Overhead line channel hidden danger distance real-time measurement method, system and equipment based on handheld laser scanner

Abstract

The invention relates to the technical field of electric power overhead line channel checking, in particular to an overhead line channel hidden danger distance real-time measurement method, system and device based on a handheld laser scanner. The device comprises a handheld laser scanner and a mobile terminal, the handheld laser scanner is connected with the mobile terminal in a matched mode through a wifi module, a data decoding program is arranged in the mobile terminal, the data decoding program converts decoded data into a three-dimensional scene, and the three-dimensional scene is displayed on a screen of the mobile terminal. The point cloud range of the lead and the hidden danger object is selected through a built-in frame selection tool of the data decoding program, and the data decoding program automatically calculates the minimum clearance distance between the selected lead and the hidden danger object based on a point cloud distance measurement algorithm. According to the invention, the wire and the hidden danger object are scanned through the handheld laser scanner, and the scanned data are transmitted to the data decoding program of the mobile terminal, so that whether the channel between the wire and the hidden danger object has hidden danger is judged, and the operation is simple and convenient.

Description

Technical Field

[0001] The present invention belongs to the technical field of overhead line channel verification, and in particular relates to a method, system and equipment for real-time measurement of hidden danger distances in overhead line channels based on a handheld laser scanner. Background Art

[0002] During routine maintenance and inspection of overhead power lines, it is crucial to check whether obstacles, vegetation, buildings, crossing wires, etc. around the lines threaten line safety. Existing technical solutions mainly include the following:

[0003] Manual inspection:

[0004] Inspection personnel primarily rely on visual inspection or simple measuring tools, such as rangefinders and altimeters, to inspect the environment surrounding the lines and record potential safety hazards. Manual inspections are simple to perform and do not require complex equipment, making them suitable for areas with relatively flat terrain or easy access. However, manual inspections are time-consuming and labor-intensive, inefficient, and easily affected by environmental factors (such as inclement weather and complex terrain). They carry the risk of missed inspections and errors, and cannot accurately quantify safety distances.

[0005] Drone inspection:

[0006] Drones equipped with high-definition cameras or infrared cameras can remotely capture and monitor lines, assisting inspectors in identifying potential hazards within corridors. Drones can cover a wide area, adapt to complex terrain, and reduce the workload of manual inspections, making them particularly suitable for inspecting high-risk areas. While drones can provide video and image data, data analysis still relies on manual or semi-automated tools, making real-time analysis and classification difficult. Furthermore, the use of drones is limited by weather conditions, and flight time and battery life restrict their inspection range.

[0007] Vehicle-mounted LiDAR inspection:

[0008] Vehicle-mounted LiDAR scans the route, acquiring point cloud data of the surrounding environment. This data is then processed and analyzed in the background to identify potential hazards. Vehicle-mounted LiDAR can collect large amounts of high-precision 3D data in a short period of time, covering long route distances and achieving high data acquisition efficiency. However, vehicle-mounted LiDAR inspections also have their drawbacks, such as the need for dedicated vehicles and high-cost LiDAR equipment. Data processing is typically performed in the background, preventing real-time analysis and feedback. Furthermore, vehicle-mounted equipment is difficult to implement in areas with poor road conditions or where vehicles are inaccessible.

[0009] Static LiDAR point cloud detection:

[0010] Static LiDAR equipment is installed in specific areas (such as near substations and tower bases) to periodically or continuously scan the surrounding environment and upload point cloud data to the backend for processing and analysis. This method is suitable for continuous monitoring of fixed points, generating high-precision, continuous point cloud data for long-term environmental change monitoring. However, this method has the disadvantages of limited coverage of fixed-point LiDAR, making it ineffective for monitoring long-distance power lines. Data processing requires backend support, resulting in poor real-time performance and high costs.

[0011] The Chinese patent with announcement number CN108830893A discloses a method for optimizing power grid lines based on a three-dimensional laser scanner. The method is as follows: using a three-dimensional laser scanner to obtain point cloud data of electric towers and lines; importing the point cloud data into Geomagic Studio software to realize point cloud data processing and three-dimensional model establishment, and determining the type of high-voltage transmission line and its line corridor standard and safety distance according to the model; and determining whether the line corridor and the minimum distance from the building meet the safety distance according to the model. If not, line optimization is performed. The above invention cannot quickly derive the minimum clearance distance based on the frame selection position, and the scanning position requirements of the laser scanner are too high, and the impact of the scanning error is too large. Therefore, it is urgent for those skilled in the art to solve the above technical problems. Summary of the Invention

[0012] The technical problem to be solved by the present invention is that in the above-mentioned prior art, the inspection of hidden dangers in overhead line channels is greatly affected by weather and environment, and cannot be flexibly measured, resulting in poor inspection results of line hidden dangers.

[0013] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0014] A real-time measurement device for hidden danger distances in overhead line channels based on a handheld laser scanner includes a handheld laser scanner and a mobile terminal. The handheld laser scanner is connected to the mobile terminal via a Wi-Fi module. The mobile terminal is provided with a data decoding program. The data decoding program decodes the data measured by the laser scanner, converts the decoded data into a three-dimensional scene, and presents it on the screen of the mobile terminal. The point cloud range of the conductor and the hidden danger object is selected using the built-in box selection tool of the data decoding program, and the data decoding program automatically calculates the minimum clearance distance between the selected conductor and the hidden danger object.

[0015] By adopting the above technical solutions, the equipment allows inspectors to quickly and efficiently complete inspections of hidden dangers in power line channels without relying on traditional manual inspection methods, reducing workload and time costs. Data is collected through a high-precision handheld laser scanner, and combined with GNSS and INS technology to provide accurate position and attitude information, ensuring the authenticity and accuracy of point cloud data. The function of automatically calculating the minimum clearance distance reduces human error and provides a more reliable safety distance assessment. The equipment can complete solution, fusion and transmission of data while collecting, realizing true real-time measurement, allowing inspectors to obtain results and respond immediately. The three-dimensional scene rendering on the mobile terminal allows inspectors to view and analyze the on-site situation in real time, speeding up the decision-making process. The handheld design allows the device to be used in various terrain conditions, including those not suitable for drones or vehicles, greatly expanding its scope of application.

[0016] The present invention also discloses a real-time measurement system for hidden danger distances of overhead line channels based on a handheld laser scanner. The real-time measurement device for hidden danger distances of overhead line channels based on a handheld laser scanner is used as a carrier. The system includes a real-time data acquisition module, a real-time data processing module, a real-time data transmission module and a data decoding and display module. The real-time data acquisition module measures the position information of the conductor and the hidden danger object and the laser point cloud information through the handheld laser scanner and transmits them to the real-time data processing module. The real-time data processing module transmits the processed data to the data decoding and display module through the real-time data transmission module. The data decoding and display module in the mobile terminal decodes the data and presents it on the display screen.

[0017] By adopting the above technical solutions, the entire process from data collection to final result display is highly automated, reducing human intervention and improving work efficiency. Automated data processing and calculation reduce errors caused by human operational errors. The combination of GNSS, INS and laser point cloud technology ensures the accuracy of location information, thereby improving the accuracy of hidden danger distance measurement. The seamless connection between modules ensures the rapid flow of data from collection to display and provides almost instant result feedback. The handheld design makes the device easily applicable to various complex environments, including those that are not suitable for large equipment to enter. It is not restricted by weather conditions and can be used for inspections at any time, which increases work flexibility. It can promptly detect and warn of potential safety hazards, help prevent accidents, and ensure the safe operation of the power grid. By accurately identifying the locations that require maintenance, maintenance resources can be arranged more specifically to avoid unnecessary inspections or delays.

[0018] Furthermore, the real-time data processing module includes a real-time position and attitude solution module, a real-time data fusion module, and a point cloud thinning and denoising module; the data of the real-time data acquisition module is transmitted to the real-time position and attitude solution module through global satellite navigation and inertial navigation to collect the position information of the wire and the hidden danger, and the laser point cloud data is obtained by laser scanning the wire and the hidden danger and transmitted to the real-time data fusion module; the data processed by the real-time position and attitude solution module and the real-time data fusion module are imported into the point cloud thinning and denoising module for processing.

[0019] By adopting the above technical solution, by combining the Global Navigation Satellite System (GNSS) and the Inertial Navigation System (INS), more accurate position and attitude information can be provided, and error accumulation can be reduced. Even in the case of poor signal or no GNSS signal, the INS can continue to provide relatively stable position and attitude updates, ensuring the continuous operation of the system. The module can quickly solve the position and attitude of the carrier, providing a timely and accurate basis for subsequent data processing. By complementing the advantages of multiple data sources, it can eliminate the limitations that may exist in a single data source, such as GNSS signal obstruction problems or INS drift errors over time. The use of fusion algorithms (such as Kalman filters) can improve the accuracy of data solution while ensuring calculation speed. Through thinning processing, unnecessary point cloud data is reduced, which reduces storage requirements and transmission bandwidth, while maintaining the integrity of key features. After removing noise points, the efficiency and speed of subsequent calculations are improved, which is particularly important when performing complex calculations on mobile terminals.

[0020] Furthermore, the real-time data transmission module includes a scanner WIFI module and a mobile WIFI module. The scanner WIFI module and the mobile WIFI module are matched and connected, and the data processed by the real-time data processing module is transmitted to the mobile WIFI module through the scanner WIFI module.

[0021] By adopting the above technical solution, the wireless connection achieved through the WIFI module does not require additional wiring, which simplifies the equipment deployment process and improves the flexibility of on-site operations. The automatic matching connection between the scanner WIFI module and the mobile WIFI module ensures that the two can quickly establish a communication link, reducing setup time. Modern WIFI technology (such as 802.11ac or 802.11ax) provides a high bandwidth, which is sufficient to meet the real-time transmission requirements of large amounts of point cloud data, ensuring the speed and efficiency of data transmission. The low latency feature ensures that the entire process from data acquisition to display is almost seamless, and users can obtain almost instant result feedback, which is crucial for application scenarios that require rapid decision-making. WIFI modules generally have good anti-interference capabilities and signal stability, and can maintain reliable data transmission even in complex electromagnetic environments. The built-in error detection and correction mechanism can effectively prevent data packet loss or damage, ensuring the integrity and accuracy of transmitted data.

[0022] Furthermore, the data decoding and display module includes a real-time point cloud rendering function, a manual selection function and a spatial distance calculation function; the data received by the mobile WIFI module is rendered on the display screen of the mobile terminal through the real-time point cloud rendering function, and the target area is selected through the manual selection function, and the spatial distance calculation function automatically realizes the minimum clearance distance calculation of the target area.

[0023] The present invention also discloses a real-time measurement method for the hidden danger distance of an overhead line channel based on a handheld laser scanner. The method measures and calculates the minimum clearance distance of a hidden danger object or conductor using a real-time measurement system for the hidden danger distance of an overhead line channel based on a handheld laser scanner. The method comprises the following steps:

[0024] Step 1: Use the real-time data acquisition module to collect real-time position data and laser point cloud data;

[0025] Step 2: The real-time data processing module is used to solve the position data and integrate it to obtain the real-time position, speed, and attitude information;

[0026] Step 3: Match the points of the laser point cloud with the real-time positioning data obtained by mobile measurement, and fuse the laser point cloud data with the calculated absolute position and posture information to obtain real-time point cloud data with absolute coordinates;

[0027] Step 4: Perform thinning and denoising on the solved real-time point cloud data;

[0028] Step 5: The thinned and denoised point cloud data is sent to the mobile terminal via the real-time data transmission module. The data decoding and display module of the mobile terminal obtains a three-dimensional scene through decoding and visualization rendering.

[0029] Step 6: On the mobile terminal, you can translate or rotate the real-time point cloud scene, use the selection tool to manually select the wire and potential danger point cloud range, and calculate the minimum clearance distance between the selected wire and the potential danger point cloud.

[0030] Through the above technical solution, the entire process from data collection to final result display is highly automated, reducing manual intervention and improving work efficiency. Users can instantly view the processed 3D scene and calculation results and make decisions quickly, which is particularly suitable for responding in emergency situations. The combination of GNSS, INS and laser point cloud technology ensures the accuracy of location information, thereby improving the accuracy of hidden danger distance measurement. By thinning and denoising the point cloud data, not only the data volume is reduced, but also the accuracy and speed of subsequent analysis are improved. The handheld design makes the device easily applicable to various complex environments, including those places that are not suitable for large equipment to enter. It is not restricted by weather conditions and can perform inspections at any time, which increases work flexibility. It can promptly detect and warn of potential safety hazards, help prevent accidents, and ensure the safe operation of the power grid. By accurately identifying the locations that require maintenance, maintenance resources can be arranged more targeted to avoid unnecessary inspections or delays.

[0031] Furthermore, in step 1, a GNSS receiver, an inertial navigation module and a laser transmitter are provided in the handheld laser scanner. A real-time position and attitude solution module is formed by the GNSS receiver, the inertial navigation module and the laser transmitter. The mobile measurement process adopts a carrier coordinate system, with the origin of the inertial navigation coordinate system as the origin of the carrier coordinate system, the forward direction of the carrier as the positive direction of the Y axis, the right as the positive direction of the X axis, and the upward direction as the positive direction of the Z axis. Real-time GNSS data, INS data and laser point cloud data are collected by the GNSS receiver, the inertial navigation device and the laser transmitter.

[0032] Furthermore, in steps 2 and 3, real-time position information is obtained according to the GNSS receiver; the INS data of the inertial navigation module is solved to obtain attitude update information, velocity update information and position update information; real-time state estimation is performed based on the GNSS data, and the absolute position and attitude information are calculated. The GNSS positioning algorithm and the strapdown inertial guidance numerical recursive algorithm are combined through the Kalman filter, and the position and other change information output by the two are matched. State estimation is performed online to obtain the state at each moment, and the absolute position and attitude information are obtained. The absolute position information recording system is in the geodetic coordinates (B, L, H) under the WGS84 coordinate system, wherein the attitude angle information includes: roll angle, pitch angle and yaw angle, wherein the roll angle is the angle between the x-axis of the carrier and the horizontal direction, and the right side of the carrier is downward and positive; the pitch angle is the angle between the y-axis of the carrier and the horizontal direction, and the carrier is upward and positive; the yaw angle is the angle between the forward direction of the carrier and the true north direction;

[0033] Match the points of the laser point cloud with the obtained real-time positioning data, and fuse the laser point cloud data with the calculated absolute position and posture information through the real-time data fusion module to obtain real-time point cloud data with absolute coordinates. The calculation formula for real-time point cloud data with absolute coordinates is as follows:

[0034]

[0035] Among them, X b Indicates the original point cloud coordinates in the carrier coordinate system, X e Represents the three-dimensional point cloud coordinates in the world coordinate system, Represents the rotation matrix from the carrier coordinate system to the world coordinate system, Represents the position vector of the origin of the carrier coordinate system in the world coordinate system;

[0036] Rotation Matrix The calculation formula is as follows:

[0037]

[0038] , where yaw represents the yaw angle, roll represents the roll angle, and pitch represents the pitch angle.

[0039] Furthermore, in step 4, the solved point cloud data is thinned and denoised through the point cloud thinning and denoising module, and the voxel grid filtering method is used in the point cloud thinning and denoising module to thin out the point cloud data of the wires or hidden dangers; when performing denoising, statistical analysis or density-based filtering methods are used to remove outliers or erroneous data points to reduce the false alarm of noise points during the measurement process.

[0040] Furthermore, in steps 5 and 6, real-time point cloud data transmission is achieved through the scanner WIFI module, the mobile terminal receives the point cloud data through the mobile terminal WIFI module, and the data decoding and display module of the mobile terminal decodes and renders the data to obtain a visualized three-dimensional point cloud scene. The wire or hidden danger is manually selected as the target area through the selection tool, and the data decoding and display module calculates the Euclidean distance or the point-to-surface distance to achieve the minimum clearance distance measurement between the target objects. The Euclidean distance is:

[0041]

[0042] The spatial coordinates of P1 are (x1 y1 z1), the spatial coordinates of P2 are (x2 y2 z2), and d is the spatial distance between P1 and P2. P1 is the position of the wire selected by the box, and P2 is the position of the hidden danger selected by the box.

[0043] The present invention has the following beneficial effects:

[0044] 1. This invention uses a handheld laser scanner to scan lines and can be used in various complex environments, including those unsuitable for drones or vehicles. This greatly expands the scope of application and is not restricted by weather conditions. Inspection operations can be carried out at any time, increasing work flexibility. 3D scene rendering on mobile terminals allows users to more intuitively understand the on-site situation. The built-in selection tool simplifies user operation steps, enabling timely detection and warning of potential safety hazards, helping to prevent accidents and ensure the safe operation of the power grid.

[0045] 2. This invention highly automates the entire process from data acquisition to final result display, reducing manual intervention and improving work efficiency. Processed 3D scenes and calculation results can be viewed instantly on mobile terminals, enabling rapid decision-making. This system is particularly suitable for emergency response. The wireless connection achieved through the Wi-Fi module simplifies the equipment deployment process, improves the flexibility of on-site operations, supports the real-time transmission of large amounts of point cloud data, ensures the speed and efficiency of data transmission, provides near-instant result feedback, and ensures a nearly seamless process from data acquisition to display.

[0046] 3. This invention combines GNSS, INS, and laser point cloud technologies to ensure high-precision position information and stable attitude information. In the case of poor or no GNSS signal, the inertial navigation system (INS) can continue to provide stable position and attitude updates, reducing error accumulation. The GNSS positioning algorithm and the strapdown inertial guidance numerical recursive algorithm are combined through the Kalman filter to improve the accuracy of data solution. At the same time, point cloud thinning and denoising processing effectively reduce the amount of unnecessary data and remove noise points, improving the accuracy and speed of subsequent analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 Schematic diagram of the system structure of the present invention;

[0048] Figure 2 A schematic diagram of the handheld laser scanner system of the present invention performing data acquisition;

[0049] Figure 3 Schematic diagram of the real-time position and attitude calculation module of the present invention;

[0050] Figure 4 This is a schematic diagram of processing laser point cloud data according to the present invention;

[0051] Figure 5 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be further described in detail below with reference to the accompanying drawings and specific preferred embodiments.

[0053] In the description of the present invention, it should be understood that the terms "left side," "right side," "upper," "lower," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Terms such as "first" and "second" do not indicate the importance of components and therefore should not be construed as limitations on the present invention. The specific dimensions used in this embodiment are intended only to illustrate the technical solution and do not limit the scope of protection of the present invention.

[0054] like Figure 1 、 Figure 2 、 Figure 3 and Figure 4 As shown in the figure, a real-time measurement device for hidden danger distances in overhead power lines, based on a handheld laser scanner, consists of a handheld laser scanner and a mobile terminal, seamlessly connected via a WiFi module. The handheld laser scanner is the core data acquisition device of the entire system, responsible for high-precision three-dimensional scanning of overhead power lines and their surroundings. Its built-in GNSS receiver, inertial navigation module (INS), and laser transmitter together form a real-time position and attitude solution module, ensuring accurate position, velocity, and attitude information in any environment. The laser scanner can quickly generate large amounts of point cloud data to describe the geometric features of the measured object. As the communication bridge between the handheld laser scanner and the mobile terminal, the WiFi module enables seamless connection between the two, eliminating the need for additional wiring, simplifying the equipment deployment process and increasing the flexibility of field operations. It also supports the efficient transmission of large amounts of data, ensuring a rapid flow from data acquisition to display. The mobile terminal can be a portable electronic device such as a smartphone or tablet, making it easy to carry and operate. The built-in data decoding program is a key component, responsible for decoding the received point cloud data, converting it into a visual 3D scene, and presenting it on the screen. Users can use the built-in selection tool to manually select the point cloud range of wires and hidden dangers in the 3D scene, and then automatically calculate the minimum clearance distance between the two, assisting inspectors in making safety assessments.

[0055] The present invention also discloses a real-time measurement system for the hidden danger distance of an overhead line channel based on a handheld laser scanner, which includes a real-time data acquisition module, a real-time data processing module, a real-time data transmission module, and a data decoding and display module;

[0056] The real-time data acquisition module uses a handheld laser scanner to perform high-precision 3D scanning of overhead power lines and their surroundings, acquiring location information and laser point cloud data for conductors and potential hazards. This module incorporates a built-in GNSS receiver, inertial navigation system (INS), and laser transmitter to ensure accurate position, velocity, and attitude information is acquired in any environment, rapidly generating large amounts of point cloud data to describe the geometric features of the measured objects.

[0057] The real-time data processing module includes a real-time position and attitude solution module, a real-time data fusion module, and a point cloud thinning and denoising module. The real-time position and attitude solution module combines global satellite navigation (GNSS) and inertial navigation (INS) to provide more accurate position and attitude information and reduce error accumulation; even in the case of poor signal or no GNSS signal, INS can continue to provide stable position and attitude updates. The real-time data fusion module effectively fuses data from different sensors (such as GNSS, INS, laser scanners) to eliminate the limitations that may exist in a single data source, such as GNSS signal obstruction problems or INS drift errors over time. The point cloud thinning and denoising module uses voxel grid filtering to thin out point cloud data to reduce the amount of unnecessary data; and uses statistical analysis or density-based filtering methods to remove outliers or erroneous data points to reduce false alarms of noise points during the measurement process;

[0058] The real-time data transmission module, consisting of the scanner WIFI module and the mobile terminal WIFI module, serves as a communication bridge between the handheld laser scanner and the mobile terminal, achieving seamless connection between the two. This eliminates the need for additional wiring, simplifies the equipment deployment process, and improves the flexibility of on-site operations. It also supports the efficient transmission of large amounts of data, ensuring rapid data flow from acquisition to display.

[0059] The data decoding and display module includes real-time point cloud rendering, manual selection, and spatial distance calculation functions. The real-time point cloud rendering function decodes the received point cloud data and converts it into a 3D visualization scene, allowing users to intuitively view and analyze the on-site situation. The manual selection function allows users to manually select the point cloud range of wires and hidden dangers in the 3D scene. The spatial distance calculation function automatically calculates the minimum clearance distance between the selected wire and the hidden danger, assisting inspectors in making safety assessments.

[0060] like Figure 5 As shown, the present invention further discloses a real-time measurement method for the hidden danger distance of an overhead line channel based on a handheld laser scanner, which uses the real-time measurement system for the hidden danger distance of an overhead line channel based on a handheld laser scanner as described in any one of claims 2 to 5 to measure the minimum clearance distance of a hidden danger object or conductor, comprising the following steps:

[0061] Step 1: Use the real-time data acquisition module to collect real-time position data and laser point cloud data;

[0062] Step 2: The real-time data processing module is used to solve the position data and integrate it to obtain the real-time position, speed, and attitude information;

[0063] Step 3: Match the points of the laser point cloud with the real-time positioning data obtained by mobile measurement, and fuse the laser point cloud data with the calculated absolute position and posture information to obtain real-time point cloud data with absolute coordinates;

[0064] Step 4: Perform thinning and denoising on the solved real-time point cloud data;

[0065] Step 5: The thinned and denoised point cloud data is sent to the mobile terminal via the real-time data transmission module. The data decoding and display module of the mobile terminal obtains a 3D scene through decoding and visualization rendering.

[0066] Step 6: On the mobile terminal, you can translate or rotate the real-time point cloud scene, use the selection tool to manually select the wire and potential danger point cloud range, and calculate the minimum clearance distance between the selected wire and the potential danger point cloud.

[0067] The handheld laser scanner system includes a GNSS receiver, an inertial navigation module (INS) and a laser scanner. These components together constitute the positioning and orientation system (POS) to ensure high-precision measurement results. To achieve this goal, the system uses a specific coordinate system definition: the carrier coordinate system is used in the mobile measurement process, with the coordinate origin of the inertial navigation coordinate system as the origin of the carrier coordinate system, which is defined as follows: the X-axis is in the right direction, the Y-axis is in the direction of the carrier's forward movement, and the Z-axis is in the upward direction; the world coordinate system is based on the WGS-84 ellipsoid or CGCS2000 benchmark, and the central meridian is set according to the local longitude for projection (such as Gauss projection or transverse Mercator projection), plus the local elevation system, forming a three-dimensional coordinate system of plane rectangular coordinates plus elevation, which is used to describe absolute position information;

[0068] In terms of data acquisition, the GNSS receiver acquires real-time location information and provides precise geographic coordinates. The inertial navigation module (INS) calculates attitude, velocity, and position updates, maintaining relatively stable position and attitude estimates even in the absence of GNSS signals. The laser scanner generates a large amount of point cloud data, which is used to describe the geometric features of the measured object. During data processing, the system's real-time position, velocity, and other information are quickly obtained through a real-time GNSS positioning algorithm. The INS uses a real-time strapdown inertial navigation numerical increment algorithm, including attitude update algorithms, velocity update algorithms, and position update algorithms. Using a recursive iterative method, it uses the navigation information at the previous moment and the inertial device measurement values at the current moment as input information, and recursively calculates the current moment's attitude, velocity, position, and other navigation information. In the fusion and state estimation stages, the Kalman filter effectively combines the GNSS positioning algorithm and the strapdown inertial navigation numerical recursive algorithm. The Kalman filter is an algorithm that uses linear system state equations and observational data from the system's input and output to optimally estimate the system state. It combines the precise but potentially intermittent position information provided by GNSS with the continuous but time-drifting attitude and position information provided by INS. This allows for online state estimation, determining the state at each moment and ultimately obtaining absolute position and attitude information. Absolute position information is recorded in geodetic coordinates (B, L, H) in the WGS84 coordinate system, where B represents latitude, L represents longitude, and H represents elevation. Attitude information includes three angular parameters: roll, the angle between the vehicle's x-axis and the horizontal, with positive values pointing downward to the right; pitch, the angle between the vehicle's y-axis and the horizontal, with positive values pointing upward; and yaw, the angle between the vehicle's forward direction and true north.

[0069] Match the laser point cloud points with the real-time positioning data, and use a computer to fuse the laser point cloud data with the calculated absolute position and posture information to obtain real-time point cloud data with absolute coordinates. The calculation formula for real-time point cloud data with absolute coordinates is as follows:

[0070]

[0071] Where X b Indicates the original point cloud coordinates in the carrier coordinate system, X e Represents the three-dimensional point cloud coordinates in the world coordinate system, Represents the rotation matrix from the carrier coordinate system to the world coordinate system, Represents the position vector of the origin of the carrier coordinate system in the world coordinate system; rotation matrix The calculation formula is as follows:

[0072]

[0073] The scanner's built-in processor first performs thinning and denoising on the calculated point cloud data. Voxel grid filtering is typically used to reduce the data volume, speeding up calculations and reducing data transmission latency while preserving the point cloud's shape and structural details. Denoising is then performed, using statistical analysis or density-based filtering to remove outliers or erroneous data points, reducing false positives during measurement.

[0074] Real-time point cloud data transmission is achieved through the built-in Wi-Fi module of the scanner. The mobile terminal receives the point cloud data transmitted by the scanner via Wi-Fi. At the same time, the APP on the mobile terminal decodes and renders the data to obtain a visual three-dimensional point cloud scene.

[0075] Achieving these capabilities requires an integrated spatial index suitable for online visualization of cloud scenes on mobile endpoints. This index first utilizes an improved KD-tree, which takes into account the network bandwidth and computational rendering performance characteristics of mobile terminals, to achieve balanced partitioning and encoding of point cloud data. This index then constructs a Level of Dimension (LOD) model for the point cloud data and manages its organization using an improved octree. Finally, the improved octree is linked through the improved KD-tree encoding to form an optimized index structure of (1 primary tree: 1 secondary tree). This index supports LOD-based point cloud scene rendering strategies on mobile devices, enables the determination of spatial relationships in point cloud data at the data block level, and supports multi-threaded data querying.

[0076] The app allows users to manually select any two targets, with P1 representing the wire location and P2 representing the potential danger location. The system then calculates the minimum clearance distance between the targets by calculating the Euclidean distance or point-to-surface distance. The measurement results are instantly fed back for on-site personnel's reference.

[0077] Euclidean distance:

[0078]

[0079] The spatial coordinates of P1 are (x1 y1 z1), the spatial coordinates of P2 are (x2 y2 z2), and d is the spatial distance between P1 and P2.

[0080] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all fall within the scope of protection of the present invention.

Claims

1. A real-time measurement device for the distance to hidden dangers in overhead line channels based on a handheld laser scanner, characterized by: The system includes a handheld laser scanner and a mobile terminal. The handheld laser scanner is connected to the mobile terminal via a Wi-Fi module. The mobile terminal is provided with a data decoding program. The data decoding program decodes the data measured by the laser scanner, converts the decoded data into a three-dimensional scene, and presents it on the screen of the mobile terminal. The point cloud range of the wire and the hidden danger is selected through the built-in selection tool of the data decoding program. The data decoding program automatically calculates the minimum clearance distance between the selected wire and the hidden danger.

2. A real-time measurement system for the distance to hidden dangers in overhead line channels based on a handheld laser scanner, characterized by: Using the real-time measurement device for hidden danger distances of overhead line channels based on a handheld laser scanner as described in claim 1 as a carrier, the system includes a real-time data acquisition module, a real-time data processing module, a real-time data transmission module, and a data decoding and display module; the real-time data acquisition module measures the position information of the conductor and the hidden danger object and the laser point cloud information through the handheld laser scanner and transmits them to the real-time data processing module, the real-time data processing module transmits the processed data to the data decoding and display module through the real-time data transmission module, and the data decoding and display module in the mobile terminal decodes the data and presents it on the display screen.

3. The real-time measurement system for overhead line channel hidden danger distance based on a handheld laser scanner according to claim 2 is characterized by: The real-time data processing module includes a real-time position and attitude solution module, a real-time data fusion module, and a point cloud thinning and denoising module. The data of the real-time data acquisition module is transmitted to the real-time position and attitude solution module through global satellite navigation and inertial navigation to collect the position information of the wire and the hidden danger object, and laser point cloud data is obtained by laser scanning the wire and the hidden danger object and transmitted to the real-time data fusion module. The data processed by the real-time position and attitude solution module and the real-time data fusion module are imported into the point cloud thinning and denoising module for processing.

4. The real-time measurement device for hidden danger distance of overhead line channels based on a handheld laser scanner according to claim 3 is characterized by: The real-time data transmission module includes a scanner WIFI module and a mobile terminal WIFI module. The scanner WIFI module and the mobile terminal WIFI module are matched and connected. The data processed by the real-time data processing module is transmitted to the mobile terminal WIFI module through the scanner WIFI module.

5. The real-time measurement system for overhead line channel hidden danger distance based on a handheld laser scanner according to claim 4 is characterized in that: The data decoding and display module includes real-time point cloud rendering function, manual selection function and spatial distance calculation function; the data received by the mobile WIFI module is rendered on the display screen of the mobile terminal through the real-time point cloud rendering function, and the target area is selected through the manual selection function, and the spatial distance calculation function automatically realizes the minimum clearance distance calculation of the target area.

6. A real-time measurement method for the distance to hidden dangers in overhead line channels based on a handheld laser scanner, characterized by: The method of calculating the minimum clearance distance of a hidden danger object or a conductor by using the real-time measurement system for hidden danger distance of an overhead line channel based on a handheld laser scanner as described in any one of claims 2 to 5 comprises the following steps: Step 1: Use the real-time data acquisition module to collect real-time position data and laser point cloud data; Step 2: The real-time data processing module is used to solve the position data and integrate it to obtain the real-time position, speed, and attitude information; Step 3: Match the points of the laser point cloud with the real-time positioning data obtained by mobile measurement, and fuse the laser point cloud data with the calculated absolute position and posture information to obtain real-time point cloud data with absolute coordinates; Step 4: Perform thinning and denoising on the solved real-time point cloud data; Step 5: The thinned and denoised point cloud data is sent to the mobile terminal via the real-time data transmission module. The data decoding and display module of the mobile terminal obtains a three-dimensional scene through decoding and visualization rendering. Step 6: On the mobile terminal, you can translate or rotate the real-time point cloud scene, use the selection tool to manually select the wire and potential danger point cloud range, and calculate the minimum clearance distance between the selected wire and the potential danger point cloud.

7. The method for real-time measurement of hidden danger distances in overhead line channels based on a handheld laser scanner according to claim 6, characterized in that: In step 1, a GNSS receiver, an inertial navigation module and a laser transmitter are provided in the handheld laser scanner. The GNSS receiver, the inertial navigation module and the laser transmitter form a real-time position and attitude solution module. The mobile measurement process adopts a carrier coordinate system, with the origin of the inertial navigation coordinate system as the origin of the carrier coordinate system, the forward direction of the carrier as the positive direction of the Y axis, the right as the positive direction of the X axis, and the upward direction as the positive direction of the Z axis. Real-time GNSS data, INS data and laser point cloud data are collected by the GNSS receiver, the inertial navigation device and the laser transmitter.

8. The method for real-time measurement of hidden danger distances in overhead line channels based on a handheld laser scanner according to claim 7, characterized in that: In steps 2 and 3, real-time position information is obtained according to the GNSS receiver; the INS data of the inertial navigation module is solved to obtain attitude update information, velocity update information and position update information; real-time state estimation is performed based on the GNSS data, and the absolute position and attitude information are calculated. The GNSS positioning algorithm and the strapdown inertial guidance numerical recursive algorithm are combined through the Kalman filter, and the position and other change information output by the two are matched. The state estimation is performed online to obtain the state at each moment, and the absolute position and attitude information are obtained. The absolute position information recording system is in the geodetic coordinates (B, L, H) under the WGS84 coordinate system, where the attitude angle information includes: roll angle, pitch angle and yaw angle, where the roll angle is the angle between the x-axis of the carrier and the horizontal direction, and the right side of the carrier is positive downward; the pitch angle is the angle between the y-axis of the carrier and the horizontal direction, and the carrier is positive upward; the yaw angle is the angle between the forward direction of the carrier and the true north direction; Match the points of the laser point cloud with the obtained real-time positioning data, and fuse the laser point cloud data with the calculated absolute position and posture information through the real-time data fusion module to obtain real-time point cloud data with absolute coordinates. The calculation formula for real-time point cloud data with absolute coordinates is as follows: Among them, X b Indicates the original point cloud coordinates in the carrier coordinate system, X e Represents the three-dimensional point cloud coordinates in the world coordinate system, Represents the rotation matrix from the carrier coordinate system to the world coordinate system, Represents the position vector of the origin of the carrier coordinate system in the world coordinate system; Rotation Matrix The calculation formula is as follows: Among them, yaw represents the yaw angle, roll represents the roll angle, and pitch represents the pitch angle.

9. The method for real-time measurement of hidden danger distances in overhead line channels based on a handheld laser scanner according to claim 6, characterized in that: In step 4, the solved point cloud data is thinned and denoised through the point cloud thinning and denoising module. The voxel grid filtering method is used in the point cloud thinning and denoising module to thin out the point cloud data of the wires or hidden dangers. When performing denoising, statistical analysis or density-based filtering methods are used to remove outliers or erroneous data points to reduce the false alarm of noise points during the measurement process.

10. The method for real-time measurement of hidden danger distances in overhead line channels based on a handheld laser scanner according to claim 6, characterized in that: In steps 5 and 6, real-time point cloud data transmission is achieved through the scanner WIFI module. The mobile terminal receives point cloud data through the mobile terminal WIFI module. At the same time, the data decoding and display module of the mobile terminal decodes and renders the data to obtain a visualized 3D point cloud scene. The wire or hidden danger is manually selected as the target area through the selection tool. The data decoding and display module calculates the Euclidean distance or point-to-surface distance to achieve the minimum clearance distance measurement between the target objects. The Euclidean distance is: The spatial coordinates of P1 are ( x1 y1 z 1) , the spatial coordinates of P2 are ( x2 y2 z 2) , d is the spatial distance between P1 and P2, where P1 is the position of the wire selected by the box, and P2 is the position of the hidden danger selected by the box.

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