A deflection non-contact detection method applied to a round steel pipe rod of a net rack structure

Abstract

The application discloses a kind of deflection non-contact detection methods applied to net rack structure round steel pipe member, and the application relates to steel pipe pole rack technical field.The method steps include: obtaining net rack structure point cloud data by laser scanner, and high-density voxel is obtained by voxel division and density analysis screening;High-density voxel is fitted to spherical surface, and spatial spherical anchor point is extracted according to spherical surface fitting difference value;Net rack space candidate connection matrix is constructed based on spatial spherical anchor point, and linear point cloud paragraph is screened, and least square method fitting member axis based on RANSAC algorithm;With spatial spherical anchor point line as member theoretical axis, deflection degree value and deflection offset vector are calculated by offset analysis with fitted axis;When deflection degree value exceeds preset threshold, mark abnormal member, and construct net rack local subgraph with it as center;The deflection direction consistency index and deflection degree consistency index in subgraph are calculated, and the local risk comprehensive index is calculated by combining the two, and risk grade is divided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel pipe pole frame, in particular to a deflection non-contact detection method applied to a round steel pipe pole of a net rack structure. BACKGROUND

[0002] In the fields of buildings, bridges, industrial plants, etc., the net rack structure is widely used due to its light weight, large span, reasonable stress and other advantages. The round steel pipe pole, as the core load-bearing component of the net rack structure, its deflection deformation is directly related to the overall safety and stability of the structure. During long-term use, the round steel pipe pole is prone to abnormal deflection due to factors such as load change, material aging, environmental erosion, etc. If not detected and evaluated in time, it may cause local structure failure or even overall collapse. Therefore, accurate and efficient detection of the deflection is a key link to ensure the safe operation of the net rack structure.

[0003] In the prior art, the non-contact detection of the deflection of the round steel pipe pole generally adopts single-point deformation measurement based on single-station laser scanning. A laser scanner is arranged at a fixed position, a plurality of key points of a single round steel pipe pole are selected, three-dimensional coordinates of the key points are obtained by scanning, and the deflection value is calculated by comparing the initial design coordinates or historical scanning data.

[0004] However, the single-point deformation measurement based on single-station laser scanning avoids direct contact interference with the round steel pipe pole, but only focuses on the calculation of the deflection value of a single pole, lacks collaborative analysis of the deformation direction and degree of abnormal poles and surrounding poles, and thus it is difficult to accurately assess the risk from the overall perspective of the local structure. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a deflection non-contact detection method applied to a round steel pipe pole of a net rack structure to solve the problems in the background art.

[0006] To achieve the above purpose, the present application is implemented by the following technical scheme: a deflection non-contact detection method applied to a round steel pipe pole of a net rack structure, comprising the following steps:

[0007] Step S1: scanning the net rack structure of the round steel pipe pole by a laser scanner to obtain net rack structure point cloud data; performing voxel division on the net rack structure point cloud data to obtain a net rack structure voxel; performing density analysis on the net rack structure voxel to obtain a high-density voxel; performing spherical surface fitting on the high-density voxel and calculating a spherical surface fitting difference value; screening the high-density voxel according to the spherical surface fitting difference value to obtain a spatial spherical anchor point;

[0008] Step S2: based on the spatial spherical anchor point, a space truss spatial candidate connection matrix is constructed; through rod screening on the space truss spatial candidate connection matrix, a straight line point cloud paragraph is obtained; through axis fitting on the straight line point cloud paragraph based on the least square method of RANSAC algorithm, a rod fitting axis is obtained;

[0009] Step S3: the connecting line of the geometric center of the spatial spherical anchor point is taken as a rod theoretical axis, and the deflection degree value and deflection offset vector are calculated through offset analysis on the rod theoretical axis and the rod fitting axis;

[0010] Step S4: by comparing the deflection degree value of the round steel pipe rod with the preset threshold value, if it is greater than the preset threshold value, it is marked as an abnormal rod; based on the abnormal rod, a space truss local subgraph is constructed; the deflection direction consistency index is obtained by calculating the cosine similarity of the deflection offset vector in the space truss local subgraph; the deflection degree consistency index is calculated through the synergy analysis of the deflection degree value in the space truss local subgraph;

[0011] Step S5: by combining the deflection direction consistency index and the deflection degree consistency index, the local risk comprehensive index is calculated, and the risk level is divided according to the local risk comprehensive index, so as to realize the non-contact detection of the round steel pipe rod.

[0012] Preferably, the space truss structure of the round steel pipe rod is scanned by the laser scanner to obtain space truss structure point cloud data, including the following specific steps:

[0013] The entire space truss structure is divided into several layers along the vertical direction, each layer is taken as an independent scanning unit, and each layer is divided into several sectors according to the distribution direction of the round steel pipe rod in each layer; the laser scanner is installed in the accessible area of each sector in each layer in the vertical direction; in each sector, the laser scanner is used for multi-angle scanning, and finally the space truss structure point cloud data is obtained.

[0014] Preferably, the space truss structure point cloud data is divided into voxels to obtain space truss structure voxels, and the high-density voxels are obtained by density analysis on the space truss structure voxels, including the following steps:

[0015] Based on the space truss structure point cloud data, the entire space is uniformly meshed according to the preset voxel size to form three-dimensional space truss structure voxels, each space truss structure voxel is taken as a basic space unit, and the number of point clouds contained in the space truss structure voxel is recorded;

[0016] The point cloud density in each space truss structure voxel is calculated:

[0017]

[0018] wherein MD is a point cloud density in a lattice structure voxel, is a number of point clouds in a voxel, is a volume of a voxel;

[0019] The lattice structure voxel with the point cloud density greater than the preset density threshold is marked as a high-density voxel.

[0020] Preferably, the calculating the spherical fitting difference value by spherical fitting on the high-density voxel includes the following steps:

[0021] spherical fitting on the high-density voxel by a least square method to obtain a fitting sphere center of the mth high-density voxel and a fitting sphere radius of the mth high-density voxel;

[0022] calculating a root mean square error of the fitting sphere of the mth high-density voxel:

[0023]

[0024] wherein, is the root mean square error of the mth high-density voxel, is a number of point cloud points in the mth high-density voxel, is the ith point cloud point in the mth high-density voxel, is the fitting sphere center of the mth high-density voxel, , is the fitting radius of the mth high-density voxel;

[0025] calculating a normal vector consistency of the fitting sphere of the mth high-density voxel:

[0026]

[0027] wherein, is the normal vector consistency of the mth high-density voxel, std() is a standard deviation function, is the ith point cloud point in the mth high-density voxel, is the fitting sphere center of the mth high-density voxel, , is a set of point cloud points in the mth high-density voxel;

[0028] calculating the spherical fitting difference value by combining the root mean square error and the normal vector consistency:

[0029]

[0030] wherein, is the spherical fitting difference value of the mth high-density voxel, ​the root mean square error of the mth high-density voxel, the normal vector consistency of the mth high-density voxel, the root mean square error threshold, the normal vector consistency threshold, and the adjustment coefficient of the root mean square error and the normal vector consistency, respectively, + =1.

[0031] Preferably, the screening of the high-density voxels according to the spherical fitting difference value to obtain the spatial spherical anchor point comprises the following steps:

[0032] According to the spherical fitting difference value, the high-density voxels with a spherical fitting difference value less than 1 are screened as spatial spherical anchor points.

[0033] Preferably, the construction of the space candidate connection matrix of the space truss based on the spatial spherical anchor point comprises the following specific steps:

[0034] The spherical center coordinates of the i th spatial spherical anchor point are taken as the coordinates of the spatial spherical anchor point =( , , );

[0035] Based on the spatial spherical anchor point, the space candidate connection matrix of the space truss is constructed:

[0036]

[0037] wherein, the minimum length of the circular steel pipe member is 0.5 m by default, the maximum length of the circular steel pipe member is 10 m by default, the coordinates of the i th spatial spherical anchor point, the coordinates of the j th spatial spherical anchor point.

[0038] Preferably, the straight line point cloud segment is obtained by performing member screening on the space candidate connection matrix of the space truss, which comprises the following specific steps:

[0039] In the space candidate connection matrix of the space truss, the two spatial spherical anchor points corresponding to =1 and , the central axis of the two spatial spherical anchor points is calculated , and the direction vector of the central axis is =( - , - , - ), length is ; as the center, expand radius in the direction perpendicular to the direction vector , form a cylindrical search area;

[0040] For K point cloud points in the cylindrical search area, the number of points in the neighborhood of the kth point cloud point neighborhood radius , then the local density of the kth point cloud point in the cylindrical search area is: = , and the gradient vector of the point cloud point is calculated by the neighborhood density difference fitting method , the gradient vector of the point cloud point and the direction vector of the central axis The angle between the direction vector ranges from , then the point is retained, and the angle range is not in , otherwise the point is rejected;

[0041] For the retained point , calculate the radial distance of the retained point to the central axis ; calculate the average value and standard deviation of the radial distance of all retained points, , then the radial distribution of the cylindrical search area is uniform;

[0042] Project all retained points onto a plane perpendicular to the central axis , get the corresponding two-dimensional points, and fit the circle equation of all corresponding two-dimensional points by least squares method, get the fitting circle with radius , and calculate the fitting error of the retained point to the fitting circle:

[0043]

[0044] Wherein, is the fitting error of the retained point to the fitting circle, and are the two-dimensional coordinates of the retained point , a is the horizontal coordinate of the center of the fitting circle, b is the vertical coordinate of the center of the fitting circle, is the radius of the fitting circle;

[0045] Through the fitting error, calculate the roundness of the fitting circle:

[0046] ​​​

[0047] wherein, is the roundness of the fitted circle, is the reserved point is the fitting error to the fitted circle, is the radius of the fitted circle;

[0048] The and the roundness 0.95, the point cloud points in the cylindrical search region are marked as the straight point cloud segment of the circular steel pipe pole.

[0049] Preferably, the axis fitting of the straight point cloud segment by the least square method based on the RANSAC algorithm obtains a pole fitting axis, and the axis fitting comprises the following specific steps:

[0050] The straight line fitting of the straight point cloud segment by the least square method based on the RANSAC algorithm is performed, the RANSAC algorithm iteration number is 50 times, the distance threshold value is that the maximum allowed distance of the point cloud points in the straight line point cloud segment to the candidate straight line is 2 cm, the RANSCA algorithm iteration is performed as follows: two point cloud points are randomly selected from the straight line point cloud segment to generate a candidate straight line; all points in the point cloud are traversed, and the Euclidean distance of each point to the candidate straight line is calculated; the number of inliers whose distance is less than the distance threshold value is counted; after 50 iterations, the candidate straight line with the largest number of inliers is selected as the optimal initial axis;

[0051] The least square method is used to re-fit the straight line for the inlier set corresponding to the optimal initial axis to obtain a pole fitting axis:

[0052]

[0053] wherein, is the coordinate of the starting point of the fitted axis, and t is a length parameter, is the unit direction vector of the pole fitting axis.

[0054] Preferably, the deflection degree value and the deflection offset vector are calculated by performing offset analysis on the pole theoretical axis and the pole fitting axis, and the offset analysis comprises the following specific steps:

[0055] The parametric equation of the pole theoretical axis is:

[0056]

[0057] wherein, is the pole theoretical axis of the i th spatial spherical anchor point and the j th spatial spherical anchor point, is the coordinate of the i th spatial spherical anchor point, and t is a length parameter, a direction vector of the i-th spatial spherical anchor point and the j-th spatial spherical anchor point;

[0058] N evenly sampled points are taken on the fitting axis of the rod, and the n-th sampled point is , the distance of to the theoretical axis of the rod is calculated:

[0059]

[0060] wherein, is the distance of the n-th sampled point to the theoretical axis of the rod, is a direction vector of the i-th spatial spherical anchor point and the n-th sampled point , and is a direction vector of the i-th spatial spherical anchor point and the j-th spatial spherical anchor point;

[0061] Among the N sampled points, the maximum value of the distance to the theoretical axis of the rod is selected as the maximum deflection of the circular steel pipe rod, and the maximum deflection is divided by the theoretical length of the theoretical axis of the rod to obtain the normalized maximum deflection as the deflection degree value = ;

[0062] According to the sampled point corresponding to the maximum deflection, the deflection offset vector of the point deviating from the theoretical axis of the rod is calculated:

[0063]

[0064] wherein, represents the deflection offset vector, represents the coordinates of the sampled point corresponding to the maximum deflection, is the maximum value of the distance of the sampled point to the theoretical axis of the rod, represents the projection point coordinates of the sampled point on the theoretical axis of the rod.

[0065] Preferably, the local risk comprehensive index is calculated by combining the deflection direction consistency index and the deflection degree consistency index, including the following specific steps:

[0066] The deflection direction consistency index is calculated by calculating the cosine similarity of the deflection offset vectors of all matched pipe rods and abnormal rods in the local subgraph of the grid structure:

[0067]

[0068] wherein, is the direction consistency index of the local subgraph of the space truss, B is the number of the to-be-matched members in the local subgraph of the space truss, b is the index of the to-be-matched member, is the deflection offset vector of the bth to-be-matched member, is the deflection offset vector of the abnormal member;

[0069] The deflection degree consistency index is calculated by performing a consistency analysis on the deflection degree values in the local subgraph of the space truss:

[0070]

[0071] wherein, is the deflection degree consistency index, B is the number of the to-be-matched members in the local subgraph of the space truss, b is the index of the to-be-matched member, is the deflection degree value of the bth to-be-matched member, is the average deflection degree value in the local subgraph of the space truss, is the deflection degree value of the abnormal member;

[0072] The local risk comprehensive index is calculated by combining the direction consistency index and the deflection degree consistency index:

[0073]

[0074] wherein, is the local risk comprehensive index, FZ is the deflection direction consistency index of the local subgraph of the space truss, PX is the deflection degree consistency index, is a nonlinear adjustment factor, and the default value is 1.5.

[0075] The application provides a deflection non-contact detection method applied to a round steel pipe member of a space truss structure, relates to machine learning and deep learning technologies, and has the following beneficial effects:

[0076] (1) The spatial spherical anchor points are obtained by screening high-density voxels according to spherical fitting difference values, the spherical node positions of the round steel pipe members in the space truss structure are accurately positioned, the spatial spherical anchor points serve as key spatial references, provide reliable spatial coordinate bases for subsequent construction of member connection relationships and determination of theoretical axes, effectively eliminate interference point clouds in non-spherical node regions, and ensure the accuracy of subsequent member identification and axis fitting.

[0077] (2), the deflection degree value and the deflection offset vector are calculated by offset analysis on the theoretical axis and the fitting axis of the rod piece, and the point cloud data is converted into a quantifiable structural deformation index: the deflection degree value can intuitively reflect the bending deformation amplitude of the rod piece, and the judgment of whether the single rod piece is abnormal is realized; the deflection offset vector describes the deformation direction, provides a directional basis for analyzing the stress state and deformation trend of the rod piece, and is a key bridge from geometric shape analysis to structural performance evaluation.

[0078] (3), the local risk comprehensive index is calculated by combining the direction deflection direction consistency index and the deflection degree consistency index, the synergy of the abnormal rod piece and the surrounding rod piece in the deformation direction and degree is comprehensively considered, the one-sidedness of single index evaluation is avoided, and the overall risk state of the local structure can be more comprehensively reflected. BRIEF DESCRIPTION OF DRAWINGS

[0079] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0080] Fig. 1 A step flow chart of a deflection non-contact detection method applied to a round steel pipe rod piece of a grid structure is provided for the present application.

[0081] Fig. 2 A step level chart for obtaining deflection degree value and deflection offset vector in the deflection non-contact detection method applied to the round steel pipe rod piece of the grid structure is provided for the present application.

[0082] Fig. 3 A step level chart for obtaining local risk comprehensive index in the deflection non-contact detection method applied to the round steel pipe rod piece of the grid structure is provided for the present application. DETAILED DESCRIPTION

[0083] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0084] Please refer to Figs. 1-3 The present application provides a technical solution: a deflection non-contact detection method applied to a round steel pipe rod piece of a grid structure.

[0085] Step S1: scanning the grid structure of the round steel pipe member by a laser scanner to obtain grid structure point cloud data; performing voxel division on the grid structure point cloud data to obtain grid structure voxels; performing density analysis on the grid structure voxels to obtain high-density voxels; performing spherical surface fitting on the high-density voxels and calculating a spherical surface fitting difference value; screening the high-density voxels according to the spherical surface fitting difference value to obtain spatial spherical anchor points.

[0086] The entire grid structure is divided into several layers along the vertical direction, each layer serving as an independent scanning unit, and the layering interval can be determined in combination with the structure height (such as 5-10 meters) or the floor distribution to ensure the relative independence of the components in each layer in space, facilitating subsequent scanning planning; then, for the round steel pipe members in each layer, the members are further divided into multiple sectors on the plane according to their distribution directions (such as horizontal, vertical, and diagonal directions), and the sector angle range is set according to the density and direction complexity of the round steel pipe members (such as 30° to 60°), to ensure that the directions of the round steel pipe members in the same sector are similar and to reduce mutual occlusion of round steel pipe members with different directions; a laser scanner is installed in the accessible area (such as the ground, scaffolding, temporary platform, etc.) of each sector in each layer in the vertical direction, and the installation point needs to satisfy that the laser beam emitted by the laser scanner can penetrate the gap between the round steel pipe members to cover all the round steel pipe members in the target sector, and can adjust the horizontal rotation angle and the vertical pitch angle to perform multi-angle scanning on the same target sector to enhance the completeness of the point cloud data; finally, appropriate scanning parameters are set according to the size, material, and distance of the round steel pipe members, including the laser scanning resolution (point spacing), range, accuracy, and frequency, to balance the data volume and processing efficiency, and then the divided scanning units (vertical layering + sectors) are scanned in sequence, the scanner position is fixed and rotated at a predetermined angle interval (such as 5°-10°) in the process, the entire sector is covered, the angle point cloud data is recorded, and the overlap degree of adjacent areas is ensured to be ≥30%, and each unit is scanned at least 3 times to obtain redundant data; finally, the point cloud quality is checked in real time after scanning, including the completeness of the key component point cloud, whether there is an occlusion blind area, and the registration accuracy, and if data is missing, the data is scanned in time, and finally the grid structure point cloud data is obtained.

[0087] Based on the grid structure point cloud data, the entire space is uniformly meshed according to a predetermined voxel size (the average point spacing of the overall point cloud data is 3-5 times the average point spacing) to form a three-dimensional grid structure voxel. Each grid structure voxel serves as a basic spatial unit and records the number of point clouds contained therein.

[0088] The point cloud density in each grid structure voxel is calculated.

[0089]

[0090] wherein MD is the point cloud density in the lattice structure voxel, is the number of point clouds in the voxel, is the volume of the voxel.

[0091] The lattice structure voxel with the point cloud density greater than the preset density threshold is marked as a high-density voxel. The high-density voxel is subjected to spherical fitting by a least square method, and a target function is a residual square sum of minimizing the sphere center and the radius .

[0092]

[0093] wherein is the fitting sphere center of the mth high-density voxel, is the fitting radius of the mth high-density voxel, is the ith point cloud point in the mth high-density voxel, is the set of point cloud points in the mth high-density voxel.

[0094] The fitting sphere center and the fitting sphere radius of the mth high-density voxel are finally obtained by a least square method.

[0095] The root mean square error of the fitting sphere of the mth high-density voxel is calculated:

[0096]

[0097] wherein is the root mean square error of the mth high-density voxel, is the number of point cloud points in the mth high-density voxel, is the ith point cloud point in the mth high-density voxel, is the fitting sphere center of the mth high-density voxel, , is the fitting radius of the mth high-density voxel.

[0098] The normal vector consistency of the fitting sphere of the mth high-density voxel is calculated:

[0099]

[0100] wherein is the normal vector consistency of the mth high-density voxel, std() is a standard deviation function, is the ith point cloud point in the mth high-density voxel, is the fitting sphere center of the mth high-density voxel, , is the mth high-density voxel.​

[0101] The spherical fitting difference value is calculated by combining the root mean square error and the normal vector consistency:

[0102]

[0103] wherein, is the spherical fitting difference value of the mth high-density voxel, is the root mean square error of the mth high-density voxel, is the normal vector consistency of the mth high-density voxel, is the root mean square error threshold value, is the normal vector consistency threshold value, and are the adjustment coefficients of the root mean square error and the normal vector consistency, respectively, + = 1.

[0104] It should be noted that, and are the adjustment coefficients of the root mean square error and the normal vector consistency, respectively, when the geometric accuracy is preferred, and = 0.7, = 0.3; when the shape consistency is preferred, and = 0.4, = 0.6. The root mean square error threshold value is taken as 2.0 mm, and the normal vector consistency threshold value is taken as 0.15, <1 indicates that the fitting is accepted. For example, when the shape consistency is preferred, is 1.55 mm, is 0.12, is 0.79, indicating that the fitting is accepted.

[0105] It's important to note that the spherical fit difference is calculated by combining root mean square error (RMS) and normal consistency. RMS quantifies the average distance deviation between the point cloud and the fitted sphere, reflecting the overall geometric fit. Normal consistency, on the other hand, measures the dispersion of the point cloud's local surface orientation (i.e., normal vector) around the center of the fitted sphere, revealing whether the point cloud exhibits the uniform outward radiation characteristic of a sphere in its local topology. Using RMS error alone cannot distinguish pseudo-spheres where the point cloud is densely distributed but has chaotic orientations (such as dense pits or bumps). Using normal consistency alone ignores pseudo-fits where the point cloud as a whole is too far from the sphere. By combining these weighted approaches to form a spherical fit difference, we can more comprehensively determine whether high-density voxels truly correspond to spherical nodes (anchor points) in space. This effectively eliminates interfering areas where the point cloud is densely clustered but non-spherical in shape (such as rod parts, connecting plates, or obstructions), ensuring the accuracy of spatial spherical anchor point identification in subsequent steps.

[0106] High-density voxels are screened according to the spherical fitting difference value, and high-density voxels with a spherical fitting difference value less than 1 are used as spatial spherical anchor points.

[0107] Step S2: Based on the spatial spherical anchor points, a grid space candidate connection matrix is ​​constructed; by performing rod screening on the grid space candidate connection matrix, a straight point cloud segment is obtained; and by performing axis fitting on the straight point cloud segment using the least squares method based on the RANSAC algorithm, a rod fitting axis is obtained.

[0108] The coordinates of the center of the sphere of the i-th spatial spherical anchor point are used as the coordinates of the spatial spherical anchor point =( , , ).

[0109] Based on the spatial spherical anchor points, a grid space candidate connection matrix is ​​constructed:

[0110]

[0111] in, The minimum length of the round steel tube member is 0.5m by default. The maximum length of the round steel tube member is 10m by default. is the coordinate of the i-th spatial spherical anchor point, is the coordinate of the j-th spatial spherical anchor point.

[0112] In the grid space connection matrix, for Two spatial spherical anchor points corresponding to 1 and , calculate the central axis of the two spatial spherical anchor points , the direction vector of the central axis =( - , - , - ), the length is .by As the center, along the direction perpendicular to the vector Direction expansion radius (Take 1.5-2 times the maximum design diameter of the round steel pipe rod) to form a cylindrical search area.

[0113] For each point cloud point in the cylindrical search area , through the neighborhood radius of the point cloud point (5cm) neighborhood, count the number of points in the neighborhood , then the local density of the kth point cloud point in the cylindrical search area is: = , and establish a local linear density field model by fitting the density difference within the neighborhood (e)= + * , ( ) represents the first Local density of neighborhood points: Taking the e-th neighborhood point as the center, calculate the neighborhood radius of the e-th neighborhood point The local density within Represents the e-th neighborhood point and point cloud point in the neighborhood The distance is finally solved by minimizing the weighted residual square sum to obtain the gradient vector of the k-th point cloud point ), get the gradient vector of the point cloud point , if the gradient vector at this point Direction vector with respect to the central axis The angle is close to 90° (90° ), then the point is retained; otherwise, the point is discarded.

[0114] For the retention point , calculate the distance from this point to the center axis The radial distance of all retained points is calculated, and the radial distance mean and radial distance standard deviation are calculated. , then the radial distribution is considered to be consistent (which is consistent with the characteristic of stable radius of the steel pipe section).

[0115] Project all reserved points perpendicular to the central axis The plane (take the cross section in the middle of the central axis) is used to obtain the corresponding two-dimensional points. All the corresponding two-dimensional points are fitted with the circle equation by the least square method to obtain the radius of the fitting circle, and calculating the retention points the fitting error to the fitting circle :

[0116]

[0117] wherein, is the retention point the fitting error to the fitting circle, and is the retention point the corresponding two-dimensional coordinates, a is the horizontal coordinate of the center of the fitting circle, b is the vertical coordinate of the center of the fitting circle, is the radius of the fitting circle.

[0118] By the fitting error, the roundness of the fitting circle is calculated:

[0119]

[0120] wherein, is the roundness of the fitting circle, is the retention point the fitting error to the fitting circle, is the radius of the fitting circle.

[0121] The point cloud points in the cylindrical search area with and the roundness 0.95 are marked as straight line point cloud segments of the round steel pipe member.

[0122] The straight line fitting is performed on the straight line point cloud segments by the least square method based on the RANSAC algorithm. The RANSAC algorithm parameters need to be set according to the steel pipe features and the scanning accuracy: the number of iterations is 50-100 times. Too few times may miss the optimal straight line, and too many times will increase the calculation amount, and 50 times can balance between covering enough candidate straight lines and calculation efficiency (suitable for medium-sized point clouds, about 1000-5000 points). Distance threshold: set the maximum allowed distance of points to the straight line (inlier judgment standard), which can be taken as "radius error of round steel pipe member + scanning accuracy" (such as 2 cm). There is a slight radius error in the manufacture of round steel pipe members, usually ≤1 mm, and the three-dimensional scanning error is about 1-2 mm in laser scanning accuracy, and after superposition, 2 cm can cover more than 95% of the inliers, while excluding obvious noise points.

[0123] RANSAC algorithm iteration is performed: two point cloud points are randomly selected from the straight line point cloud segment (two points in space determine a straight line), a candidate straight line is generated; all points in the point cloud are traversed, the Euclidean distance of each point to the candidate straight line is calculated; the number of inliers with a distance less than a distance threshold is counted, the more inliers, the more likely the candidate straight line is the real axis; after 50 iterations, the candidate straight line with the most inliers is selected as the optimal initial axis. The projection coordinates of all points in the inlier set in the axis direction are calculated, and the minimum and maximum values of the projection coordinates are taken as the effective range of the fitted axis.

[0124] For the inlier set corresponding to the optimal initial axis, a straight line is refitted by least squares method, the least squares method further optimizes the straight line parameters (starting point, direction vector) by minimizing the sum of squares of distances of all inliers to the straight line, eliminates the error caused by random sampling of the RANSAC algorithm, and obtains a more accurate rod fitting axis:

[0125]

[0126] wherein, is the coordinate of the starting point of the fitted axis, t is the length parameter, is the unit direction vector of the rod fitting axis.

[0127] Step S3: connecting the geometric center of the space spherical anchor point as the theoretical axis of the rod, and calculating the deflection degree value and deflection offset vector by performing offset analysis on the rod theoretical axis and the rod fitting axis.

[0128] The space anchor points of the two end ball nodes of the rod are taken as the end points, and a straight line is constructed as the theoretical axis of the rod. The parametric equation of the rod theoretical axis is:

[0129]

[0130] wherein, is the rod theoretical axis of the ith space spherical anchor point and the jth space spherical anchor point, is the coordinate of the ith space spherical anchor point, t is the length parameter, is the direction vector of the ith space spherical anchor point and the jth space spherical anchor point.

[0131] N sampling points are uniformly taken on the rod fitting axis (such as taking 1 point every 10 cm), the nth sampling point is , the distance of to the rod theoretical axis is calculated:

[0132]

[0133] wherein, is the nth sampling point the distance from the sampling point to the theoretical axis of the rod, the direction vector of the i-th spatial spherical anchor point and the n-th sampling point the direction vector of the i-th spatial spherical anchor point and the j-th spatial spherical anchor point.

[0134] It should be noted that N sampling points are uniformly taken on the rod fitting axis, and the distance from each point to the theoretical axis of the rod is calculated, which is to cover the full length of the rod by multiple points to avoid the contingency of single point measurement, and to comprehensively capture the deflection of the rod at different positions, so as to accurately determine the value and position of the maximum deflection, and to provide a reliable basis for subsequent calculation of the normalized deflection degree value.

[0135] Among the N sampling points, the maximum value of the distance from the sampling point to the theoretical axis of the rod is taken as the maximum deflection of the circular steel pipe rod, and the maximum deflection is divided by the theoretical length of the theoretical axis of the rod to obtain the normalized maximum deflection as the deflection degree value .

[0136] It should be noted that the deflection degree value , which is the maximum value of the distance from the sampling point to the theoretical axis of the rod among the N sampling points, can accurately capture the most significant position and degree of the bending deformation of the rod, and reflect the critical state of the stress deformation; and the normalization of the maximum deflection by dividing the theoretical length of the theoretical axis of the rod can eliminate the problem of absolute deflection value incomparability caused by length difference of different rods, so that the deformation degree of circular steel pipe rods of different specifications and lengths has a unified measurement standard, and the deflection degree value obtained can more objectively reflect the relative deformation amplitude of the rod, and provide quantitative basis for subsequent comparison with the preset threshold to determine whether it is an abnormal rod.

[0137] According to the sampling point corresponding to the maximum deflection, the deflection offset vector of the point deviating from the theoretical axis of the rod is calculated:

[0138]

[0139] wherein, represents the deflection offset vector, represents the coordinates of the sampling point corresponding to the maximum deflection, is the maximum value of the distance from the sampling point to the theoretical axis of the rod, represents the projection point coordinates of the sampling point on the theoretical axis of the rod.

[0140] ​​To prevent error interference in single detection, a multi-frame scanning fusion strategy is further introduced, that is, by repeatedly fitting the same rod at multiple time points or multiple angles, the average of the deflection degree value and the average of the deflection offset vector are calculated as the final result output.

[0141] Step S4: By comparing the deflection degree value of the round steel pipe rod with the preset threshold value, if it is greater than the preset threshold value, it is marked as an abnormal rod; based on the abnormal rod, a local subgraph of the space truss is constructed; by calculating the cosine similarity of the deflection offset vector in the local subgraph of the space truss, a deflection direction consistency index is obtained; by performing a consistency analysis on the deflection degree value in the local subgraph of the space truss, a deflection degree consistency index is calculated.

[0142] The spatial spherical anchor point is taken as a node unit in the topological graph of the space truss structure, and the rod fitting axis is taken as an edge unit in the topological graph of the space truss structure, wherein each edge corresponds to connecting two node units.

[0143] Topological relationship verification: The accuracy of the graph model is verified through point cloud data to ensure that the connection relationship of all node-rod is consistent with the actual structure (such as avoiding missing connection, wrong connection, especially checking the multi-rod connection at complex nodes).

[0144] Large deflection rod screening: A preset deflection threshold (set through engineering experience) is used to record the round steel pipe rod greater than the preset deflection threshold as an "abnormal rod".

[0145] Definition of local subgraph range of space truss: The spatial spherical anchor points at both ends of the abnormal rod are determined as the core nodes of the local subgraph of the space truss; based on the core nodes, the local subgraph of the space truss is expanded: all round steel pipe rods directly connected with the core nodes and the spatial spherical anchor points connected with the other end of the round steel pipe rod are all included in the local subgraph of the space truss; finally, after the local subgraph of the space truss is constructed, the round steel pipe rods in the local subgraph of the space truss except the abnormal rod are recorded as the matching rods.

[0146] The direction consistency index of the deflection offset vector of all matching pipe rods in the local subgraph of the space truss and the abnormal rod is calculated by cosine similarity:

[0147]

[0148] Wherein, is the direction consistency index of the local subgraph of the space truss, B is the number of matching rods in the local subgraph of the space truss, b is the index of the matching rod, is the deflection offset vector of the bth matching rod, is the deflection offset vector of the abnormal rod.

[0149] By performing a synergistic analysis on the deflection values ​​in the local subgraph of the grid, the deflection consistency index is calculated:

[0150]

[0151] in, is the consistency index of deflection degree, B is the number of rods to be matched in the local subgraph of the grid, b is the index of the rod to be matched, is the deflection value of the bth member to be matched, is the average value of the deflection degree in the local subgraph of the grid, is the deflection value of the abnormal member.

[0152] It should be noted that the deflection consistency index is obtained by introducing the average deflection value in the local subgraph of the grid. As a benchmark, quantify the mechanical synergy strength of the abnormal rod and the surrounding rods to be matched in terms of deflection value, and calculate the deviation of the rods to be matched Deviation from abnormal member The product and sum of the two reveal the correlation between the deformation trends; the denominator is standardized to eliminate the dimension effect, so that the output value reflects the consistency of the deflection degree of local structural deformation.

[0153] Step S5: By combining the deflection direction consistency index and the deflection degree consistency index, a local risk comprehensive index is calculated, and risk levels are divided according to the local risk comprehensive index to achieve non-contact detection of round steel tube rods.

[0154] By combining the directional consistency index and the deflection consistency index, the local risk comprehensive index is calculated:

[0155]

[0156] in, is the comprehensive index of local risk, FZ is the consistency index of the deflection direction of the local subgraph of the grid, PX is the consistency index of the deflection degree, It is a nonlinear adjustment factor, and the default value is 1.5.

[0157] It should be noted that the local risk comprehensive index is calculated by combining the deflection direction consistency index and the deflection degree consistency index. The deflection direction consistency index reflects the spatial correlation between the abnormal member and the surrounding members in the deformation direction, while the deflection degree consistency index quantifies their statistical correlation in deformation amplitude. CCI combines the deflection direction consistency index and the deflection degree consistency index through a nonlinear formula, in which the adjustment factor The contribution of the consistency of the degree of deflection is strengthened. The local risk comprehensive index indicates that the CCI outputs a high risk value only when the direction and degree are significantly consistent, effectively excluding local noise interference and reducing the misjudgment rate.

[0158] According to the local risk comprehensive index (CCI), the risk level is divided as follows: when CCI≤0.3, it is determined as a low risk level, indicating that the deflection of the abnormal rod is weakly related to the risk of the surrounding rod, and the local stability of the structure is good; when 0.3<CCI≤0.7, it is determined as a medium risk level, indicating that there is a certain consistency between the risk of the abnormal rod and the surrounding rod, and the local structure needs to be monitored in time; when CCI>0.7, it is determined as a high risk level, meaning that the deflection direction and degree of the abnormal rod and the surrounding rod are highly consistent, and the local structure may have abnormal overall stress, which needs to be immediately detected and reinforced.

[0159] This paper introduces a non-contact detection method for the deflection of circular steel pipe rods in net rack structures. This method obtains point cloud data by vertically layering laser scanners, selects spatial spherical anchor points through voxel division and density analysis, constructs a connection matrix based on anchor points and fits the rod axis, then analyzes the deflection parameters through the offset analysis of the theoretical axis and the fitted axis, and finally calculates the local risk comprehensive index combining the local direction and degree consistency index to realize the risk level division and non-contact detection of the rod.

[0160] The spatial spherical anchor points are obtained by screening high-density voxels according to the spherical fitting difference value. The significance lies in accurately positioning the spherical node positions of the circular steel pipe rods in the net rack structure. These anchor points serve as key spatial references, providing reliable spatial coordinate basis for subsequent construction of rod connection relationships and determination of theoretical axis, while effectively eliminating the interference points in the non-spherical node area, ensuring the accuracy of subsequent rod identification and axis fitting.

[0161] The deflection degree value and deflection offset vector are calculated by offset analysis of the theoretical axis and the fitted axis of the rod. The significance lies in converting point cloud data into quantifiable structural deformation indicators: the deflection degree value can intuitively reflect the bending deformation amplitude of the rod, realizing the judgment of whether a single rod is abnormal; the deflection offset vector describes the direction of deformation, providing a directional basis for analyzing the stress state and deformation trend of the rod, and is a key bridge from geometric shape analysis to structural performance evaluation.

[0162] The local risk comprehensive index is calculated by combining the deflection direction consistency index and the deflection degree consistency index, which has the significance of comprehensively considering the synergy of the abnormal rod and the surrounding rod in the deformation direction and degree, avoiding the one-sidedness of single index evaluation, and can more comprehensively reflect the overall risk state of the local structure, providing a scientific and quantitative basis for accurately dividing the risk level and judging whether the local structure has overall stress abnormality, and further laying a foundation for formulating targeted detection and reinforcement measures.

[0163] It should be noted that, in this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0164] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, combinations, and variations can be made by those skilled in the art without departing from the spirit and scope of the present application, which is defined by the appended claims and their equivalents.

Claims

1. A non-contact deflection detection method for circular steel tube members in a grid structure, characterized by: The following steps are involved: Step S1: Scanning the grid structure of the round steel tube rods with a laser scanner to obtain grid structure point cloud data; performing voxel division on the grid structure point cloud data to obtain grid structure voxels; performing density analysis on the grid structure voxels to obtain high-density voxels; performing spherical fitting on the high-density voxels and calculating spherical fitting difference values; screening the high-density voxels according to the spherical fitting difference values ​​to obtain spatial spherical anchor points; Step S2: Based on the spatial spherical anchor points, a grid space candidate connection matrix is ​​constructed; by performing rod screening on the grid space candidate connection matrix, a straight point cloud segment is obtained; and by performing axis fitting on the straight point cloud segment using the least squares method based on the RANSAC algorithm, a rod fitting axis is obtained; Step S3: Using the line connecting the geometric centers of the spatial spherical anchor points as the theoretical axis of the rod, performing an offset analysis on the theoretical axis of the rod and the fitting axis of the rod to calculate the deflection value and the deflection offset vector, including the following specific steps: The parametric equation of the theoretical axis of the rod is: ； in, is the theoretical axis of the rod at the i-th spatial spherical anchor point and the j-th spatial spherical anchor point, is the coordinate of the i-th spatial spherical anchor point, t is the length parameter, is the direction vector of the i-th spatial spherical anchor point and the j-th spatial spherical anchor point; Take N sampling points evenly on the fitting axis of the rod, and the nth sampling point is ,calculate Distance to the theoretical axis of the member: ； in, is the nth sampling point The distance to the theoretical axis of the member, is the i-th spatial spherical anchor point and the n-th sampling point The direction vector, is the direction vector of the i-th spatial spherical anchor point and the j-th spatial spherical anchor point; Among N sampling points, select the maximum distance to the theoretical axis of the rod , as the maximum deflection of the round steel tube member, and divide the maximum deflection by the theoretical length of the theoretical axis of the member , get the normalized maximum deflection as the deflection degree value = ; According to the sampling point corresponding to the maximum deflection, the deflection offset vector of the point from the theoretical axis of the member is calculated: ； in, represents the deflection offset vector, represents the coordinates of the sampling point corresponding to the maximum deflection, is the maximum value of the theoretical axis distance of the sampling point member, Indicates sampling point Coordinates of the projection point on the theoretical axis of the member; Step S4: By comparing the deflection value of the round steel tube member with a preset threshold, if the deflection value is greater than the preset threshold, it is marked as an abnormal member; based on the abnormal member, a local subgraph of the grid is constructed; by calculating the cosine similarity of the deflection offset vector in the local subgraph of the grid, a deflection direction consistency index is obtained; by performing a synergy analysis on the deflection value in the local subgraph of the grid, a deflection consistency index is calculated; Step S5: Calculate a local risk comprehensive index by combining the deflection direction consistency index and the deflection degree consistency index, and divide the risk levels according to the local risk comprehensive index to achieve non-contact detection of round steel pipe rods; The calculation of the local risk comprehensive index includes the following specific steps: The deflection direction consistency index is calculated by calculating the cosine similarity of the deflection offset vectors of all the pipe members to be matched and the abnormal members in the local subgraph of the grid: ； in, is the directional consistency index of the local subgraph of the grid, B is the number of rods to be matched in the local subgraph of the grid, b is the index of the rod to be matched, is the deflection offset vector of the bth member to be matched, is the deflection offset vector of the abnormal member; By performing a synergistic analysis on the deflection values ​​in the local subgraph of the grid, the deflection consistency index is calculated: ； in, is the consistency index of deflection degree, B is the number of rods to be matched in the local subgraph of the grid, b is the index of the rod to be matched, is the deflection value of the bth member to be matched, is the average value of the deflection degree in the local subgraph of the grid, is the deflection value of the abnormal member; By combining the directional consistency index and the deflection consistency index, the local risk comprehensive index is calculated: ； in, is the comprehensive index of local risk, FZ is the consistency index of the deflection direction of the local subgraph of the grid, PX is the consistency index of the deflection degree, It is a nonlinear adjustment factor, and the default value is 1.

5.

2. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 1, characterized in that: Scanning the grid structure of the round steel tube rods by a laser scanner to obtain grid structure point cloud data includes the following specific steps: The entire grid structure is divided into several layers along the vertical direction. Each layer serves as an independent scanning unit and is divided into several sectors according to the distribution direction of the round steel tube members in each layer. A laser scanner is installed in the accessible area of ​​each sector in each vertical layer. In each sector, the laser scanner performs multi-angle scanning to finally obtain the grid structure point cloud data.

3. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 2, characterized in that: The grid structure voxels are obtained by performing voxel division on the grid structure point cloud data; Performing density analysis on the grid structure voxels to obtain high-density voxels includes the following steps: Based on the grid structure point cloud data, the entire space is evenly gridded according to the preset voxel size to form a three-dimensional grid structure voxel. Each grid structure voxel is used as a basic spatial unit, and the number of point clouds contained in the grid structure voxel is recorded; Calculate the point cloud density in each grid structure voxel: ； Among them, MD is the point cloud density in the grid structure voxel, is the number of point clouds within the voxel, is the volume of the voxel; The grid structure voxels whose point cloud density is greater than the preset density threshold are marked as high-density voxels.

4. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 3, characterized in that: The method of performing spherical fitting on the high-density voxels and calculating the spherical fitting difference value comprises the following steps: The high-density voxels are subjected to the least squares method. Perform spherical fitting to obtain the fitting sphere center of the mth high-density voxel and the radius of the fitting sphere ; Calculate the root mean square error of the fitted sphere for the mth high-density voxel: ； in, is the root mean square error of the mth high-density voxel, is the number of point cloud points in the mth high-density voxel, is the i-th point cloud point in the m-th high-density voxel, is the fitting sphere center of the mth high-density voxel, , is the fitting radius of the mth high-density voxel; Calculate the normal vector consistency of the fitted sphere for the mth high-density voxel: ； in, is the normal vector consistency of the mth high-density voxel, std() is the standard deviation function, is the i-th point cloud point in the m-th high-density voxel, is the fitting sphere center of the mth high-density voxel, , is the set of point cloud points in the mth high-density voxel; By combining the root mean square error and normal vector consistency, the spherical fitting difference value is calculated: ； in, is the spherical fitting difference value of the mth high-density voxel, is the root mean square error of the mth high-density voxel, is the normal vector consistency of the mth high-density voxel, is the root mean square error threshold, is the normal vector consistency threshold, and are the adjustment coefficients for the root mean square error and normal vector consistency, + =1.

5. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 4, characterized in that: The method of screening high-density voxels according to the spherical fitting difference value to obtain a spatial spherical anchor point includes the following steps: The high-density voxels are screened according to the spherical fitting difference value, and the high-density voxels with the spherical fitting difference value less than 1 are used as spatial spherical anchor points.

6. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 5, characterized in that: The step of constructing a grid space candidate connection matrix based on the spatial spherical anchor points comprises the following specific steps: The coordinates of the center of the sphere of the i-th spatial spherical anchor point are used as the coordinates of the spatial spherical anchor point =( , , ); Based on the spatial spherical anchor points, a grid space candidate connection matrix is ​​constructed: ； in, The minimum length of the round steel tube member is 0.5m by default. The maximum length of the round steel tube member is 10m by default. is the coordinate of the i-th spatial spherical anchor point, is the coordinate of the j-th spatial spherical anchor point.

7. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 6, characterized in that: The method of obtaining a straight line point cloud segment by screening the candidate connection matrix of the grid space includes the following specific steps: In the grid space connection matrix, Two spatial spherical anchor points corresponding to 1 and , calculate the central axis of the two spatial spherical anchor points , the direction vector of the central axis =( - , - , - ), the length is ; by As the center, along the direction perpendicular to the vector Direction expansion radius , forming a cylindrical search area; For K point cloud points in the cylindrical search area, count the kth point cloud point Neighborhood radius The number of points in the neighborhood , then the local density of the kth point cloud point in the cylindrical search area is: = , and calculate the gradient vector of the point cloud point by the density difference fitting method in the neighborhood , point cloud point The gradient vector With the central axis Direction vector The angle range is If the point is not in the range of Otherwise, remove the point; For the retention point , calculate the distance from the reserved point to the center axis Calculate the radial distance average and radial distance standard deviation of all retained points. , then the radial distribution of the cylindrical search area is consistent; Project all reserved points perpendicular to the central axis The plane of the 2D point is obtained, and the circle equation is fitted by the least square method to obtain the radius of the 2D point. The fitting circle and calculation of the retained points Fitting error to the fitted circle : ； in, For reservation point The fitting error to the fitted circle, and For reserved points The corresponding two-dimensional coordinates, a is the horizontal coordinate of the center of the fitting circle, b is the vertical coordinate of the center of the fitting circle, is the radius of the fitted circle; The circularity of the fitting circle is calculated using the fitting error: ； in, is the roundness of the fitted circle, For reserved points The fitting error to the fitted circle, is the radius of the fitted circle; Will and roundness Point cloud points in a cylindrical search area of ​​0.95 mark the straight point cloud segments of the circular steel tube member.

8. The non-contact deflection detection method for round steel tube members of a grid structure according to claim 7, characterized in that: The axis fitting of the straight point cloud segment by the least square method based on the RANSAC algorithm to obtain the rod fitting axis includes the following specific steps: The linear point cloud segment is fitted using the least squares method based on the RANSAC algorithm. The number of RANSAC algorithm iterations is 50, and the distance threshold is: the maximum allowable distance between the point cloud points in the linear point cloud segment and the candidate line is 2 cm. The RANSCA algorithm is iterated: two point cloud points are randomly selected from the linear point cloud segment to generate a candidate line; all points in the point cloud are traversed, and the Euclidean distance of each point to the candidate line is calculated; the number of inliers whose distance is less than the distance threshold is counted; after repeating the iteration 50 times, the candidate line with the largest number of inliers is selected as the optimal initial axis; For the set of interior points corresponding to the optimal initial axis, the least squares method is used to refit the straight line to obtain the fitting axis of the member: ； in, is the coordinate of the starting point of the fitting axis, t is the length parameter, is the unit direction vector of the member fitting axis.

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