High-precision positioning mobile terminal device for electric power pipeline augmented reality inspection

Abstract

The invention relates to the technical field of mobile positioning calculation, in particular to high-precision positioning mobile terminal equipment for augmented reality inspection of power pipelines, which comprises a PDA (personal digital assistant) handheld terminal, a camera is fixedly connected to one side of the PDA handheld terminal, a display is arranged at one end, far away from the camera, of the PDA handheld terminal, and an electronic compass, a gyroscope and a processing system are arranged in the PDA handheld terminal; the processing system comprises an image acquisition module, a calibration module, a positioning module, an inspection data acquisition module, a GIS (Geographic Information System) data request module, a data standardization processing module, an SAR (Synthetic Aperture Radar) space construction module, a reality rendering enhancement module and a display module. And the GIS two-dimensional spatial data of the electric power pipeline are converted into visual augmented reality SAR data, so that the maintenance difficulty of the urban cable pipeline data is reduced, and the efficiency of cross-department business cooperation in an electric power enterprise is improved.

Description

Technical Field

[0001] The present invention relates to the field of mobile positioning computing technology, and in particular to a high-precision positioning mobile terminal device used for augmented reality inspection of power pipelines. Background Art

[0002] In the daily inspection process of urban cable pipelines, due to the high concealment of urban underground cable pipelines, the use of traditional underground cable pipeline GIS information not only has a certain threshold for map recognition, but also due to changes in environmental reference objects such as environmental changes, geological changes, and vegetation changes in real scenes, it is impossible to determine the specific actual location of the underground cable pipeline in the GIS information. At the same time, due to the lack of spatial sense of viewing pipelines in GIS information, the quality of line inspection by line inspectors cannot be guaranteed, and the accuracy of pipeline excavation cannot be guaranteed.

[0003] Therefore, it is necessary to propose a high-precision positioning mobile terminal device for augmented reality inspection of power pipelines to improve the efficiency of line inspection. When supervising and guiding non-power construction, there is no need for professionals to follow and check cable drawings on site, which improves work efficiency and ensures work safety. Summary of the invention

[0004] To solve the above problems, the present invention provides a high-precision positioning mobile terminal device for augmented reality inspection of power pipelines. By combining the GIS data of cable pipelines with the high-precision positioning of mobile terminals, and converting the GIS two-dimensional spatial data of power pipelines into intuitive, visualized augmented reality SAR data, the difficulty of maintaining urban cable pipeline data is reduced, and the efficiency of cross-departmental business collaboration within power companies is improved.

[0005] In order to achieve the above-mentioned object, the technical scheme of the present invention is as follows: a mobile terminal device for high-precision positioning of power pipeline augmented reality inspection comprises a PDA handheld terminal, a camera is fixedly connected to one side of the PDA handheld terminal, a display is provided at the end of the PDA handheld terminal away from the camera, and an electronic compass, a gyroscope and a processing system are provided in the PDA handheld terminal;

[0006] The processing system includes image acquisition module, calibration module, positioning module, inspection data acquisition module, GIS data request module, data normalization processing module, SAR space construction module, reality rendering enhancement module and display module;

[0007] An image acquisition module is used to capture images of the real environment through a camera;

[0008] The calibration module is used to correct the true north direction and calibrate the electronic compass and gyroscope;

[0009] Positioning module, including RTK positioning mode and CORS differential source base station positioning mode, is used to obtain external differential signals through positioning service providers, realize positioning, and obtain positioning information data;

[0010] Inspection data collection module, used to collect existing construction drawing data and surveying data of the target inspection site;

[0011] GIS data request module, used to request the cable pipeline GIS data within the authority from the data center according to the positioning information data;

[0012] Data normalization processing module, used for normalization processing of GIS data, construction drawing data and surveying and mapping data;

[0013] SAR space construction module, used to combine the converted plane data with the GIS data of the cable pipeline, and use it as the value of the Z axis of the three-dimensional coordinate system to convert the plane coordinate system to the three-dimensional coordinate system, and draw the dynamic cable pipeline model in the three-dimensional space to construct the SAR space;

[0014] A reality rendering enhancement module is used to overlay the virtual underground cable pipeline model onto the real scene image acquired by the camera based on the positioning information and data conversion results;

[0015] The display module is used to display the real scene image superimposed with the virtual model in real time.

[0016] The technical principle of the above scheme is as follows: the camera of the PDA handheld terminal obtains the image of the real environment, and the processing system handles the process from obtaining the spatial position information of the current position to integrating the virtual model with the spatial information of the underground cable, finding the marking points of the underground cables, converting the virtual marking point information into a cable pipeline model, and superimposing the rendered image on the image obtained by the camera to display the AR impression through the display screen. The gyroscope and gravity accelerometer are used to collect the six-axis posture information of the PAD, and adjust the position of the rendered cable model on the display in real time according to the posture and direction information.

[0017] The above scheme has the following beneficial effects:

[0018] 1. This solution uses augmented reality technology to accurately superimpose virtual underground cable pipeline models on real scenes, achieving intuitive and dynamic display of underground power pipelines. Operators can clearly see the layout, direction, burial depth and other key information of underground pipelines through the display screen of PDA handheld terminals, lowering the threshold for traditional GIS information recognition, so that non-professionals can quickly understand the actual situation of underground pipelines. At the same time, because AR technology can update the display content in real time, operators can view the latest pipeline information anytime and anywhere, thereby improving inspection efficiency and inspection safety.

[0019] 2. In this solution, the mobile terminal device integrates a variety of high-precision sensors, which can collect the location information, moving speed, and angle information of the mobile terminal in real time. Through the precise calculation and analysis of the processing system, the processing system can realize real-time positioning and tracking of the underground cable model, so that operators can obtain the precise location information of underground pipelines anytime and anywhere. No matter where the pipeline is located, it can be quickly and accurately located, which is of great significance for pipeline maintenance, inspection and troubleshooting, and can greatly improve the accuracy and efficiency of the work.

[0020] 3. In this solution, the mobile terminal device not only has the function of high-precision positioning, but also can be deeply integrated with the cable location information of the system database. Through the GIS data request module and the data normalization processing module, the device can obtain and process the cable pipeline GIS data, construction drawing data and surveying data within the authority in real time, so as to realize the comprehensive utilization of data, which not only enables the cable location information to be accurately displayed, but also improves the comprehensive utilization level of data. Enterprises can manage and utilize these data resources more conveniently, conduct more efficient data analysis and decision-making, thereby improving management efficiency and decision-making accuracy. At the same time, this data fusion method also provides strong support for future intelligent and automated inspections.

[0021] Furthermore, in the data normalization processing module, after the data is imported, the file is identified by MD5, and the existing data is identified and duplicated. At the same time, the summary data and the source file, creation time and name are stored in a unified data version;

[0022] When the data is CAD construction data and GIS data, it is also necessary to read the editing time inside the file to expand the file identifier. Finally, the internal editing time record of CAD and GIS is the first priority, and the creation and editing time of the file is the secondary priority for data version control.

[0023] Beneficial effects: File identification through the MD5 algorithm can ensure the uniqueness of each data file. This uniqueness not only helps to quickly identify and retrieve data, but also effectively prevents repeated data imports, thereby avoiding data redundancy and confusion. At the same time, identification and duplication detection with existing data can ensure data integrity and prevent loss or damage during data transmission or storage. In addition, unified data version storage of summary data and source files, creation time, and name can clearly track the source, change history, and current status of the data, ensure data traceability and consistency, and facilitate quick positioning of the correct data version when needed.

[0024] Furthermore, after the same data version is stored in the data normalization processing module, if multiple data sources are involved in the line data of a specified cable, the data source time is used first. If a cable data has different names in multiple data sources but other parameters are similar, it is regarded as the same line for merged version management.

[0025] Beneficial effects: When multiple data sources involve line data of the same cable, the data source time is used as the basis for priority adoption to ensure that the latest and most accurate data is adopted. This avoids decision-making errors caused by data lags or errors, and improves data consistency and reliability. In addition, for cable data with different names in multiple data sources but very similar other parameters (such as line direction, range, mileage, etc.), they are considered as the same line for merged version management, which effectively solves the data redundancy and inconsistency problems caused by naming differences and enhances data consistency.

[0026] Furthermore, in the SAR space construction module, the conversion of three-dimensional coordinates is performed through Gaussian inverse calculation to convert the projection coordinate system. The establishment of the Gaussian projection coordinate system requires the determination of the basic parameters of the cone surface. First, it is necessary to determine the central meridian on which it is located, and then determine the longitude on the meridian as the zero point, and use the longitude of a point on the meridian and the altitude of the point to determine the cone where the point is located.

[0027] Beneficial effects: Accurate projection coordinate system conversion through Gaussian inverse calculation can ensure that key information such as position, shape and size of two-dimensional GIS data is accurately retained when it is converted into three-dimensional spatial data, which helps to improve the positioning accuracy and visualization effect during power pipeline inspection. In addition, converting various types of non-uniform data (such as CAD data, surveying and mapping data, etc.) into unified standard WGS84 geodetic coordinate system data can eliminate differences and conflicts between data, achieve data unification and integration, and help build a complete cable pipeline data center and inspection visualization data application system.

[0028] Furthermore, the ORB-SLAM3 framework is used in the reality rendering enhancement module. The ORB-SLAM3 framework provides real-time rendering and interaction functions for the virtual underground cable pipeline model, including a SLAM system of visual inertial navigation and hybrid maps.

[0029] Beneficial effects: Improve positioning accuracy: The SLAM system of the ORB-SLAM3 framework can track the movement trajectory of the device in real time, and accurately locate it in combination with map information, ensuring that the virtual underground cable pipeline model can be accurately superimposed on the real environment, providing intuitive and accurate pipeline location information for inspection personnel. In addition, because the ORB-SLAM3 framework supports visual inertial navigation and hybrid maps, the device can maintain stable performance in various complex environments, whether it is light changes, interference from obstructions or dynamic scenes, the device can continue to operate stably, providing reliable support for inspection personnel.

[0030] Furthermore, the SLAM system supports the IMU mechanism, which uses the data obtained by the IMU unit to derive solutions through attitude, velocity, and position differential equations, converting them into approximate forms in discrete time, thereby solving the navigation information under discrete time sampling.

[0031] Beneficial effects: The IMU mechanism can obtain derived solutions of differential equations such as attitude, velocity, and position, and can solve navigation information more accurately under discrete time sampling, which helps to reduce positioning errors caused by environmental interference (such as weather and building occlusion) and improve the positioning accuracy of the overall system. In addition, combined with the multi-map and multi-session system characteristics of ORB-SLAM3, IMU data can assist the system to achieve more stable tracking and positioning in complex environments, ensuring accurate display of cable pipeline data.

[0032] Further, the IMU mechanism includes a visual MAP estimation module, an inertial MAP estimation module, and a visual inertial MAP estimation module;

[0033] The visual MAP estimation module initializes the monocular or binocular SLAM and starts running in the shortest time to obtain a map of a certain size consisting of k = 10 camera poses and a number of points. The map is optimized using visual BA only. These camera poses are converted into the context of the map for reference to obtain the trajectory I 0:k =[R,p] 0:k , where I and p mainly identify the variables of the next scale;

[0034] Inertial MAP estimation module is used to estimate the inertial 0:k and inertial measurements between these keyframes to obtain the best estimate of the inertial variables;

[0035] The visual-inertial MAP estimation module is used to perform joint visual-inertial optimization after having good estimates of inertial and visual parameters to further improve the results.

[0036] Beneficial effects: Rapid map construction: A map of a certain scale can be constructed in a short time, providing a basis for subsequent positioning and navigation. In addition, through visual-only BA optimization, the accuracy and consistency of the map are improved, and the positioning error is reduced.

[0037] Furthermore, in the inertia MAP estimation module, the inertia variables can be superimposed on the inertia-only state vector:

[0038]

[0039] where s is the visual-only scale factor, R wg is a rotation matrix used to calculate the gravity vector g = R in the reference frame wg gI, gI=(0,0,G)T, G is the magnitude of gravity; b=(b a ,b g )∈R6 are the biases of the accelerometer and gyroscope, which are considered constants during the initialization phase. is the velocity of the body from the first keyframe to the last keyframe, and the initial estimate comes from I 0:k , and only consider the inertial measurement set I 0:k ={I0,1...I k-1 ,k};

[0040] State the MAP estimation problem, where the posterior distribution to be maximized is:

[0041] p(y k |I 0:k )∝p(I 0:k |y k )p(y k )

[0042] p(I 0:k |y k ) represents the likelihood estimate, p(y k ) represents the prior value; considering the independence of measurement, the inertial MAP estimation problem can be written as:

[0043]

[0044] Taking the negative logarithm and assuming IMU pre-integration and Gaussian errors of the prior distribution, this ultimately leads to the optimization problem:

[0045]

[0046] The latest trajectory in the visual SLAM estimation is treated as a constant, and a prior residual is added to force the IMU bias to be close to zero;

[0047] When formally estimating, a shrinkage needs to be defined to update R during the estimation optimization process.wg , update using two angles (δ αg ,δ βg ) to parameterize:

[0048]

[0049] At the same time, in order to ensure that the scale factor remains greater than 0 during the optimization process, its update is defined as:

[0050] s new =s old Exp(δ s )

[0051] After the inertial optimization is complete, the frame pose, velocity, and 3D map points are scaled by the estimated scale factor and rotated to align the z-axis with the estimated gravity direction, the bias is updated, and the IMU pre-integration is repeated.

[0052] Beneficial effects: By integrating inertial information, the MAP estimation module can more accurately estimate the motion state of the device, thereby improving positioning accuracy. Especially in environments with insufficient light or many obstructions, the addition of inertial information can significantly reduce positioning errors. IMU data provides additional motion information, which helps the system remain robust in the face of fast motion or complex environments. The MAP estimation module further improves the stability and reliability of the system by optimizing the algorithm. In addition, through efficient algorithms and optimization processes, the MAP estimation module can reduce computing costs, improve resource utilization, help reduce system power consumption, and extend device usage time.

[0053] Furthermore, in the positioning module, the RTK mode calculates the current XYZ coordinates of the RTK by receiving orbital information and time information from satellite data and establishing a formula using the distance and the known XYZ coordinates of each satellite.

[0054] Beneficial effects: RTK mode can achieve centimeter-level or even sub-centimeter-level positioning accuracy, and can also receive and process satellite signals in real time, calculate and output high-precision positioning data in real time, making RTK mode perform well in application scenarios that require real-time positioning. In addition, RTK mode uses signals from multiple satellites for positioning. Even if some satellite signals are interfered with or blocked, accurate positioning can still be achieved through signals from other satellites, allowing RTK mode to maintain stable positioning performance in complex environments.

[0055] Furthermore, in the positioning module, the CORS differential source base station positioning mode is used to correct the positioning data. Based on the existing reference station, the continuously running reference station established by the multi-base station network real-time dynamic differential technology is used to measure the position, and the position coordinates of the mobile terminal device are accurately calculated with a measurement accuracy of centimeters.

[0056] Beneficial effects:

[0057] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The diagram is a schematic diagram of the operation of the processing system of an embodiment of a mobile terminal device for high-precision positioning of power pipeline augmented reality inspection according to the present invention. DETAILED DESCRIPTION

[0059] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] The following is further described in detail through specific implementation methods:

[0061] Embodiment 1:

[0062] As attached Figure 1 As shown: A high-precision positioning mobile terminal device for augmented reality inspection of power pipelines includes a PDA handheld terminal. The PDA handheld terminal integrates a camera, a display, an electronic compass, a gyroscope and a processing system, and has all the conditions required for developing augmented reality technology. The processing system includes an image acquisition module, a calibration module, a positioning module, an inspection data acquisition module, a GIS data request module, a data normalization processing module, a SAR space construction module, a reality rendering enhancement module and a display module.

[0063] The operation process of the equipment is described by taking the use process of a patrol inspection as an example:

[0064] First, the operator turns on the power of the device, loads the application, and initializes the reality rendering enhancement module. Since it adopts the ORB-SLAM3 framework, the ORB-SLAM3 framework provides real-time rendering and interactive functions for the virtual underground cable pipeline model, including the SLAM system of visual inertial navigation and hybrid map, and the SAR space is initialized by the SLAM system.

[0065] The operator can then capture the impact of the real environment through the image acquisition module, that is, the camera, and under guidance, point the PDA finger terminal to the geographic north direction to start the calibration module. The calibration module uses a unique independent plug-in that is isolated from magnetic force and is compatible with a physical magnetometer to perform north direction positioning correction to ensure accurate calibration of the electronic compass and gyroscope equipment.

[0066] After the application starts to calibrate the true north direction, the positioning module begins to play its role and obtain high-precision positioning information. However, due to the influence of environmental factors such as weather and buildings, signal differences may have a certain impact on positioning accuracy. Therefore, the high-precision positioning module is specially designed with two positioning modes: RTK positioning mode and CORS differential source base station positioning mode to ensure positioning accuracy.

[0067] The RTK mode receives orbit information (position) and time information from satellite data, and uses the distance and known coordinates (X, Y, Z) of each satellite to establish a formula to calculate the current precise coordinates (X, Y, Z) of RTK. In addition, as the number of satellites received increases, the known quantity will also increase, thereby further improving the positioning accuracy of RTK.

[0068] The CORS differential source base station positioning mode is equivalent to an RTK source, which is used to correct the positioning data to ensure the accuracy of the fixed solution calculation results. This design is based on the three existing reference stations in Shanghai, and uses the continuous operation reference station established by multi-base station network real-time dynamic differential technology to perform position measurement. According to the coordinates of the three known reference stations, the position coordinates of the mobile terminal device can be accurately calculated, and the measurement accuracy is as high as centimeter level.

[0069] After determining the positioning data, the PDA handheld mobile terminal starts the GIS data request module and requests the cable pipeline GIS data within the authority from the data center based on these positioning data. At the same time, the inspection data collection module collects the existing construction drawing data and surveying data of the target inspection site.

[0070] Next, the collected data and the requested GIS data are uniformly transferred to the data normalization processing module for data normalization processing. After importing each data, the file is identified by MD5, and the existing data is identified and repeated. At the same time, the summary data and the source file, creation time and name are uniformly stored in the data version; when the data is CAD construction data and GIS data, it is also necessary to read the internal editing time of the file to expand the file identification. Finally, the internal editing time record of CAD and GIS is the first priority, and the creation and editing time of the file is the secondary priority for data version control.

[0071] After completing the storage of the same data version, if multiple data sources are involved in the line data of a specified cable, the data source time will be used first; if a cable data has different names in multiple data sources but other parameters are similar, it will be regarded as the same line for merged version management.

[0072] After the data is normalized, the stored data is transferred to the SAR space construction module. This embodiment takes the WGS84 coordinate system data as an example, and converts the WGS84 geodetic coordinate system data into plane data, and combines the buried depth of the cable pipeline, the ellipsoid coefficient and other parameters as the value of the Z axis of the stereo coordinate system to convert the plane coordinate system into the stereo coordinate system. This means that the point P (Px, Py) in the plane coordinate system will be expressed as (Px, Py, Pz) in the stereo coordinate system, that is:

[0073]

[0074] Where N is the radius of the circle, a is the major axis of the Earth's ellipsoid; b is the minor axis of the Earth's ellipsoid.

[0075] This conversion can transform two-dimensional GIS data into three-dimensional spatial data and draw dynamic cable pipeline models in three-dimensional space, thereby completing the construction of SAR space.

[0076] The function of SAR augmented reality is mainly achieved by processing the reality-enhanced SAR space and presenting it visually through the display module of the PDA mobile terminal.

[0077] The reality rendering enhancement module adopts the ORB-SLAM3 framework, which provides real-time rendering and interactive functions for the virtual underground cable pipeline model, including visual inertial navigation and hybrid map SLAM system. The SLAM system supports the IMU mechanism, using the data obtained by the IMU unit to derive solutions through attitude, velocity, and position differential equations, and convert them into approximate forms under discrete time, so as to solve navigation information under discrete time sampling. This makes it possible for us to solve navigation information under discrete time sampling. Using the angular velocity and acceleration measured by the IMU, we calculate the current navigation information based on the navigation information of the previous moment, including attitude solution, velocity solution, position solution, etc., to make SLAM fit the real world space more accurately, thereby realizing accurate display, navigation, line patrol and other operations of SAR cable pipelines.

[0078] The IMU mechanism includes a visual MAP estimation module, an inertial MAP estimation module, and a visual inertial navigation MAP estimation module;

[0079] The visual MAP estimation module initializes the monocular or binocular SLAM and starts running in the shortest time to obtain a map of a certain size consisting of k = 10 camera poses and a number of points. The map is optimized using visual BA only. These camera poses are converted into the context of the map for reference to obtain the trajectory I 0:k =[R,p] 0:k , where I and p mainly identify the variables of the next scale.

[0080] Inertial MAP estimation module, in this step, our goal is to use I 0:k The inertial measurements between these keyframes are used to obtain the best estimate of the inertial variables, which can be superimposed on the inertia-only state vector in the Inertial MAP estimation module:

[0081]

[0082] where s is the visual-only scale factor, R wg is a rotation matrix used to calculate the gravity vector g = R in the reference frame wg gI, gI=(0,0,G)T, G is the magnitude of gravity; b=(b a ,b g )∈R6 are the biases of the accelerometer and gyroscope, which are considered constants during the initialization phase. is the velocity of the body from the first keyframe to the last keyframe, and the initial estimate comes from I 0:k , and only consider the inertial measurement set I 0:k ={I0,1...I k-1 ,k};

[0083] State the MAP estimation problem, where the posterior distribution to be maximized is:

[0084] p(y k |I 0:k )∝p(I 0:k |y k )p(y k )

[0085] p(I 0:k |y k ) represents the likelihood estimate, p(y k ) represents the prior value; considering the independence of measurement, the inertial MAP estimation problem can be written as:

[0086]

[0087] Taking the negative logarithm and assuming IMU pre-integration and Gaussian errors of the prior distribution, this ultimately leads to the optimization problem:

[0088]

[0089] The latest trajectory in the visual SLAM estimation is treated as a constant, and a prior residual is added to force the IMU bias to be close to zero;

[0090] When formally estimating, a shrinkage needs to be defined to update R during the estimation optimization process. wg, update using two angles (δ αg ,δ βg ) to parameterize:

[0091]

[0092] At the same time, in order to ensure that the scale factor remains greater than 0 during the optimization process, its update is defined as:

[0093] s new =s old Exp(δ s )

[0094] After the inertial optimization is complete, the frame pose, velocity, and 3D map points are scaled by the estimated scale factor and rotated to align the z-axis with the estimated gravity direction, the bias is updated, and the IMU pre-integration is repeated.

[0095] The visual-inertial MAP estimation module is used to perform joint visual-inertial optimization after having good estimates of inertial and visual parameters to further improve the results.

[0096] The MAP estimation mode designed in this scheme can achieve a scale error of 5% under a 2-second trajectory.

[0097] Finally, the display module will display the real-life scene image superimposed with the virtual model in real time through the display screen. The operator will inspect along the predetermined route based on the AR display on the screen to observe the location, direction, burial depth and other information of the cable pipeline.

[0098] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A high-precision positioning mobile terminal device for augmented reality inspection of power pipelines, characterized in that: It includes a PDA handheld terminal, a camera is fixedly connected to one side of the PDA handheld terminal, a display is arranged at the end of the PDA handheld terminal away from the camera, and an electronic compass, a gyroscope and a processing system are arranged in the PDA handheld terminal; The processing system includes image acquisition module, calibration module, positioning module, inspection data acquisition module, GIS data request module, data normalization processing module, SAR space construction module, reality rendering enhancement module and display module; An image acquisition module is used to capture images of the real environment through a camera; The calibration module is used to correct the true north direction and calibrate the electronic compass and gyroscope; Positioning module, including RTK positioning mode and CORS differential source base station positioning mode, is used to obtain external differential signals through positioning service providers, realize positioning, and obtain positioning information data; Inspection data collection module, used to collect existing construction drawing data and surveying data of the target inspection site; GIS data request module, used to request the cable pipeline GIS data within the authority from the data center according to the positioning information data; Data normalization processing module, used for normalization processing of GIS data, construction drawing data and surveying and mapping data; SAR space construction module, used to combine the converted plane data with the GIS data of the cable pipeline, and use it as the value of the Z axis of the three-dimensional coordinate system to convert the plane coordinate system to the three-dimensional coordinate system, and draw the dynamic cable pipeline model in the three-dimensional space to construct the SAR space; A reality rendering enhancement module is used to overlay the virtual underground cable pipeline model onto the real scene image acquired by the camera based on the positioning information and data conversion results; The display module is used to display the real scene image superimposed with the virtual model in real time.

2. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 1 is characterized in that: In the data normalization processing module, after the data is imported, the file is identified by MD5, and the existing data is identified and duplicated. At the same time, the summary data and the source file, creation time and name are stored in a unified data version; When the data is CAD construction data and GIS data, it is also necessary to read the editing time inside the file to expand the file identifier. Finally, the internal editing time record of CAD and GIS is the first priority, and the creation and editing time of the file is the secondary priority for data version control.

3. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 2 is characterized in that: After the same data version is stored in the data normalization processing module, if multiple data sources are involved in the line data of a specified cable, the data source time will be used first. If a cable data has different names in multiple data sources but other parameters are similar, it will be regarded as the same line for merged version management.

4. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 3 is characterized in that: In the SAR space construction module, the conversion of stereo coordinates is performed through Gaussian inverse calculation to convert the projection coordinate system. The establishment of the Gaussian projection coordinate system requires the determination of the basic parameters of the cone surface. First, it is necessary to determine the central meridian on which it is located, and then determine the longitude on the meridian as the zero point, and use the longitude of a point on the meridian and the altitude of the point to determine the cone where the point is located.

5. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 4 is characterized in that: In the reality rendering enhancement module, the ORB-SLAM3 framework is used. The ORB-SLAM3 framework provides real-time rendering and interactive functions for the virtual underground cable pipeline model, including a SLAM system of visual inertial navigation and hybrid maps.

6. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 5 is characterized in that: The SLAM system supports the IMU mechanism, and uses the data obtained by the IMU unit to derive solutions through the attitude, velocity and position differential equations, converting them into approximate forms under discrete time, thereby solving the navigation information under discrete time sampling.

7. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 6 is characterized in that: The IMU mechanism includes a visual MAP estimation module, an inertial MAP estimation module, and a visual inertial navigation MAP estimation module; The visual MAP estimation module initializes the monocular or binocular SLAM and starts running in the shortest time to obtain a map of a certain size consisting of k = 10 camera poses and a number of points. The map is optimized using visual BA only. These camera poses are converted into the context of the map as key frames for reference to obtain the trajectory I 0:k =[R,p] 0:k , where I and p mainly identify the variables of the next scale; Inertial MAP estimation module is used to estimate the inertial 0:k and inertial measurements between several keyframes to obtain the best estimate of the inertial variables; The visual-inertial MAP estimation module is used to perform joint visual-inertial optimization after having good estimates of inertial and visual parameters to further improve the results.

8. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 7 is characterized in that: In the Inertia MAP estimation module, the inertia variables can be added to the inertia-only state vector: where s is the visual-only scale factor, R wg is a rotation matrix used to calculate the gravity vector g = R in the reference frame wg gI, gI=(0,0,G)T, G is the magnitude of gravity; b=(b a ,b g )∈R6 are the biases of the accelerometer and gyroscope, which are considered constants during the initialization phase. is the velocity of the body from the first keyframe to the last keyframe, and the initial estimate comes from I 0:k , and only consider the inertial measurement set I 0:k ={I0,1...I k-1 ,k}; State the MAP estimation problem, where the posterior distribution to be maximized is: p(y k |I 0:k )∝p(I 0:k |y k )p(y k ) p(I 0:k |y k ) represents the likelihood estimate, p(y k ) represents the prior value; considering the independence of the measurements, the inertial MAP estimation formula is as follows: Taking the negative logarithm and assuming the Gaussian error of IMU pre-integration and prior distribution, the formula after bringing in the independent variables and simplifying is as follows: Trajectory Estimation in Visual SLAM I i-1,i is regarded as a constant, and a priori residuals are added to force the IMU bias to be close to zero. The possible range of values ​​of the IMU bias is predetermined by the covariance matrix ∑b. A contraction needs to be defined in the formal estimation to update R during the estimation optimization process. wg , update using two angles (δ αg ,δ βg ) to parameterize: At the same time, in order to ensure that the scale factor remains greater than 0 during the optimization process, its update is defined as: s new =s old Exp(δ s ) After the inertial optimization is completed, the frame pose, velocity and 3D map points are scaled by the estimated scale factor and rotated to align the z-axis with the estimated gravity direction, the bias is updated and the IMU pre-integration is repeated, followed by the visual inertial MAP estimation.

9. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 8, characterized in that: In the positioning module, the RTK positioning mode receives the orbit information and time information from the satellite data, uses the distance and the known XYZ coordinates of each satellite to establish a formula, and calculates the current XYZ coordinates of the RTK.

10. The high-precision positioning mobile terminal device for augmented reality inspection of power pipelines according to claim 9, characterized in that: In the positioning module, the CORS differential source base station positioning mode is used to correct the positioning data. Based on the existing reference station, the continuously running reference station established by the real-time dynamic differential technology of the multi-base station network is used to perform position measurement and calculate the position coordinates of the mobile terminal device with a measurement accuracy of centimeters.

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