current viewing height, current viewing orientation, and current viewing pitch value of the consistency detection device. The current viewing orientation and current viewing pitch value can be collected by the built-in gyroscope of the consistency detection device.

[0032] As an alternative embodiment, the method for obtaining the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline by performing analysis on the key frame through a pre-trained image analysis module based on the pose data of the consistency detection device in step 302 may specifically include: Perform light effect enhancement on the key frame to obtain an enhanced key frame; Denoise the enhanced key frame to obtain an optimized key frame; Perform edge recognition on the optimized key frame, and the recognition result includes the target boundary of the target electromechanical pipeline; Detect the target distance from the consistency detection device to the target endpoint of the target boundary; Based on the target distance and the pose data of the consistency detection device, calculate the target boundary endpoint coordinates of the target endpoint; wherein, the pose data at least includes the current device coordinates, current viewing height, current viewing orientation, and current viewing pitch value of the consistency detection device, and the current device coordinates are located in the device coordinate system.

[0033] Among them, by implementing this embodiment, light effect enhancement and denoising can be performed on the key frame, improving the quality of the key frame, and thus improving the accuracy of target boundary recognition. In addition, the coordinates of the target endpoint can be calculated based on the detected target distance from the consistency detection device to the target endpoint and the pose data, improving the accuracy of the calculation of the target boundary endpoint coordinates.

[0034] In the embodiment of the present application, the Retinex algorithm can be used to improve the brightness and color of the image to make the image clearer and more vivid, thereby realizing light effect enhancement of the key frame to obtain an enhanced key frame.

[0035] In the embodiment of the present application, the BM3D algorithm can be used to denoise the enhanced key frame to obtain an optimized key frame, thereby maximizing the retention of the detailed information of the enhanced key frame.

[0036] In the embodiments of the present application, the edge contour of the target mechanical and electrical pipeline can be detected by the Canny operator, and the target boundary in the edge contour can be detected by the Hough transform. In addition, information such as the corner points and end points of the edge contour of the target mechanical and electrical pipeline can also be identified.

[0037] Optionally, the calculation method of the target boundary end point coordinates can be:

[0038] where is the current device coordinate, the target distance, the current view pitch value, is the current view orientation.

[0039] In the embodiments of the present application, the origin of the device coordinate system can be the center point of the 3-synchronous positioning module, and the positive direction of the y-axis of the device coordinate system can be the orientation of the camera in the 1-video acquisition module; the x-axis of the device coordinate system can be a horizontal line perpendicular to the y-axis, and the direction of the x-axis is not limited; the z-axis of the device coordinate system can be a line perpendicular to the plane formed by the y-axis and the x-axis, and the direction of the z-axis is not limited.

[0040] Step 303, obtain the standard boundary in the pre-stored standard mechanical and electrical pipeline model that matches the target boundary.

[0041] As an optional implementation manner, the specific pre-storing method of the standard mechanical and electrical pipeline model may include: Import the standard mechanical and electrical pipeline model into the learning and storage module in the consistency detection device; Obtain the model origin coordinates of the standard mechanical and electrical pipeline model and the initial device origin coordinates of the consistency detection device; where the model origin coordinates are located in the standard coordinate system, and the initial device origin coordinates are located in the device coordinate system; Determine the coordinate difference between the model origin coordinates and the initial device origin coordinates; Based on the coordinate difference, convert the model mechanical and electrical pipeline coordinates included in the standard mechanical and electrical pipeline model to the device coordinate system to obtain the standard mechanical and electrical pipeline coordinates;

[0042] Among them, when implementing this implementation method, the standard mechanical and electrical pipeline model can be stored in the consistency detection device in advance, and the model mechanical and electrical pipeline coordinates of the standard mechanical and electrical pipeline model can be converted into the device coordinate system to obtain the standard mechanical and electrical pipeline coordinates; the pose data corresponding to the standard mechanical and electrical pipeline model can also be determined as the initial pose data of the consistency detection device, so that the standard mechanical and electrical pipeline model can be better integrated into the consistency detection device.

[0043] In the embodiments of the present application, the origin of the standard coordinate system can be any point on the standard mechanical and electrical pipeline model, and the x-axis, y-axis, and z-axis of the standard coordinate system can be preset in advance, and the setting method of the x-axis, y-axis, and z-axis of the standard coordinate system is not limited.

[0044] In the embodiments of the present application, the standard mechanical and electrical pipeline coordinates The calculation method can be:

[0045] Among them, (X, Y, Z) can be the coordinate difference.

[0046] When the 4-information comparison module extracts the boundary information of the mechanical and electrical pipeline using the standard mechanical and electrical pipeline model stored in the 5-learning storage module, the boundary information is related to the initial device positioning coordinates, the initial viewing height, the initial viewing direction, and the initial viewing pitch value. Reset the viewing angle data in the standard mechanical and electrical pipeline model stored in the 5-learning storage module. The viewing angle data includes the initial viewing height, the initial viewing direction, and the initial viewing pitch value. Adjust and bind the synchronization according to the viewing angle data provided by the 3-synchronization positioning module to the 5-learning storage module, and complete the unification of the viewing angle data in the standard mechanical and electrical pipeline model stored in the 5-learning storage module and the viewing angle data of the 3-synchronization positioning module.

[0047] The 5-learning storage module reads the standard mechanical and electrical pipeline model, processes the standard mechanical and electrical pipeline model according to the basic principle of generating a model from points, lines and surfaces, eliminates the surfaces generated by the lines, and only retains the points and lines. Extract the coordinates of each point to establish the standard mechanical and electrical pipeline coordinates of the standard mechanical and electrical pipeline model, so as to improve the data comparison and processing efficiency of the 4-information comparison module when the consistency detection device is used.

[0048] The 5-learning storage module determines the initial device positioning coordinates according to the standard device positioning coordinates provided by the 3-synchronization positioning module, and establishes the initial pose data according to the viewing angle information provided by the 3-synchronization positioning module.

[0049] So far, the establishment of the standard mechanical and electrical pipeline coordinates, the initial device positioning coordinates, the initial viewing height, the initial viewing direction, and the initial viewing pitch value of the standard mechanical and electrical pipeline model is completed, laying a foundation for the data accumulation and iterative learning of subsequent modules.

[0050]

[0051] Among them, is the initial device positioning coordinate; is the same as the initial viewing height and identical; is the initial viewing direction, with a value range of 1 to 360; is the initial viewing pitch value, with a value range of -90 to 90.

[0052] In the embodiments of the present application, the experimental area can be selected to accumulate the learning data of the device. The electromechanical pipeline model in the experimental area is completely consistent with the actual electromechanical pipeline. The training content of the 5-learning storage module includes: Learning the boundary recognition of the electromechanical pipeline based on the 2-image analysis module, learning the boundary comparison of the electromechanical pipeline based on the 4-information comparison module, and learning the boundary correction of the electromechanical pipeline based on the 6-image display correction module; that is, training the 2-image analysis module, the 4-information comparison module, and the 6-image display correction module through the 5-learning storage module.

[0053] As an optional implementation manner, the training method of the image analysis module may specifically include: Obtain a training image containing a standard electromechanical pipeline model; Perform edge recognition on the training image through the image analysis module to obtain the initial boundary of the standard electromechanical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary; Detect the current distance from the consistency detection device to the initial endpoint; Input the current distance and the initial pose data into the image analysis module to obtain the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module; Train the image analysis module based on the first loss value between the initial boundary endpoint coordinates and the standard boundary endpoint coordinates to obtain the trained image analysis module; and perform the steps from performing edge recognition on the training image through the image analysis module to obtain the initial boundary of the standard electromechanical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary to obtaining the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module based on the trained image analysis module until the initial boundary endpoint coordinates output by the image analysis module match the standard boundary endpoint coordinates.

[0054] Among them, by implementing this implementation manner, the image analysis module can be trained to make the initial boundary endpoint coordinates output by the image analysis module more consistent with the standard boundary endpoint coordinates.

[0055] In the embodiments of the present application, according to the detected current distance from the device to the initial endpoint and the initial pose data of the consistency detection device, the initial boundary endpoint coordinates of the initial endpoint are calculated by the 5-learning storage module according to the following formula:

[0056] where s is the calculation number serial number of the 2-image analysis module; is the initial boundary endpoint coordinates obtained by the 2-image analysis module after calculating S times; is the current distance when the 2-image analysis module calculates S times; is the initial pitch value of the initial view angle when the 2-image analysis module calculates S times, is the initial orientation of the initial view angle when the 2-image analysis module calculates S times.

[0057] In the embodiments of the present application, during the training process, data accumulation is simultaneously performed on the coordinates to gradually improve the conversion rule, and this step is repeated until the calculated initial boundary endpoint coordinates coincide with the standard boundary endpoint coordinates at the corresponding position stored in the 5-learning storage module. Thus, the learning of the 2-image analysis module is completed.

[0058] In addition, the information comparison module can also be trained.

[0059] Specifically, the 4-information comparison module receives the electromechanical pipeline boundary recognition information transmitted by the 2-image analysis module. The 4-information comparison module, through the 5-learning storage module, reads the boundary information of the electromechanical pipeline model in the 5-learning storage module according to the coordinate information and view angle information provided by the 3-simultaneous localization module. The read content is the initial boundary endpoint coordinates corresponding to the position as described. The 4-information comparison module compares the initial boundary endpoint coordinates with the standard boundary endpoint coordinates, and the 4-information comparison module transmits the comparison result to the 5-learning storage module. The 5-learning storage module performs optimization learning, and this step is repeated until the calculated initial boundary endpoint coordinates are the same as the standard boundary endpoint coordinates at the corresponding position of the standard electromechanical pipeline model stored in the 5-learning storage module. At the same time, the iterative data is stored in the 5-learning storage module.

[0060]

[0061] In the formula: is the optimization objective function for calculating the numerical value of the X-axis coordinate of the initial boundary endpoint; is the optimization objective function for calculating the numerical value of the Y-axis coordinate of the initial boundary endpoint; is the optimization objective function for calculating the numerical value of the Z-axis coordinate of the initial boundary endpoint; is the gradient of the optimization objective function for calculating the numerical value of the X-axis coordinate of the initial boundary endpoint with respect to X; is the gradient of the optimization objective function for calculating the numerical value of the Y-axis coordinate of the initial boundary endpoint with respect to Y; Optimize the gradient of the objective function with respect to Z for calculating the Z-axis coordinate value of the initial boundary endpoint; is the learning rate. An overly high learning rate may cause the model to oscillate during training and even fail to converge. Although a too low learning rate can ensure the stability of model convergence, it will greatly increase the time required for convergence. As training progresses, gradually decrease the learning rate to ensure that the model can converge stably. The general value range is from 0.001 to 0.1.

[0062] Step 304: Compare the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates through a pre-trained information comparison module to obtain a coordinate comparison result.

[0063] Step 305: Obtain visual positioning coordinates and visual pose data through a pre-trained imaging correction module, and correct the obtained visual positioning coordinates and visual pose data to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data.

[0064] In the embodiment of the present application, the visual positioning coordinates correspond to the target boundary endpoint coordinates.

[0065] As an optional implementation manner, the way of step 305 to correct the visual positioning coordinates and visual pose data obtained by the imaging correction module through the pre-trained imaging correction module to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data may specifically include: Determine the imaging vertical coordinate by subtracting the preset device positioning difference from the visual vertical coordinate of the visual positioning coordinates; Combine the target horizontal coordinate, target vertical coordinate of the target boundary endpoint coordinates and the imaging vertical coordinate to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates; Calculate the imaging perspective pitch value from the target horizontal coordinate, the target vertical coordinate and the imaging vertical coordinate; Replace the visual perspective pitch value in the visual pose data with the imaging perspective pitch value to obtain the imaging pose data corresponding to the visual pose data.

[0066] Among them, when implementing this implementation manner, the visual vertical coordinate in the visual positioning coordinates can be adjusted according to a preset device positioning difference to obtain an adjusted imaging vertical coordinate. Furthermore, the target horizontal coordinate, target vertical coordinate, and imaging vertical coordinate of the target boundary endpoint coordinates can be combined to obtain imaging positioning coordinates. Additionally, an imaging perspective pitch value can be calculated based on the obtained imaging positioning coordinates, thereby correcting the visual positioning coordinates and visual pose data obtained by the imaging correction module, so that the corrected imaging positioning coordinates and imaging pose data match the pre-stored standard electromechanical pipeline model, reducing the errors in the visual positioning coordinates and visual pose data obtained by the imaging correction module.

[0067] In the embodiments of the present application, the imaging positioning coordinates and the imaging perspective pitch value can be calculated as follows:

[0068] where L is the device positioning difference, is the visual positioning coordinate.

[0069] As an optional implementation manner, the training method of the imaging correction module may specifically include: Obtain the initial visual positioning coordinates and visual perspective pitch value including the standard electromechanical pipeline model; Input the initial visual positioning coordinates and the visual perspective pitch value into the imaging correction module to obtain the corrected visual positioning coordinates and corrected perspective pitch value output by the imaging correction module; Based on the second loss value between the corrected visual positioning coordinates and the standard electromechanical pipeline coordinates, and the third loss value between the corrected perspective pitch value and the initial perspective pitch value, train the imaging correction module to obtain a trained imaging correction module; and based on the trained imaging correction module, execute the step of inputting the initial visual positioning coordinates and the visual perspective pitch value into the imaging correction module to obtain the corrected visual positioning coordinates and corrected perspective pitch value output by the imaging correction module until the corrected visual positioning coordinates match the standard electromechanical pipeline coordinates, and the corrected perspective pitch value matches the initial perspective pitch value.

[0070] Among them, when implementing this implementation manner, the imaging correction module can be trained so that the corrected visual positioning coordinates output by the imaging correction module match the standard electromechanical pipeline coordinates more closely, and the corrected perspective pitch value matches the initial perspective pitch value more closely.

[0071] Step 306: Based on the imaging positioning coordinates, the imaging pose data, and the standard electromechanical pipeline model, output a comparison image of the coordinate comparison result through the imaging correction module.

[0072] In the embodiment of the present application, in the coordinate comparison result, if the standard boundary endpoint coordinates coincide with the target boundary endpoint coordinates, the target boundary endpoint coordinates are determined as black identifiers; if the standard boundary endpoint coordinates do not coincide with the target boundary endpoint coordinates, the target boundary endpoint coordinates are determined as red identifiers.

[0073] Moreover, if both target boundary endpoint coordinates of a target boundary are black identifiers, then this target boundary is also determined as a black identifier; if both target boundary endpoint coordinates of a target boundary are red identifiers, then this target boundary is also determined as a red identifier; if one of the two target boundary endpoint coordinates of a target boundary is a black identifier and the other is a red identifier, then this target boundary is also determined as a black identifier.

[0074] In the embodiment of the present application, the inspector visually compares the endpoints and lines of different colors presented through the 6-imaging correction module with the lines of the electromechanical pipeline to be inspected, and compares the actual installation situation of the electromechanical pipeline with the standard installation effect of the model electromechanical pipeline, achieving the purpose of consistent use of the device for video measurement and detection of the electromechanical pipeline.

[0075] Implementing the above steps 301 to 306 can perform consistency detection on the actual electromechanical pipeline and the standard electromechanical pipeline model at the installation site of the electromechanical pipeline, enabling more convenient and rapid obtaining of the consistency detection result, and improving the efficiency of the consistency detection of the electromechanical pipeline. In addition, the present application can also improve the accuracy of target boundary recognition. In addition, the present application can also improve the accuracy of calculating the target boundary endpoint coordinates. In addition, the present application can also enable the standard electromechanical pipeline model to be better integrated into the consistency detection device. In addition, the present application can also make the initial boundary endpoint coordinates output by the image analysis module more consistent with the standard boundary endpoint coordinates. In addition, the present application can also make the corrected visual positioning coordinates output by the imaging correction module more consistent with the standard electromechanical pipeline coordinates, and make the corrected viewing angle pitch value more consistent with the initial viewing angle pitch value.

[0076] The present application also provides an application scenario that applies the above-mentioned method for consistency detection of electromechanical pipelines. Specifically: The method for consistency detection of electromechanical pipelines provided in this embodiment can be applied in the scenario of electromechanical pipeline installation and construction. After the electromechanical pipeline is installed, consistency detection can be performed on the electromechanical pipeline and the standard electromechanical pipeline model. The method for consistency detection of electromechanical pipelines provided in this embodiment belongs to the link of performing consistency detection on the electromechanical pipeline and the standard electromechanical pipeline model after the electromechanical pipeline is installed.

[0077] Based on the same inventive concept, an embodiment of the present application further provides a consistency detection device for electromechanical pipelines for implementing the above-mentioned consistency detection method for electromechanical pipelines. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the consistency detection device for electromechanical pipelines provided below can refer to the limitations on the consistency detection method for electromechanical pipelines in the above text, and will not be repeated here.

[0078] In an exemplary embodiment, as Figure 4 shown, a consistency detection device for electromechanical pipelines is provided, including a video acquisition module 401, an image analysis module 402, a learning and storage module 403, an information comparison module 404, and an image display correction module 405, where: The video acquisition module 401 is configured to obtain key frames containing the target electromechanical pipeline from the collected real-scene video of the electromechanical pipeline; The image analysis module 402 is configured to perform image analysis on the key frames based on the pose data of the consistency detection device to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline; The learning and storage module 403 is configured to obtain a standard boundary in the pre-stored standard electromechanical pipeline model that matches the target boundary; The information comparison module 404 is configured to compare the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates to obtain a coordinate comparison result; The image display correction module 405 is configured to obtain visual positioning coordinates and visual pose data through the image display correction module 405, and correct the obtained visual positioning coordinates and visual pose data to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data; where the visual positioning coordinates correspond to the target boundary endpoint coordinates; The image display correction module 405 is further configured to output a comparison image of the coordinate comparison result based on the imaging positioning coordinates, the imaging pose data, and the standard electromechanical pipeline model through the image display correction module.

[0079] As an optional implementation manner, the manner in which the image analysis module 402 performs analysis on the key frames based on the pose data of the consistency detection device to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline may specifically be: Perform light effect enhancement on the key frames to obtain enhanced key frames; Perform denoising on the enhanced key frames to obtain optimized key frames; Perform edge recognition on the optimized key frame, and the obtained recognition result includes the target boundary of the target electromechanical pipeline; Detect the target distance from the consistency detection device to the target endpoint of the target boundary; Based on the target distance and the pose data of the consistency detection device, calculate the target boundary endpoint coordinates of the target endpoint; wherein, the pose data at least includes the current device coordinates, the current viewing height, the current viewing orientation, and the current viewing pitch value of the consistency detection device, and the current device coordinates are located in the device coordinate system.

[0080] Among them, by implementing this implementation method, the light effect of the key frame can be enhanced and denoised, improving the quality of the key frame, and thus the accuracy of target boundary recognition can be improved. In addition, according to the detected target distance from the consistency detection device to the target endpoint and the pose data, the coordinates of the target endpoint can be processed, improving the accuracy of calculating the target boundary endpoint coordinates.

[0081] As an optional implementation method, the method for the imaging correction module 405 to correct the visual positioning coordinates and visual pose data obtained by the imaging correction module 405 to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging pose data corresponding to the visual pose data can be specifically as follows: Determine the imaging vertical coordinate by subtracting the preset device positioning difference from the visual vertical coordinate of the visual positioning coordinates; Combine the target horizontal coordinate, the target vertical coordinate of the target boundary endpoint coordinates, and the imaging vertical coordinate to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates; Calculate the imaging viewing pitch value from the target horizontal coordinate, the target vertical coordinate, and the imaging vertical coordinate; Replace the visual viewing pitch value in the visual pose data with the imaging viewing pitch value to obtain the imaging pose data corresponding to the visual pose data.

[0082] Among them, by implementing this implementation method, the visual vertical coordinate in the visual positioning coordinates can be adjusted according to the preset device positioning difference to obtain the adjusted imaging vertical coordinate, and then the target horizontal coordinate, the target vertical coordinate of the target boundary endpoint coordinates, and the imaging vertical coordinate can be combined to obtain the imaging positioning coordinates; the imaging viewing pitch value can also be calculated from the obtained imaging positioning coordinates, so as to correct the visual positioning coordinates and visual pose data obtained by the imaging correction module, so that the corrected imaging positioning coordinates and imaging pose data match the pre-stored standard electromechanical pipeline model, reducing the errors of the visual positioning coordinates and visual pose data obtained by the imaging correction module.

[0083] As an alternative implementation manner, the specific way of pre-storing the standard mechanical and electrical pipeline model may specifically include: Import the standard mechanical and electrical pipeline model into the learning and storage module in the consistency detection device; Obtain the model origin coordinates of the standard mechanical and electrical pipeline model and the initial device origin coordinates of the consistency detection device; wherein, the model origin coordinates are located in the standard coordinate system, and the initial device origin coordinates are located in the device coordinate system; Determine the coordinate difference between the model origin coordinates and the initial device origin coordinates; Based on the coordinate difference, convert the model mechanical and electrical pipeline coordinates included in the standard mechanical and electrical pipeline model to the device coordinate system to obtain the standard mechanical and electrical pipeline coordinates; Determine the standard device positioning coordinates, viewing height, viewing orientation, and viewing pitch value corresponding to the standard mechanical and electrical pipeline model as the initial pose data of the consistency detection device; wherein, the initial pose data includes the initial device positioning coordinates, the initial viewing height, the initial viewing orientation, and the initial viewing pitch value.

[0084] Among them, by implementing this implementation manner, the standard mechanical and electrical pipeline model can be pre-stored in the consistency detection device, and the model mechanical and electrical pipeline coordinates of the standard mechanical and electrical pipeline model can be converted to the device coordinate system to obtain the standard mechanical and electrical pipeline coordinates; the pose data corresponding to the standard mechanical and electrical pipeline model can also be determined as the initial pose data of the consistency detection device, so that the standard mechanical and electrical pipeline model can be better integrated into the consistency detection device.

[0085] As an alternative implementation manner, the image analysis module 402 is trained through the learning and storage module 403. The specific training method of the image analysis module 402 may specifically include: Obtain a training image containing the standard mechanical and electrical pipeline model; Perform edge recognition on the training image through the image analysis module 402 to obtain the initial boundary of the standard mechanical and electrical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary; Detect the current distance from the consistency detection device to the initial endpoint; Input the current distance and the initial pose data into the image analysis module 402 to obtain the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module 402; Based on the first loss value between the initial boundary endpoint coordinates and the standard boundary endpoint coordinates, train the image analysis module 402 to obtain the trained image analysis module 402; and based on the trained image analysis module 402, execute the steps from edge recognition of the training image by the image analysis module 402 to obtain the initial boundary of the standard electromechanical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary, to obtaining the initial boundary endpoint coordinates of the initial endpoints output by the image analysis module 402 until the initial boundary endpoint coordinates output by the image analysis module 402 match the standard boundary endpoint coordinates.

[0086] Among them, implementing this implementation method can train the image analysis module so that the initial boundary endpoint coordinates output by the image analysis module are more consistent with the standard boundary endpoint coordinates.

[0087] As an alternative implementation method, the imaging correction module 405 is trained through the learning and storage module 403. The training method of the imaging correction module 405 can specifically include: Obtain the initial visual positioning coordinates and the visual angle pitch value of the standard electromechanical pipeline model through the imaging correction module 405; Input the initial visual positioning coordinates and the visual angle pitch value into the imaging correction module 405 to obtain the corrected visual positioning coordinates and the corrected angle pitch value output by the imaging correction module 405; Based on the second loss value between the corrected visual positioning coordinates and the standard electromechanical pipeline coordinates, and the third loss value between the corrected angle pitch value and the initial angle pitch value, train the imaging correction module 405 to obtain the trained imaging correction module 405; and based on the trained imaging correction module 405, execute the step of inputting the initial visual positioning coordinates and the visual angle pitch value into the imaging correction module to obtain the corrected visual positioning coordinates and the corrected angle pitch value output by the imaging correction module 405 until the corrected visual positioning coordinates match the standard electromechanical pipeline coordinates, and the corrected angle pitch value matches the initial angle pitch value.

[0088] Among them, implementing this implementation method can train the imaging correction module so that the corrected visual positioning coordinates output by the imaging correction module are more consistent with the standard electromechanical pipeline coordinates, and the corrected angle pitch value is more consistent with the initial angle pitch value.

[0089] By implementing the above embodiments, the consistency between the actual mechanical and electrical pipelines and the standard mechanical and electrical pipeline model can be detected at the installation site of the mechanical and electrical pipelines, and the consistency detection result can be obtained more conveniently and quickly, improving the efficiency of the consistency detection of the mechanical and electrical pipelines. In addition, the present application can also improve the accuracy of target boundary recognition. In addition, the present application can also improve the accuracy of calculating the coordinates of the target boundary endpoints. In addition, the present application can also enable the standard mechanical and electrical pipeline model to be better integrated into the consistency detection device. In addition, the present application can also make the initial boundary endpoint coordinates output by the image analysis module more consistent with the standard boundary endpoint coordinates. In addition, the present application can also make the corrected visual positioning coordinates output by the imaging correction module more consistent with the standard mechanical and electrical pipeline coordinates, and make the corrected viewing angle pitch value more consistent with the initial viewing angle pitch value.

[0090] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 5 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store video tag processing data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a method for detecting the consistency of mechanical and electrical pipelines.

[0091] Those skilled in the art can understand that Figure 5 the structure shown in

[0092] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0093] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which when executed by a processor implements the steps in the above method embodiments.

[0094] In an exemplary embodiment, a computer program product is provided, including a computer program, which when executed by a processor implements the steps in the above method embodiments.

[0095] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0096] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0097] In each of the embodiments provided in this application, the database involved may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., without limitation. In each of the embodiments provided in this application, the processor may be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without limitation.

[0098] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0099] In this article, specific examples are used to elaborate on the principles and implementation manners of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A consistency detection method for electromechanical pipelines, characterized in that: The method is applied to a consistency detection device for electromechanical pipelines arranged on a safety helmet, and the consistency detection method for electromechanical pipelines comprises: Obtaining key frames containing target electromechanical pipelines from the collected real-life video of electromechanical pipelines; Based on the posture data of the consistency detection device, performing image analysis on the key frame through a pre-trained image analysis module to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline; Acquire a standard boundary matching the target boundary in a pre-stored standard electromechanical pipeline model; Comparing the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates through a pre-trained information comparison module to obtain a coordinate comparison result; Obtain visual positioning coordinates and visual posture data through a pre-trained imaging correction module, and correct the obtained visual positioning coordinates and visual posture data to obtain imaging positioning coordinates corresponding to the visual positioning coordinates and imaging posture data corresponding to the visual posture data; wherein the visual positioning coordinates correspond to the coordinates of the target boundary endpoint; Based on the imaging positioning coordinates, the imaging posture data and the standard electromechanical pipeline model, a comparison image of the coordinate comparison result is outputted through the imaging correction module.

2. The consistency detection method of electromechanical pipelines according to claim 1 is characterized in that: The step of analyzing the key frame based on the posture data of the consistency detection device by a pre-trained image analysis module to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline specifically includes: Performing light effect enhancement on the key frame to obtain an enhanced key frame; Denoising the enhanced key frame to obtain an optimized key frame; Performing edge recognition on the optimized key frame, and obtaining a recognition result including a target boundary of the target electromechanical pipeline; Detecting a target distance from the consistency detection device to a target endpoint of the target boundary; Based on the target distance and the posture data of the consistency detection device, the target boundary endpoint coordinates of the target endpoint are calculated; wherein the posture data at least includes the current device coordinates, current viewing angle height, current viewing angle direction and current viewing angle pitch value of the consistency detection device, and the current device coordinates are located in the device coordinate system.

3. The consistency detection method of electromechanical pipelines according to claim 1 is characterized in that: The method of correcting the visual positioning coordinates and visual posture data acquired by the imaging correction module through the pre-trained imaging correction module to obtain the imaging positioning coordinates corresponding to the visual positioning coordinates and the imaging posture data corresponding to the visual posture data specifically includes: Determine the difference between the visual vertical coordinate of the visual positioning coordinate and the preset device positioning difference as the imaging vertical coordinate; Combining the target horizontal coordinate and the target vertical coordinate of the target boundary endpoint coordinate and the imaging vertical coordinate to obtain the imaging positioning coordinate corresponding to the visual positioning coordinate; Calculating the target horizontal coordinate, the target vertical coordinate and the imaging vertical coordinate to obtain an imaging viewing angle pitch value; The visual viewing angle pitch value in the visual posture data is replaced with the imaging viewing angle pitch value to obtain imaging posture data corresponding to the visual posture data.

4. The consistency detection method of electromechanical pipeline according to any one of claims 1 to 3, characterized in that: The method of pre-storing the standard electromechanical pipeline model specifically includes: Importing the standard electromechanical pipeline model into the learning storage module in the consistency detection device; Obtaining the model origin coordinates of the standard electromechanical pipeline model and the initial device origin coordinates of the consistency detection device; wherein the model origin coordinates are located in the standard coordinate system, and the initial device origin coordinates are located in the device coordinate system; Determining the coordinate difference between the model origin coordinate and the initial device origin coordinate; Based on the coordinate difference, the model electromechanical pipeline coordinates included in the standard electromechanical pipeline model are converted into the device coordinate system to obtain the standard electromechanical pipeline coordinates; The standard device positioning coordinates, viewing angle height, viewing angle direction and viewing angle pitch value corresponding to the standard electromechanical pipeline model are determined as the initial posture data of the consistency detection device; wherein the initial posture data includes the initial device positioning coordinates, initial viewing angle height, initial viewing angle direction and initial viewing angle pitch value.

5. The consistency detection method of electromechanical pipelines according to claim 4 is characterized in that: The image analysis module is trained by the learning storage module, and the training method of the image analysis module specifically includes: Obtaining a training image containing a standard electromechanical pipeline model; Performing edge recognition on the training image through an image analysis module to obtain the initial boundary of the standard electromechanical pipeline model and the standard boundary endpoint coordinates of the initial endpoints of the initial boundary; Detecting a current distance from the consistency detection device to the initial endpoint; Inputting the current distance and the initial posture data into the image analysis module to obtain the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module; Based on the first loss value of the initial boundary endpoint coordinates and the standard boundary endpoint coordinates, the image analysis module is trained to obtain a trained image analysis module; and based on the trained image analysis module, the steps from edge recognition of the training image by the image analysis module to obtain the initial boundary of the standard electromechanical pipeline model and the standard boundary endpoint coordinates of the initial endpoint of the initial boundary, to obtaining the initial boundary endpoint coordinates of the initial endpoint output by the image analysis module, until the initial boundary endpoint coordinates output by the image analysis module match the standard boundary endpoint coordinates.

6. The consistency detection method of electromechanical pipelines according to claim 5 is characterized in that: The imaging correction module is trained by the learning storage module, and the training method of the imaging correction module specifically includes: Acquiring the initial visual positioning coordinates and the visual viewing angle pitch value of the standard electromechanical pipeline model through the imaging correction module; Inputting the initial visual positioning coordinates and the visual viewing angle pitch value into the display correction module to obtain the corrected visual positioning coordinates and the corrected viewing angle pitch value output by the display correction module; Based on the second loss value between the corrected visual positioning coordinates and the standard electromechanical pipeline coordinates, and the third loss value between the corrected viewing angle pitch value and the initial viewing angle pitch value, the display correction module is trained to obtain a trained display correction module; and based on the trained display correction module, the steps of inputting the initial visual positioning coordinates and the visual viewing angle pitch value into the display correction module to obtain the corrected visual positioning coordinates and the corrected viewing angle pitch value output by the display correction module are performed until the corrected visual positioning coordinates match the standard electromechanical pipeline coordinates, and the corrected viewing angle pitch value matches the initial viewing angle pitch value.

7. A consistency detection device for electromechanical pipelines, characterized in that: The electromechanical pipeline consistency detection device is arranged on a safety helmet, and the electromechanical pipeline consistency detection device includes a video acquisition module, an image analysis module, a learning storage module, an information comparison module and an image correction module, wherein: The video acquisition module is used to obtain key frames containing the target electromechanical pipeline from the acquired real-scene video of the electromechanical pipeline; The image analysis module is used to perform image analysis on the key frame based on the posture data of the consistency detection device to obtain the target boundary endpoint coordinates of the target boundary of the target electromechanical pipeline; The learning storage module is used to obtain a standard boundary matching the target boundary in a pre-stored standard electromechanical pipeline model; The information comparison module is used to compare the standard boundary endpoint coordinates of the standard boundary with the target boundary endpoint coordinates to obtain a coordinate comparison result; The imaging correction module is used to obtain visual positioning coordinates and visual posture data through the imaging correction module, and correct the obtained visual positioning coordinates and visual posture data to obtain imaging positioning coordinates corresponding to the visual positioning coordinates and imaging posture data corresponding to the visual posture data; wherein the visual positioning coordinates correspond to the target boundary endpoint coordinates; The imaging correction module is also used to output a comparison image of the coordinate comparison result through the imaging correction module based on the imaging positioning coordinates, the imaging posture data and the standard electromechanical pipeline model.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the electromechanical pipeline consistency detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the electromechanical pipeline consistency detection method described in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the electromechanical pipeline consistency detection method described in any one of claims 1 to 6 are implemented.

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