Communication cable bridge number metering method and device based on tunnel point cloud, medium and equipment

Abstract

The invention discloses a communication cable bridge number metering method and device based on tunnel point cloud, a medium and equipment. The method comprises the following steps: acquiring tunnel point cloud data; obtaining a tunnel wall point cloud and a plane equation of the tunnel wall point cloud according to the tunnel point cloud data; acquiring communication cable bridge point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; and performing clustering analysis on the point cloud data of the communication cable bridges, counting the total number of categories, and generating the number of the communication cable bridges. According to the method, high-robustness automatic identification and metering of the communication cable bridge are realized in a complex environment, noise and shielding are effectively overcome, and auditing precision and efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of point cloud analysis technology, and in particular to a method, device, medium and equipment for measuring the number of communication cable bridges based on tunnel point clouds. Background Art

[0002] In tunnel construction, the construction audit of communication cable bridges is an important part of ensuring project quality and cost control. The traditional method of measuring the number of bridges mainly relies on manual measurement and drawing verification, which is not only inefficient but also susceptible to human errors. Especially in complex tunnel environments, due to factors such as small space and insufficient light, the accuracy of manual measurement is difficult to guarantee, resulting in large deviations in audit results. In addition, traditional methods are difficult to update the construction progress in real time, and cannot meet the requirements of modern engineering management for data real-time and accuracy, which seriously affects the efficiency and reliability of construction audits.

[0003] With the continuous expansion of tunnel engineering scale and the continuous advancement of construction technology, the traditional method of measuring the number of bridges can no longer meet the needs of modern engineering audits. The existing technology lacks effective use of tunnel point cloud data and cannot realize automated and intelligent measurement of bridge quantity. Although point cloud data can provide high-precision three-dimensional spatial information, its application in bridge construction audits is limited due to complex data processing and immature algorithms. In addition, the existing methods lack real-time monitoring of the installation status of the bridge during construction, and cannot promptly detect and correct problems in construction, which increases the difficulty and risk of audits. Therefore, developing a method for measuring the number of communication cable bridges based on tunnel point clouds is of great significance for improving the efficiency and accuracy of construction audits. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method, device, medium and equipment for measuring the number of communication cable trays based on tunnel point cloud. To achieve the above purpose, the present invention is implemented by adopting the following technical solutions: In a first aspect, the present invention provides a method for measuring the number of communication cable trays based on tunnel point cloud, comprising: Obtain tunnel point cloud data; According to the tunnel point cloud data, obtaining a tunnel wall point cloud and a plane equation of the tunnel wall point cloud; Acquire communication cable tray point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; The communication cable tray point cloud data is clustered and analyzed, the total number of categories is counted, and the number of communication cable trays is generated.

[0005] In combination with the first aspect, optionally, acquiring a tunnel wall point cloud and a plane equation of the tunnel wall point cloud according to the tunnel point cloud data includes: Performing plane fitting on the tunnel point cloud data to obtain a plane equation of the tunnel ground point cloud; According to a preset height range, intercepting point cloud data that is within the preset height range from the plane equation of the tunnel ground point cloud, and determining the tunnel wall point cloud to be clustered; Clustering the tunnel wall point clouds to be clustered according to density clustering, and determining the point cloud data corresponding to the category with the largest number of point clouds after clustering as the tunnel wall point cloud; Perform plane fitting on the tunnel wall point cloud to obtain the plane equation of the tunnel wall point cloud.

[0006] In combination with the first aspect, optionally, performing plane fitting on the tunnel point cloud data to obtain a plane equation of the tunnel ground point cloud includes: Using radius filtering to filter the tunnel point cloud data to obtain a filtered point cloud; A random sampling consistency method is used to perform plane fitting on the filtered point cloud to obtain a plane equation of the tunnel ground point cloud.

[0007] In combination with the first aspect, optionally, acquiring the communication cable tray point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud includes: According to the plane equation of the tunnel wall point cloud, obtaining the normal direction of the tunnel wall plane; According to a preset length value, intercepting point cloud data of the tunnel wall point cloud that is away from the plane equation of the tunnel wall by the preset length value, and determining it as the bridge end point cloud data; Clustering the bridge endpoint point cloud data and calculating the center coordinates of each category; According to the center coordinates of each category, the normal direction of the tunnel wall plane and the tunnel wall point cloud, the bridge point cloud corresponding to each category is obtained to form the communication cable bridge point cloud data.

[0008] In combination with the first aspect, optionally, obtaining the bridge point cloud corresponding to each category according to the center coordinates of each category, the normal direction of the tunnel wall plane and the tunnel wall point cloud to form the communication cable bridge point cloud data includes: Determine the straight line equation corresponding to each category according to the center coordinates of each category and the normal direction of the tunnel wall plane; Calculating the distance between the tunnel wall point cloud and the straight line equation corresponding to each category; If the distance is less than a preset distance, the point cloud is determined as a bridge point cloud corresponding to each category; The bridge point clouds corresponding to all categories are superimposed to form the communication cable bridge point cloud data.

[0009] In a second aspect, the present invention provides a communication cable tray quantity metering device based on tunnel point cloud, comprising: Point cloud acquisition module: obtain tunnel point cloud data; Tunnel wall point cloud analysis module: obtaining the tunnel wall point cloud and the plane equation of the tunnel wall point cloud according to the tunnel point cloud data; Bridge point cloud acquisition module: acquires communication cable bridge point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; Quantity measurement module: cluster analysis is performed on the communication cable tray point cloud data, the total number of categories is counted, and the quantity of the communication cable tray is generated.

[0010] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for measuring the number of communication cable trays based on tunnel point cloud as described in any one of the first aspects.

[0011] In a fourth aspect, the present invention provides a communication cable tray quantity metering device based on tunnel point cloud, comprising: A memory for storing instructions; A processor is used to execute the instructions so that the device performs operations to implement the method for measuring the number of communication cable trays based on tunnel point cloud as described in any one of the first aspects.

[0012] Compared with the prior art, the beneficial effects achieved by the method, device, medium and equipment for measuring the number of communication cable trays based on tunnel point cloud provided by the embodiments of the present invention include: The present invention obtains tunnel point cloud data; obtains tunnel wall point cloud and the plane equation of the tunnel wall point cloud according to the tunnel point cloud data; obtains communication cable bridge point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; clusters the communication cable bridge point cloud data, counts the total number of categories, and generates the number of communication cable bridges. The present invention realizes highly robust automatic identification and measurement of communication cable bridges in complex environments, effectively overcomes noise and occlusion, and improves audit accuracy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A flowchart of a method for measuring the number of communication cable trays based on tunnel point cloud is provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0014] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of this embodiment can be combined with each other. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. 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.

[0015] Embodiment 1: Figure 1 As shown, an embodiment of the present invention provides a method for measuring the number of communication cable trays based on tunnel point cloud, including: S1: Obtain tunnel point cloud data; Specifically, for the acquisition of tunnel point cloud data, laser radar scanning can be used. It determines the distance of the target object by emitting a laser beam and measuring the time of reflected light, thereby obtaining three-dimensional spatial information. In the tunnel environment, the laser radar can be mounted on a vehicle or mobile platform and quickly scanned along the tunnel. It can efficiently and accurately collect large-area tunnel point cloud data, and is less affected by light conditions and can adapt to complex and dark tunnel environments. It can also be reconstructed through structured light three-dimensional reconstruction. This method uses a projector to project a specific pattern onto the tunnel surface, and the camera shoots synchronously from different angles. Based on the principle of triangulation, the three-dimensional coordinates of each point on the surface of the object are calculated by analyzing the deformation of the pattern at different viewing angles, and then a point cloud is generated. This method has high accuracy and good scanning effect on small tunnels or local details, but the measurement range is relatively limited and has certain requirements for ambient light.

[0016] S2: acquiring a tunnel wall point cloud and a plane equation of the tunnel wall point cloud according to the tunnel point cloud data; In a specific embodiment, the step of obtaining a tunnel wall point cloud and a plane equation of the tunnel wall point cloud according to the tunnel point cloud data includes: S2-1: performing plane fitting on the tunnel point cloud data to obtain a plane equation of the tunnel ground point cloud; In a specific embodiment, performing plane fitting on the tunnel point cloud data to obtain the plane equation of the tunnel ground point cloud includes: S2-1-1: Filter the tunnel point cloud data using radius filtering to obtain a filtered point cloud; S2-1-2: Use the random sampling consistency method to perform plane fitting on the filtered point cloud to obtain the plane equation of the tunnel ground point cloud.

[0017] Specifically, the radius filter function remove_radius_outlier function in the open3D development library is used to perform the radius filtering operation. Its input is the filtering radius and the minimum number of neighborhood points. It returns the filtered point cloud index ind and a Boolean value cl (indicating whether the filtering is successful). Then, the filtered point cloud is extracted according to the index through the select_by_index function. The setting of the radius is based on the average density value of the point cloud. The radius is set to 10 times the average density value, and the minimum number of neighborhood points is set to 10. After the filtering is completed, the segment_plane function in the open3D development library is used for plane fitting. This function uses a random sampling consistency algorithm to fit the plane. The core idea of ​​the algorithm is to randomly sample a point set, assume it is the inner point of the plane model, and then calculate the plane model parameters. Repeat this process many times, and select the plane model with the most inner points as the final fitting result. In the point cloud data, the plane fitting function can identify the point set with plane features and determine its plane equation, which is generally expressed as Ax+By+Cz+D=0, where A, B, C, and D are plane parameters.

[0018] S2-2: According to a preset height range, intercept point cloud data that is within the preset height range from the plane equation of the tunnel ground point cloud to determine the tunnel wall point cloud to be clustered; Specifically, assume that the parameters A, B, C, and D of the plane equation are known. Convert the point cloud coordinates into homogeneous coordinate form and construct the points_homogeneous matrix. Then, through a matrix dot multiplication operation, use the np.dot function to calculate the signed distance from all points to the plane, and then use np.abs to take the absolute value to obtain the true distance value. At the same time, use np.linalg.norm to calculate the modulus of the plane normal vector to complete the calculation of the distance formula. In this way, with the help of the vectorization characteristics of matrix operations, the distance from all point cloud points to the specified plane can be efficiently calculated at one time, which greatly improves the calculation efficiency compared to the traditional loop calculation method. After obtaining the distance between the point cloud and the plane, according to the preset height range, 1.5 meters to 2.5 meters is taken in general engineering, and the np.where condition is used to filter out the point cloud within the preset height range and determine it as the tunnel wall point cloud to be clustered.

[0019] S2-3: clustering the tunnel wall point clouds to be clustered according to density clustering, and determining the point cloud data corresponding to the category with the largest number of point clouds after clustering as the tunnel wall point cloud; Specifically, the DBSCAN density clustering algorithm is used to cluster the point cloud. DBSCAN is a density-based spatial clustering algorithm. Its core idea is to divide the data space into high-density areas and low-density areas. The points in the high-density area are divided into different clusters, while the points in the low-density area are regarded as noise points. In the point cloud data, the algorithm implements clustering by defining two key parameters: the neighborhood radius (eps) and the minimum number of points in the neighborhood (min_points). For each point, the algorithm checks the number of its neighborhood points within the radius eps. If the number of neighborhood points is greater than or equal to min_points, the point is regarded as a core point, starting with the core point and continuously expanding to form a cluster. If the number of neighborhood points of a point is less than min_points and the point is not a directly or indirectly density-reachable point of the core point, the point is marked as a noise point. In the actual process, the cluster_dbscan function in the open3D development library is used to perform the DBSCAN clustering operation and return the cluster label to which each point belongs. The number of clusters can be obtained by analyzing the labels, and different colors can be assigned to the point clouds of different clusters for visualization according to the labels.

[0020] S2-4: Perform plane fitting on the tunnel wall point cloud to obtain the plane equation of the tunnel wall point cloud.

[0021] S3: Acquire communication cable tray point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; In a specific embodiment, the step of acquiring the communication cable tray point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud includes: S3-1: Obtaining the normal direction of the tunnel wall plane according to the plane equation of the tunnel wall point cloud; Specifically, the plane equation is expressed in a general expression, which is represented by Ax+By+Cz+D=0, where A, B, C, and D are plane parameters, and the vector (A, B, C) can be expressed as the normal direction of the tunnel wall plane.

[0022] S3-2: According to a preset length value, intercept the point cloud data of the tunnel wall point cloud that is away from the plane equation of the tunnel wall by the preset length value, and determine it as the bridge end point cloud data; Specifically, in actual engineering, the length of the bridge is generally between 20 cm and 40 cm, so for determining the preset length value, an adaptive method is adopted. With 40 cm as the preset length, the point cloud data in the tunnel wall point cloud that is 40 cm away from the plane equation of the tunnel wall is intercepted. If the number of point clouds is less than 1000, the preset length is reduced by 1, and the point cloud is intercepted according to the new preset length until the number of intercepted point clouds is greater than 1000.

[0023] S3-3: clustering the bridge endpoint point cloud data and calculating the center coordinates of each category; Specifically, after clustering is completed, for each category, the method for calculating the center coordinates is as follows: the x-coordinate values ​​of all point clouds in the category are accumulated and summed, and then divided by the number of point clouds in the category to obtain the center coordinate value of the category in the x-axis direction; similarly, the same operation is performed on the y-coordinate and z-coordinate to calculate the center coordinate values ​​in the y-axis and z-axis directions respectively. The coordinate values ​​in these three directions are combined to determine the center coordinates of the point cloud data of this category.

[0024] S3-4: According to the center coordinates of each category, the normal direction of the tunnel wall plane and the tunnel wall point cloud, the bridge point cloud corresponding to each category is obtained to form the communication cable bridge point cloud data.

[0025] Specifically, assuming that the center coordinates of a category are (x0, y0, z0), and the normal direction of the tunnel wall plane is (A, B, C), then the straight line passing through the point (x0, y0, z0) and with the direction (A, B, C) is expressed as A*(x-x0)+B*(y-y0)+C*(z-z0)=0. Calculate the distance between the tunnel wall point cloud and the straight line, and take the point cloud with a distance less than 0.05 meters as the bridge point cloud corresponding to this category.

[0026] S4: Perform cluster analysis on the communication cable tray point cloud data, count the total number of categories, and generate the number of communication cable trays.

[0027] The communication cable tray quantity measurement method based on tunnel point cloud provided by the present invention realizes highly robust automatic identification and measurement of communication cable trays in complex environments, effectively overcomes noise and occlusion, and improves audit accuracy and efficiency.

[0028] Embodiment 2: The embodiment of the present invention provides a communication cable tray quantity metering device based on tunnel point cloud, comprising: Point cloud acquisition module: acquires the point cloud data of the tunnel and the point cloud data at one end point of the communication leaky cable to be segmented; Sub-tunnel segmentation module: segmenting the tunnel point cloud data into a plurality of sub-tunnel point cloud data according to a preset distance; Direction vector acquisition module: obtains the tunnel ground plane equation and tunnel direction vector of each sub-tunnel point cloud data; Leaky cable point cloud segmentation module: segment the communication leaky cable point cloud data from the tunnel point cloud data according to the tunnel direction vector and the point cloud data at one end point of the communication leaky cable to be segmented.

[0029] The communication cable tray quantity metering device based on tunnel point cloud provided by the present invention can realize automatic identification and metering of communication cable trays with high robustness in complex environments, effectively overcome noise and occlusion, and improve audit accuracy and efficiency.

[0030] Embodiment 3: The embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a method for measuring the number of communication cable trays based on tunnel point cloud as described in Embodiment 1 is implemented.

[0031] Embodiment 4: The embodiment of the present invention provides a communication cable tray quantity metering device based on tunnel point cloud, including: A memory for storing instructions; A processor is used to execute the instructions so that the device performs operations to implement the method for measuring the number of communication cable trays based on tunnel point cloud as described in any one of the first embodiments.

[0032] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0033] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0034] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0035] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0036] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for measuring the number of communication cable trays based on tunnel point cloud, characterized in that: include: Obtain tunnel point cloud data; According to the tunnel point cloud data, obtaining a tunnel wall point cloud and a plane equation of the tunnel wall point cloud; Acquire communication cable tray point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; The communication cable tray point cloud data is clustered and analyzed, the total number of categories is counted, and the number of communication cable trays is generated.

2. According to the method for measuring the number of communication cable trays based on tunnel point cloud according to claim 1, it is characterized in that: The step of obtaining a tunnel wall point cloud and a plane equation of the tunnel wall point cloud according to the tunnel point cloud data comprises: Performing plane fitting on the tunnel point cloud data to obtain a plane equation of the tunnel ground point cloud; According to a preset height range, intercepting point cloud data that is within the preset height range from the plane equation of the tunnel ground point cloud, and determining the tunnel wall point cloud to be clustered; Clustering the tunnel wall point clouds to be clustered according to density clustering, and determining the point cloud data corresponding to the category with the largest number of point clouds after clustering as the tunnel wall point cloud; Perform plane fitting on the tunnel wall point cloud to obtain the plane equation of the tunnel wall point cloud.

3. According to the method for measuring the number of communication cable trays based on tunnel point cloud in claim 2, it is characterized in that: The performing plane fitting on the tunnel point cloud data to obtain the plane equation of the tunnel ground point cloud includes: Using radius filtering to filter the tunnel point cloud data to obtain a filtered point cloud; A random sampling consistency method is used to perform plane fitting on the filtered point cloud to obtain a plane equation of the tunnel ground point cloud.

4. According to a method for measuring the number of communication cable trays based on tunnel point cloud according to claim 1, it is characterized in that: The step of acquiring communication cable bridge point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud comprises: According to the plane equation of the tunnel wall point cloud, obtaining the normal direction of the tunnel wall plane; According to a preset length value, intercepting point cloud data of the tunnel wall point cloud that is away from the plane equation of the tunnel wall by the preset length value, and determining it as the bridge end point cloud data; Clustering the bridge endpoint point cloud data and calculating the center coordinates of each category; According to the center coordinates of each category, the normal direction of the tunnel wall plane and the tunnel wall point cloud, the bridge point cloud corresponding to each category is obtained to form the communication cable bridge point cloud data.

5. A method for measuring the number of communication cable trays based on tunnel point cloud according to claim 4, characterized in that: The method of obtaining the bridge point cloud corresponding to each category according to the center coordinates of each category, the normal direction of the tunnel wall plane and the tunnel wall point cloud to form the communication cable bridge point cloud data includes: Determining a straight line equation corresponding to each category according to the center coordinates of each category and the normal direction of the tunnel wall plane; Calculating the distance between the tunnel wall point cloud and the straight line equation corresponding to each category; If the distance is less than a preset distance, the point cloud is determined as a bridge point cloud corresponding to each category; The bridge point clouds corresponding to all categories are superimposed to form the communication cable bridge point cloud data.

6. A communication cable tray quantity metering device based on tunnel point cloud, characterized in that: include: Point cloud acquisition module: obtain tunnel point cloud data; Tunnel wall point cloud analysis module: obtaining the tunnel wall point cloud and the plane equation of the tunnel wall point cloud according to the tunnel point cloud data; Bridge point cloud acquisition module: acquires communication cable bridge point cloud data according to the tunnel wall point cloud and the plane equation of the tunnel wall point cloud; Quantity measurement module: cluster analysis is performed on the communication cable tray point cloud data, the total number of categories is counted, and the quantity of the communication cable tray is generated.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the method for measuring the number of communication cable trays based on tunnel point cloud as described in any one of claims 1-5.

8. A communication cable tray quantity measurement device based on tunnel point cloud, characterized in that: include: A memory for storing instructions; A processor is used to execute the instructions so that the device performs operations to implement the method for measuring the number of communication cable trays based on tunnel point cloud as described in any one of claims 1 to 5.

Images