Method for detecting deformation quantity of container

Abstract

The invention provides a method for detecting the deformation quantity of a container, and relates to the technical field of container measurement, and the method comprises the steps: carrying out the whole region division of a to-be-detected container according to the structural characteristics of the to-be-detected container, and obtaining a subregion division result of the to-be-detected container; performing three-dimensional laser scanning on each sub-region in sequence based on a sub-region division result to obtain a three-dimensional point cloud model of the to-be-measured container; and for the three-dimensional point cloud model, projection area fitting and recess depth measurement of a deformation generation area are respectively carried out to obtain a projection area parameter and a deformation depth parameter of the deformation area. In order to solve the problem that deformation parts, especially small deformation, of containers in the petrochemical and refinery fields are difficult to accurately identify and position, according to the method of firstly dividing areas and then dynamically splicing, deformation positions in all divided sub-areas are identified, and then the deformation parts are identified on the whole area of the containers through dynamic splicing of the sub-areas.

Description

Technical Field

[0001] The invention relates to the technical field of container measurement, and is applied to non-contact measurement and detection methods, in particular to a method for detecting the deformation amount of a container. Background Art

[0002] Large vertical oil tanks are important equipment for oil storage. During their service, due to uneven pressure on the tank wall and uneven sinking of the tank foundation, the oil tanks are prone to geometric deformation to varying degrees. This deformation will in turn induce uneven pressure on the tank wall, accelerate the deformation of the oil tank, and cause major safety accidents, casualties, and environmental pollution. At present, geometric deformation detection has been listed as one of the important contents of the annual inspection of oil tanks.

[0003] At present, conventional methods for detecting deformation of tank bodies include: using a ladder and a circumference ruler method to measure deformations such as concavity for small-volume metal storage tanks, but this method cannot accurately measure the concavity volume of large-deformation tank walls. Floating roof tank safety inspection usually uses optical reference method and photoelectric method to measure tank deformation. The optical reference method requires the use of an optical plumb line, a horizontal ruler, a mobile magnetic ruler, etc., but this single-point measurement method will produce large measurement errors when the tank wall deformation is complex. Photoelectric method for measuring tank deformation generally uses total stations and GPS, etc. This method still belongs to single-point measurement, that is, it can only obtain deformation data of a few observation points by point observation and then infer the overall deformation. It is impossible to obtain local and overall accurate deformation details, and the equipment is difficult to install on site, and the measurement time is relatively long. Therefore, it has high requirements for environmental stability, and its measurement accuracy and stability are often greatly affected. Therefore, the detection efficiency and accuracy cannot be effectively guaranteed, and cannot meet actual production needs. In addition, the existing technology requires many geometric parameters to be measured and the operation is complicated.

[0004] In recent years, the German National Metrology Institute (PTB) and the American company Trimble have developed a new volume calibration method for the Trimble CX 3D laser scanner, which has been certified by the German National Metrology Institute. This method first pre-processes the point cloud of the tank body, and then builds a triangular mesh structure corresponding to the tank body on this basis. Then, the cross section of the tank body is intercepted at every specified elevation, and the tank body volume is calculated according to the cylinder volume calculation formula. However, this method simplifies the tank body model and treats the tank body as a regular cylinder. It cannot accurately reflect the geometric deformation information of the tank body, and there is a large error with the real tank body model.

[0005] In view of the problems in the prior art, the present invention provides a method for detecting the deformation amount of a container. Summary of the invention

[0006] In view of the problems of the current prior art, the present invention provides a method for detecting the deformation of a container, the method comprising:

[0007] S1. Divide the container around the entire perimeter of the container according to the structural characteristics of the container to be tested, and obtain the sub-area division result of the container to be tested;

[0008] S2. Based on the sub-region division result, perform three-dimensional laser scanning on each sub-region in turn to obtain a three-dimensional point cloud model of the container to be tested;

[0009] S3. For the three-dimensional point cloud model, respectively perform projection area fitting and depression depth measurement on the deformation region to obtain projection area parameters and deformation depth parameters of the deformation region.

[0010] According to one embodiment of the present invention, step S1 comprises:

[0011] Acquiring original structural data of the container to be tested to obtain the structural features of the container to be tested;

[0012] Let the diameter of the container to be tested be D, and divide the container to be tested into M equal parts along the circumferential direction, satisfying Among them, m is the circumferential division coefficient;

[0013] Let the height of the container to be tested be H, and divide the container to be tested into N equal parts along the height direction, satisfying Where n is the height direction division coefficient;

[0014] After the circumferential division and the height division, the cylindrical surface of the container to be tested is divided into Q sub-areas, where Q = M × N;

[0015] The sub-regions at the same horizontal height are numbered in a clockwise order in the circumferential direction, and the sub-regions at the same vertical line are numbered in a bottom-up order in the height direction to obtain the sub-region division result of the container to be tested, wherein each sub-region on the circumferential surface of the container to be tested is numbered as (M i , N k ), i=1~M, k=1~N.

[0016] According to an embodiment of the present invention, step S1 further includes, based on the sub-region division result, setting a splicing identification point at the boundary of each sub-region, which includes:

[0017] Along the circumferential direction of each sub-area, a splicing identification point is set at a first distance interval, wherein the first distance q is the landmark coefficient;

[0018] Along the height direction of each sub-area, a splicing identification point is set at every second distance, wherein the second distance

[0019] When setting the splicing identification points, only one set of splicing identification points needs to be set at the boundary between every two adjacent sub-areas.

[0020] According to one embodiment of the present invention, step S2 comprises:

[0021] Based on the sub-region division result, three-dimensional laser scanning is performed on each sub-region in turn to obtain a sub-region point cloud data set of the container to be tested;

[0022] According to the sub-region point cloud data set and in combination with the splicing identification points, the container to be tested is dynamically spliced ​​around the entire circumference to obtain the three-dimensional point cloud model of the container to be tested.

[0023] According to one embodiment of the present invention, the sub-region point cloud data set of the container to be tested is obtained by the following steps:

[0024] a. For the sub-area to be scanned, set the scanning device and scan the sub-area in the order from bottom to top and from left to right;

[0025] b. Adjust the relative angle between the scanning field of view and the surface of the sub-area to be scanned, and return to step a after each adjustment;

[0026] c. After the scanning is completed, a point cloud data set of the sub-region of the container to be tested is obtained.

[0027] According to one embodiment of the present invention, full-circle dynamic splicing is performed through the following steps:

[0028] Based on the sub-region point cloud data set, the point cloud data of each sub-region is clipped, and the point cloud data outside each sub-region is clipped to obtain clipping result data of each sub-region;

[0029] For each sub-region, performing point cloud data optimization on the clipping result data to obtain optimized result data of each sub-region;

[0030] According to the optimization result data and in combination with the splicing identification points, the point cloud data between the sub-areas are dynamically spliced ​​to obtain the three-dimensional point cloud model of the entire circumference of the container to be tested.

[0031] According to one embodiment of the present invention, the clipping result data of each sub-region is obtained by the following steps:

[0032] The point cloud data set corresponding to the current sub-region is recorded as Q all ;

[0033] The splicing identification point corresponding to the current sub-region is taken as the boundary, and the point cloud data set outside the marked boundary is Q out , the point cloud data set within the boundary is Q in;

[0034] Execute the point cloud dataset operation Q of the current sub-area out =Q all -Q in , trim the point cloud data outside the current sub-region to obtain the trimming result data corresponding to the current sub-region.

[0035] According to one embodiment of the present invention, the optimization result data of each sub-region is obtained by the following steps:

[0036] Let the central axis of the container to be tested be O, then the deformation amount of the container to be tested perpendicular to the central axis O is Δd, where Δd is the convex height or concave depth of the container to be tested;

[0037] For the convex deformation, the point cloud at the farthest vertical distance from the central axis O is recorded as

[0038] The number of convex tip point clouds is recorded as R1. If R1 satisfies the formula: S is the point cloud number threshold, then it is determined In the range, The data within the radius are accidental point cloud data and are deleted, and K is the radius coefficient;

[0039] For the concave deformation, the point cloud at the closest vertical distance from the central axis O has a distance from the central axis O of

[0040] The number of concave tip point clouds is recorded as R2. If R2 satisfies the formula: It is determined In the range, The data within the radius is considered as accidental point cloud data and is deleted.

[0041] According to one embodiment of the present invention, the three-dimensional point cloud model of the entire circumference of the container to be tested is obtained by splicing through the following steps:

[0042] Record sub-area (M i , N k ) and sub-region (M i+1 , N k ) between each circumferential splicing identification point is Δe i , then the cumulative error of the two regions in the circumferential direction is

[0043] Record sub-area (M i , N k ) and sub-region (M i , N k+1) between each height splicing recognition point is Δe k , then the cumulative error of the two regions in the height direction is

[0044] Calculate the sub-area (M i , N k )’s cumulative error of splicing recognition points is like δ is the stitching error threshold, then the sub-region (M i , N k ) is successfully spliced ​​with the adjacent sub-region;

[0045] Sub-area (M i , N k ) After successful splicing, move to the next splicing sub-area (M i+1 , N k ) or (M i , N k+1 ), determine the sub-region (M i+1 , N k ) or (M i , N k+1 ) is successfully spliced ​​with the adjacent sub-regions, and so on, until all sub-regions are successfully spliced ​​to obtain the three-dimensional point cloud model.

[0046] According to one embodiment of the present invention, in step S3, the projection area fitting of the deformation occurrence region is performed by the following steps:

[0047] The three-dimensional point cloud model is expanded along the circumferential direction, and the long side of the expanded rectangle is the perimeter of the container, marked as the X-axis, and the short side of the expanded rectangle is the height of the container, marked as the Y-axis;

[0048] Calculate the average value of all point cloud data of the unfolded rectangle on the Z axis and mark it as the base plane of the unfolded rectangle;

[0049] The parts above and below the base plane are recorded as convex deformation and concave deformation respectively, and the traversal starts from the point cloud data farthest from the base plane until the Z coordinate value of the traversed point cloud data satisfies: Z i -Z O ≤∈, then stop traversal, where Z i is the Z coordinate value of the i-th point cloud data, Z O is the Z coordinate value of the point cloud data at the base plane, ∈ is the deformation threshold;

[0050] Record the projection contour surrounded by the point cloud where traversal stops, and the projection contour is the range where the deformation occurs;

[0051] The projection contour is fitted by using geometric figures, and the deformation contour image area obtained after fitting is the projection size of the deformation occurrence area.

[0052] According to an embodiment of the present invention, step S3 further comprises: based on the projection area parameter of the deformation area, performing position identification of the deformation occurrence area, which comprises:

[0053] Determine the shape contour of the deformation area by using the projection area parameter, and mark the centroid position of the shape contour of the deformation area;

[0054] The sub-region where the centroid is located is marked as the deformation occurrence position.

[0055] According to one embodiment of the present invention, in step S3, the depression depth measurement of the deformation occurrence area is performed by the following steps:

[0056] Selecting a deformation contour range of a concave portion in the deformation contour image;

[0057] Determine the point cloud farthest from the base plane within the deformation contour range of the concave part, and read the distance Z between the point cloud and the base plane in the Z-axis direction. imax , record Z imax is the depth of the depression in the deformation area.

[0058] According to another aspect of the present invention, a storage medium is provided, which contains a series of instructions for executing the method steps as described in any one of the above.

[0059] According to another aspect of the present invention, there is also provided a device for detecting the deformation amount of a container, which executes any of the above methods, and the device comprises:

[0060] A sub-region division module is used to divide the container into full-circle regions according to the structural characteristics of the container to be tested, and obtain a sub-region division result of the container to be tested;

[0061] A three-dimensional point cloud model module, which is used to perform three-dimensional laser scanning on each sub-area in turn based on the sub-area division result to obtain a three-dimensional point cloud model of the container to be tested;

[0062] The projection area parameter and deformation depth parameter module is used to perform projection area fitting and depression depth measurement of the deformation area for the three-dimensional point cloud model, so as to obtain the projection area parameter and deformation depth parameter of the deformation area.

[0063] The present invention provides a method for detecting the deformation of a container, which has the following advantages compared with the prior art:

[0064] 1) In order to solve the problem that deformation parts of containers in the petrochemical and refining fields, especially small deformations, are difficult to accurately identify and locate, the present invention adopts a method of first dividing the area and then dynamically splicing it, so as to first realize the deformation position identification in each divided sub-area, and then realize the identification of the deformation parts in the overall area of ​​the container through dynamic splicing of the sub-areas.

[0065] 2) In order to solve the problem that it is difficult to accurately quantify the deformation parts of containers in the petrochemical and refining fields, the present invention proposes a three-dimensional measurement method of laser structured light for measuring the surface deformation of containers, which quantifies the degree of deformation from two aspects: the projection area parameter of the deformation area and the deformation depth parameter.

[0066] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0068] Figure 1 A flowchart showing the steps of a method for detecting a container deformation amount according to an embodiment of the present invention is shown;

[0069] Figure 2 A flowchart showing the steps of obtaining the sub-region division result of the container to be tested according to one embodiment of the present invention is shown;

[0070] Figure 3 A schematic diagram of sub-region division according to an embodiment of the present invention is shown;

[0071] Figure 4 A flowchart of steps for obtaining a three-dimensional point cloud model of a container to be tested according to an embodiment of the present invention is shown;

[0072] Figure 5 A flowchart of the steps of full-circle dynamic splicing according to one embodiment of the present invention is shown;

[0073] Figure 6 A flowchart showing the steps of a point cloud data optimization method according to an embodiment of the present invention is shown;

[0074] Figure 7 A flowchart of steps for obtaining a projection area parameter, a deformation location and a deformation depth parameter of a deformation region according to an embodiment of the present invention is shown;

[0075] Figure 8A flowchart showing the steps of projected area fitting of the deformation occurrence region according to an embodiment of the present invention is shown.

[0076] In the accompanying drawings, the same reference numerals are used for the same components. In addition, the accompanying drawings are not drawn according to the actual scale. DETAILED DESCRIPTION

[0077] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings.

[0078] The prior art (CN111504214B) provides a method for optical fiber monitoring deformation of a large crude oil storage tank, wherein the optical fiber monitoring device for deformation of a large crude oil storage tank includes a distributed optical fiber strain sensor and a fiber grating array strain sensor; the distributed optical fiber strain sensor is arranged on the surface of the tank body to be monitored in a spiral manner, and the fiber grating array strain sensor is fixed on the surface of the position where the tank body to be monitored is deformed; when the distributed optical fiber strain sensor is arranged on the tank body in a spiral manner, the spiral pitch is H and the spiral angle is θ; the spiral pitch H is 0.3 to 0.4 times the height of each layer of wallboard on the tank, wherein θ=arctan(H / D); D is the diameter of the tank, and the spiral angle is the angle between the distributed optical fiber strain sensor and the diameter direction of the tank base plane. The distributed optical fiber strain sensor is used to monitor the overall deformation of the tank, and the fiber grating array strain sensor is used to accurately monitor the local part of the tank.

[0079] However, the prior art uses the optical fiber method to measure the deformation of large crude oil storage tanks. The method is to set the distributed optical fiber strain sensor in a spiral manner on the surface of the tank body to be monitored, and the fiber grating array strain sensor is fixed on the surface of the tank body to be monitored where the deformation occurs. However, this method requires manpower and time to fix the sensor on the surface of the large tank body.

[0080] The existing technology (CN114739311B) is suitable for rapid deformation monitoring of mine shafts; the equipment adopts multiple sensors to measure the initial coordinates of 2D laser radar, and then gradually lowers the 2D laser radar in the shaft; records data at different times; pre-processes the data recorded by the wheel odometer and the inertial measurement unit, calculates the wire lowering distance at different times and the posture data of the inertial measurement unit; interpolates the lowering distance data calculated by the wheel odometer and the posture data calculated by the inertial measurement unit according to the timestamp, and obtains the posture of the 2D laser radar at each timestamp; calculates the precise coordinates of the shaft wall at different depths, establishes a three-dimensional grid model of the shaft, and obtains the deformation data of the shaft; the method is safe, high in precision, low in cost, low in labor intensity, and has a large amount of measured data, which reduces and avoids injuries to surveyors caused by complex environments during shaft measurement, and greatly improves the efficiency of shaft monitoring.

[0081] However, this prior art obtains deformation data indirectly and cannot directly determine the location and extent of the deformation.

[0082] The prior art (CN114074724B) provides a wall-climbing robot suitable for the inner and outer walls of storage tanks with different curvature radii, comprising a body unit, a directional wheel drive unit and a universal wheel follower unit symmetrically arranged on both sides of the body unit from front to back, and a replaceable magnetic wheel unit; the body unit is a rectangular box-shaped structure, an array of permanent magnets is provided on the lower cover plate of the body unit, matching the replaceable magnetic wheel unit, a front side plate of the body unit is provided with a camera mounting box for fixing a front camera, and a rear camera is fixed to the rear of the upper cover plate of the body unit through a camera mounting plate; the present invention combines the body unit, the directional wheel drive unit and the universal wheel follower unit according to the specific connection relationship and position relationship defined in the present invention, so as to adjust the inclination angle according to different wall conditions, ensure the effective adsorption area and distance of the permanent magnet to the tank surface, and improve the adsorption effectiveness and safety of the robot on surfaces with different curvatures.

[0083] However, the prior art has the limitation that the robot cannot fix the recessed part with steep changes on the facade surface, and thus cannot cross the recessed defect.

[0084] The prior art (CN111854623B) provides a method and system for quickly detecting small deformations of an object. The prior art (CN114114107B) provides an experimental device for measuring small magnetostrictive deformations. The prior art (CN114878320B) provides a deformation detection mechanism, a pressure vessel detection device and a detection system. The prior art (CN103335588B) provides. The prior art (Research on the application of digital speckle method to measure the deformation of the wall of a loaded pressure vessel. Automation and Instrumentation 2012 (2), 2.) provides research on the application of digital speckle method to measure the deformation of the wall of a loaded pressure vessel. The prior art (Laser overlapping three-dimensional reconstruction of damaged blades of an aeroengine. Progress in Laser and Optoelectronics, 2020, 57 (16), 9.) provides laser overlapping three-dimensional reconstruction of damaged blades of an aeroengine. However, the above-mentioned prior art cannot simultaneously have the problem of both the measurement function and the spatial resolution of detecting the deformation of large, medium and small containers.

[0085] In summary, the existing non-contact detection technology faces the problem of being unable to simultaneously have the measurement function and the spatial resolution for detecting the deformation of large, medium and small containers.

[0086] In view of the above-mentioned defects of the prior art and the problem that deformation parts of tanks in the petrochemical and refining fields, especially small deformations, are difficult to accurately identify and locate, the present invention adopts a method of first area division and then dynamic splicing to first realize the deformation position identification in each divided sub-area, and then dynamically splice the sub-areas to realize the identification of the deformation parts in the overall area of ​​the tank.

[0087] In view of the above-mentioned defects of the prior art and the problem that it is difficult to accurately quantify the deformation parts of tanks in the petrochemical and refining fields, the present invention proposes a three-dimensional measurement method of laser structured light for measuring the surface deformation of tanks, which quantifies the degree of deformation from two levels: the projection area parameter of the deformation area and the deformation depth parameter.

[0088] Therefore, the present invention can solve the problem that the traditional tank deformation measurement technology can only obtain deformation data of a small number of observation points by point observation and then infer the overall deformation, and accurately obtain the local and overall precise deformation details. The present invention can solve the technical problems of low efficiency of tank inspection and low measurement accuracy of deformation. The present invention can solve the problem of indirectly obtaining deformation data, directly obtain the location where the tank deformation occurs, and quantitatively describe the degree of deformation.

[0089] Figure 1 A flowchart of a method for detecting a container deformation amount according to an embodiment of the present invention is shown.

[0090] like Figure 1 As shown, in step S1, the container to be tested is divided into regions around the entire container according to the structural characteristics of the container to be tested, and the sub-region division result of the container to be tested is obtained. Specifically, in step S1, for the container to be tested, Figure 2 The container full circumference area division method shown obtains the sub-area division result of the container to be tested.

[0091] Figure 2 A flowchart of the steps of obtaining the sub-region division result of the container to be tested according to an embodiment of the present invention is shown.

[0092] like Figure 2 As shown, in step S201, the original structural data of the container to be tested is obtained. Specifically, the original structural data of the container to be tested is obtained to obtain the structural characteristics of the container to be tested. Further, the original structural data record of the container to be tested is obtained, wherein the original structural data record of the container specifically includes: container diameter parameters and container height parameters.

[0093] like Figure 2 As shown, in step S202, the circumferential direction is divided. Specifically, let the diameter of the container to be tested be D, and divide the container to be tested into M equal parts along the circumferential direction, satisfying Wherein, m is the circumferential division coefficient. Further, m=1.8 or m=2.4 or m=3 or m=3.6, and the unit is the international unit of length.

[0094] like Figure 2 As shown, in step S203, the height direction is divided. Specifically, let the height of the container to be tested be H, and divide the container to be tested into N equal parts along the height direction, satisfying Wherein, n is the height direction division coefficient. Further, n=1.8 or n=2.4 or n=3 or n=3.6, and the unit is the international unit of length.

[0095] like Figure 2 As shown, in step S204, the sub-regions are marked in sequence. Specifically, after the circumferential division and the height division, the cylindrical surface of the container to be tested is divided into Q sub-regions, where Q = M × N. Further, the sub-regions at the same horizontal height are numbered in a clockwise order in the circumferential direction, and the sub-regions at the same vertical line are numbered from bottom to top in the height direction, and the sub-region division result of the container to be tested is obtained, where each sub-region of the circumferential surface of the container to be tested is numbered (M i , N k ), i=1~M, k=1~N.

[0096] Figure 3 A schematic diagram of sub-region division according to an embodiment of the present invention is shown.

[0097] like Figure 3 As shown, in step S204, the first sub-region of interest is recorded as (M1, N1), and starting from the first sub-region, the area to be tested at the same level is recorded clockwise as (M i , N1), where i = 1 to M; starting from the first sub-region, the sub-regions at the same vertical height from bottom to top are recorded as (M1, N k ), where k = 1 to N. Therefore, each sub-area of ​​the circumferential surface of the container under test is recorded as (M i , N k ), i=1~M, k=1~N.

[0098] In one embodiment, step S1 further includes, based on the result of the sub-region division, setting a splicing identification point at the boundary of each sub-region. Specifically, the splicing identification point is set at the boundary of each sub-region by the following steps: along the circumferential direction of each sub-region, a splicing identification point is set at a first distance, wherein the first distance q is the marker point coefficient; along the height direction of each sub-area, a splicing identification point is set at every second distance, where the second distance When setting the splicing identification points, only one set of splicing identification points needs to be set at the boundary of every two adjacent sub-areas. Further, q=3 or q=4 or q=5 or q=6.

[0099] like Figure 1 As shown, in step S2, based on the sub-region division result, three-dimensional laser scanning is performed on each sub-region in turn to obtain a three-dimensional point cloud model of the container to be tested. Specifically, in step S2, based on the sub-region division result, by Figure 4 The local deformation location positioning method and the container full circumference dynamic splicing method shown in the figure obtain a three-dimensional point cloud model of the container to be tested.

[0100] Figure 4 A flowchart of steps for obtaining a three-dimensional point cloud model of a container to be tested according to an embodiment of the present invention is shown.

[0101] like Figure 4 As shown, in step S401, based on the sub-region division result, three-dimensional laser scanning is performed on each sub-region in turn to obtain a sub-region point cloud data set of the container to be tested. Specifically, step S401 is a method for locating a local deformation part, and the sub-region point cloud data set of the container to be tested is obtained by the following steps:

[0102] a. For the sub-area to be scanned, set the scanning device to scan the sub-area in the order from bottom to top and from left to right. Specifically, for the selected sub-area (M i , N k ), the stripe structured light is set at a certain distance from the surface of the area to be measured, and the sub-area is scanned in a scanning order from top to bottom (or from bottom to top) and from left to right (or from right to left).

[0103] b. Adjust the relative angle between the scanning field of view and the surface of the sub-area to be scanned, and return to step a after each adjustment. Specifically, adjust the relative angle between the scanning field of view and the surface of the sub-area to be scanned, and perform steps a to b after each adjustment.

[0104] c. After scanning, a point cloud data set of the sub-region of the container to be tested is obtained. Specifically, the sub-region to be tested (M i , N k ) to obtain the complete point cloud data set of the sub-area point cloud data set of the container to be tested.

[0105] like Figure 4 As shown, in step S402, according to the sub-region point cloud data set and in combination with the splicing identification points, the container to be tested is dynamically spliced ​​around the entire circumference to obtain a three-dimensional point cloud model of the container to be tested. Specifically, step S402 is a container full circumference dynamic splicing method, further, by Figure 5 The method shown performs full-circle dynamic splicing.

[0106] Figure 5 A flowchart of the steps of full-circle dynamic splicing according to an embodiment of the present invention is shown.

[0107] like Figure 5 As shown, in step S501, based on the sub-region point cloud data set, the point cloud data of each sub-region is clipped, and the point cloud data outside each sub-region is clipped to obtain the clipping result data of each sub-region.

[0108] Specifically, the clipping result data of each sub-region is obtained through the following steps: record the current sub-region (M i , N k ) The corresponding point cloud data set is Q all ; Take the splicing identification point corresponding to the current sub-region as the boundary, and mark the point cloud data set outside the boundary as Q out , the point cloud data set within the boundary is Q in ; Execute the point cloud dataset operation Q of the current sub-area out =Q all -Q in , trim the point cloud data outside the current sub-region to obtain the trimming result data corresponding to the current sub-region.

[0109] like Figure 5 As shown, in step S502, for each sub-region, the clipping result data is optimized for point cloud data to obtain the optimized result data of each sub-region. Specifically, in step S502, for each sub-region, by Figure 6 The point cloud data optimization method shown in FIG. 1 is used to obtain the optimization result data of each sub-area.

[0110] Figure 6 A flowchart of the steps of a point cloud data optimization method according to an embodiment of the present invention is shown.

[0111] like Figure 6 As shown in FIG. 1 , the optimization result data of each sub-area is obtained by the following steps: the central axis of the container to be tested is denoted as O, and the deformation amount of the container to be tested perpendicular to the central axis O is Δd, where Δd is the convex height or concave depth of the container to be tested; for the convex deformation, the point cloud at the farthest vertical distance from the central axis O, its distance from the central axis O is denoted as The number of convex tip point clouds is recorded as R1. If R1 satisfies the formula: S is the point cloud number threshold, then it is determined In the range, The data within the radius are accidental point cloud data and are deleted, K is the radius coefficient; for the concave deformation, the point cloud at the closest vertical distance from the central axis O is at a distance from the central axis O of The number of concave tip point clouds is recorded as R2. If R2 satisfies the formula: It is determined In the range, The data within the radius is considered as accidentally appearing point cloud data and is deleted. Further, S=1-100, S is an integer. K=5 or K=6 or K=7 or K=8 or K=9 or K=10.

[0112] like Figure 5 As shown, in step S503, based on the optimization result data and in combination with the splicing identification points, the point cloud data between the sub-areas are dynamically spliced ​​to obtain a three-dimensional point cloud model of the entire circumference of the container to be tested.

[0113] Specifically, the three-dimensional point cloud model of the entire circumference of the container to be tested is obtained by splicing the following steps: i , N k ) and sub-region (M i+1 , N k ) between each circumferential splicing identification point is Δe i , then the cumulative error of the two regions in the circumferential direction is Record sub-area (M i , N k ) and sub-region (M i , N k+1 ) between each height splicing recognition point is Δe k , then the cumulative error of the two regions in the height direction is Calculate the sub-area (M i , N k )’s cumulative error of splicing recognition points is like δ is the stitching error threshold, then the sub-region (M i , N k ) is successfully spliced ​​with the adjacent sub-region; sub-region (M i , N k ) After successful splicing, move to the next splicing sub-area (M i+1 , N k ) or (M i , N k+1 ), determine the sub-region (M i+1 , N k ) or (M i , N k+1 ) is successfully spliced ​​with the adjacent sub-region, and so on, until all sub-regions are successfully spliced ​​to obtain a three-dimensional point cloud model. Further, δ = 1 / 20r, where r is the radius of the splicing identification point.

[0114] like Figure 1As shown, in step S3, for the three-dimensional point cloud model, the projection area fitting and the depression depth measurement of the deformation region are respectively performed to obtain the projection area parameter and the deformation depth parameter of the deformation region. Specifically, step S3 also includes: based on the projection area parameter of the deformation region, the position of the deformation region is identified. Further, in step S3, for the three-dimensional point cloud model, by Figure 7 The method shown in the figure obtains the projection area parameter, deformation location and deformation depth parameter of the deformation area.

[0115] Figure 7 A flowchart of the steps of obtaining the projection area parameter, deformation location and deformation depth parameter of the deformation region according to an embodiment of the present invention is shown.

[0116] like Figure 7 As shown, in step S701, the projection area of ​​the deformation region is fitted. Specifically, step S701 is a method for fitting the projection area of ​​the deformation region. Further, by Figure 8 The method shown is used to fit the projection area of ​​the deformation region.

[0117] Figure 8 A flowchart showing the steps of projected area fitting of the deformation occurrence region according to an embodiment of the present invention is shown.

[0118] like Figure 8 As shown, in step S801, the 3D point cloud model is expanded along the circumference. Specifically, the 3D point cloud model is expanded along the circumference, and the long side of the expanded rectangle is the container perimeter, marked as the X axis, and the short side of the expanded rectangle is the container height, marked as the Y axis. The name of the expanded sub-area (M i , N k ) is unchanged.

[0119] like Figure 8 As shown, in step S802, a Z-direction base plane is constructed. Specifically, the average value of all point cloud data of the unfolded rectangle in the Z axis is calculated, and it is marked as the base plane of the unfolded rectangle. That is, the average value of the Z-direction coordinates of all point cloud data of the rectangle is taken, and it is recorded as the Z-direction base plane of the unfolded rectangle.

[0120] like Figure 8 As shown, in step S803, the Z direction base plane traverses the point cloud data. Specifically, the parts above and below the base plane are recorded as convex deformation and concave deformation respectively, and the traversal starts from the point cloud data farthest from the base plane until the Z coordinate value of the traversed point cloud data satisfies: Z i -Z O ≤∈(step S804), then stop traversal (step S805), where Z iis the Z coordinate value of the i-th point cloud data, Z O is the Z coordinate value of the point cloud data at the base plane, ∈ is the deformation threshold. Further, ∈=0.01 or ∈=0.1 or ∈=0.2 or ∈=0.5.

[0121] like Figure 8 As shown, in step S806, the projection contour surrounded by the point cloud where the traversal is stopped is recorded. Specifically, the projection contour surrounded by the point cloud where the traversal is stopped is recorded, and the projection contour is the range where the deformation occurs.

[0122] like Figure 8 As shown, in step S807, a geometric figure is used to fit the projection contour. Specifically, a geometric figure is used to fit the projection contour, and the image area obtained after fitting is the projection size of the deformation occurrence area. Further, the geometric figure used to fit the projection contour is any one of a rectangle, a circle, and a triangle, or any combination of any one of them.

[0123] like Figure 7 As shown, in step S702, the deformation occurrence position is identified. Specifically, step S702 is a method for identifying the position of the deformation occurrence area, and the position of the deformation occurrence area is identified by the following steps: determining the shape contour of the deformation area by the projection area parameter, marking the centroid position of the shape contour of the deformation area; marking the sub-area where the centroid position is located as the deformation occurrence position.

[0124] like Figure 7 As shown, in step S703, the depression depth of the deformation region is measured. Specifically, step S703 is a method for measuring the depression depth of the deformation region, and the depression depth of the deformation region is measured by the following steps: Figure 3 As shown, the deformation contour range of the concave part in the deformation contour image is selected; the point cloud farthest from the base plane within the deformation contour range of the concave part is determined, and the distance Z between the point cloud and the base plane in the Z axis direction is read. imax , record Z imax is the depth of the depression in the deformation area. Further, based on the unfolded rectangular 3D point cloud surface, the deformation contour range of the depression is selected, and the point cloud farthest from the base plane within the range of the deformation contour is selected, and its Z direction distance value Z from the base plane is read. imax , which is the depth value where the concave deformation occurs.

[0125] The present invention adopts a non-contact optical detection method. During detection, the surface of the tank body to be detected is scanned and imaged by three-dimensional laser scanning at a certain distance from the tank body; it is not affected by the material of the tank body, surface protrusions or depressions.

[0126] The present invention adopts a two-step method of dividing position recognition and combining it with three-dimensional size measurement of the deformed part to achieve accurate positioning of the deformed part; the degree of deformation is quantitatively judged according to the depression depth of the deformed part and the edge projection area of ​​the deformed part.

[0127] The present invention adopts a non-contact three-dimensional detection method without the need for wiring or sensor installation. The tank body is divided into multiple sub-areas, splicing identification points are set, and dynamic splicing is performed based on the splicing identification points. The sub-areas are spliced ​​into a three-dimensional model of the entire tank body, thereby realizing the measurement of the three-dimensional tank body diameter and local deformation.

[0128] The present invention can be widely used in the optical detection and measurement of deformation of large and medium-sized equipment in the fields of petroleum and chemical industry. The method is widely applicable to the materials of the equipment itself. The proposed detection method based on the measurement of the three-dimensional deformation of the equipment is conducive to the rapid positioning of the deformation part and the quantitative evaluation of the three-dimensional geometric characteristics of the deformation part, which is of great significance for the equipment safety service evaluation technology.

[0129] The method for detecting the deformation amount of a container provided by the present invention can also be used in conjunction with a computer-readable storage medium, on which a computer program is stored, and the computer program is executed to run the method for detecting the deformation amount of a container. The computer program can run computer instructions, and the computer instructions include computer program codes, which can be in source code form, object code form, executable file or some intermediate form, etc.

[0130] Computer-readable storage media may include: any entity or device that can carry computer program code, recording media, USB flash drives, mobile hard disks, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0131] It should be noted that the content contained in computer-readable storage media can be appropriately increased or decreased based on the requirements of legislation and patent practices in the jurisdiction. For example, in some jurisdictions, based on legislation and patent practices, computer-readable storage media do not include electrical carrier signals and telecommunications signals.

[0132] According to another aspect of the present invention, a device for detecting a container deformation amount is provided, which executes a method for detecting a container deformation amount. The device includes: a sub-area division module, a three-dimensional point cloud model module, and a projection area parameter and deformation depth parameter module.

[0133] The sub-area division module is used to divide the container into full-circle areas according to the structural features of the container to be tested, and obtain the sub-area division results of the container to be tested. The three-dimensional point cloud model module is used to perform three-dimensional laser scanning on each sub-area in turn based on the sub-area division results to obtain a three-dimensional point cloud model of the container to be tested. The projection area parameter and deformation depth parameter module are used to perform projection area fitting and depression depth measurement of the deformation area on the three-dimensional point cloud model, and obtain the projection area parameter and deformation depth parameter of the deformation area.

[0134] In one embodiment, a gas buffer tank with a diameter of 7 m and a height of 7 m is used as a container to be tested, and a method for detecting the deformation amount of a container provided by the present invention is used to detect the deformation degree of the entire circumference of the cylindrical surface, and the steps are as follows:

[0135] S1. Divide the gas buffer tank into 12 equal parts along the circumferential direction;

[0136] S2. Divide the gas buffer tank into 4 equal parts along the height direction;

[0137] S3. After division, the surface of the gas buffer tank to be tested is divided into 48 sub-areas in total;

[0138] S4. A marking point is arranged at a distance of 0.3m between the splicing identification points in the circumferential direction of each sub-area;

[0139] S5. A marking point is arranged at every 0.3m interval of the splicing identification points in the axial direction of each sub-area;

[0140] S6, use stripe structured light to scan from sub-area (M1, N1) to sub-area (M1, N1) at a certain distance from the surface of the gas buffer tank. 12 , N4);

[0141] S7, obtaining a point cloud data set of the entire circumference of the cylindrical surface of the gas buffer tank;

[0142] S8, sequentially divide the sub-areas (M1, N1) to (M 12 , N4) to trim the point cloud data of the sub-area outside the X and Y directions;

[0143] S9. Let the deformation in the sub-region perpendicular to the central axis O be Δd, and optimize the farthest point cloud data in the Z direction of each sub-region:

[0144] S9.1, take K=5, S=10;

[0145] S9.2 If

[0146] S9.3, remove the point cloud data within the radius of Δd / 5;

[0147] S9.4, the remaining point cloud data is the optimized point cloud data set;

[0148] S10, stitching the cropped and optimized 48 sub-region point cloud data, with a cumulative stitching error of 1.0 mm;

[0149] S11, unfolding the three-dimensional container model along the circumferential direction into a rectangular shape;

[0150] S12, taking the average value of the Z-direction coordinates of all point cloud data of the rectangle, and recording it as the base plane of the unfolded rectangle;

[0151] S13, the parts above and below the base plane are recorded as convex deformation and concave deformation, and the traversal starts from the point cloud data farthest from the base plane until the Z coordinate of the traversed point cloud data satisfies: Z i -Z O ≤0.5, stop traversal;

[0152] S14, recording the projection contour shape enclosed by the point cloud where the traversal stops, and the shape is the range where the deformation occurs;

[0153] S15, using multiple rectangles to fit the projection contour shape, and the image area obtained after fitting is the projection size where the deformation occurs;

[0154] S16, marking the centroid position of the deformed area based on the shape contour;

[0155] S17, the sub-region where the centroid is located is the location where the deformation occurs;

[0156] S18, based on the unfolded rectangular three-dimensional point cloud surface, selecting a deformation contour range of the concave part;

[0157] S19, select the point cloud farthest from the base plane within the range of the deformation contour, and read the Z direction distance value Z from the base plane imax , which is the depth value where the concave deformation occurs.

[0158] In one embodiment, a horizontal salt mixer with a diameter of 0.6 m and a length of 3.74 m is used as a container to be tested, and a method for detecting the deformation amount of a container provided by the present invention is used to detect the deformation degree of the entire circumference of the cylindrical surface, and the steps are as follows:

[0159] S1. Divide the horizontal salt mixer into three equal parts along the circumferential direction;

[0160] S2, dividing the horizontal salt mixer into 4 equal parts along the height direction;

[0161] S3. After the division, the surface of the horizontal gas-salting mixer to be tested is divided into 12 sub-areas;

[0162] S4. A marking point is arranged at a distance of 0.18m between the splicing identification points in each sub-area along the circumferential direction;

[0163] S5. A marking point is arranged at every 0.18m interval for the splicing identification points in the axial direction of each sub-area;

[0164] S6, using stripe structured light at a certain distance from the surface of the gas buffer tank, scanning from sub-area (M1, N1) to sub-area (M3, N4) in sequence;

[0165] S7, obtaining a point cloud data set of the entire circumference of the cylindrical surface of the horizontal salt mixer;

[0166] S8, sequentially trimming the point cloud data of the sub-areas (M1, N1) to (M3, N4), and trimming the point cloud data of the sub-areas outside the X and Y directions;

[0167] S9. Let the deformation in the sub-region perpendicular to the central axis O be Δd, and optimize the farthest point cloud data in the Z direction of each sub-region:

[0168] S9.1, take K=10, S=1;

[0169] S9.2 If

[0170] S9.3, remove the point cloud data within the radius of Δd / 10;

[0171] S9.4, the remaining point cloud data is the optimized point cloud data set;

[0172] S10, stitching the cropped and optimized 12 sub-area point cloud data, with a cumulative stitching error of 0.5 mm;

[0173] S11, unfolding the three-dimensional horizontal salt mixer model along the circumferential direction into a rectangular shape;

[0174] S12, taking the average value of the Z-direction coordinates of all point cloud data of the rectangle, and recording it as the base plane of the unfolded rectangle;

[0175] S13, the parts above and below the base plane are recorded as convex deformation and concave deformation, and the traversal starts from the point cloud data farthest from the base plane until the Z coordinate of the traversed point cloud data satisfies: Z i -Z O ≤0.01, stop traversal;

[0176] S14, recording the projection contour shape enclosed by the point cloud where the traversal stops, and the shape is the range where the deformation occurs;

[0177] S15. Different from the gas buffer tank embodiment, in order to reduce the error of the projection area size, this embodiment uses two geometric figures, a rectangle combined with a circle, to fit the projection contour shape, and the image area obtained after fitting is the projection size where the deformation occurs;

[0178] S16, calculating and marking the centroid position of the deformed area based on the shape contour;

[0179] S17, the sub-region where the centroid is located is the location where the deformation occurs;

[0180] S18, based on the unfolded rectangular three-dimensional point cloud surface, selecting a deformation contour range of the concave part;

[0181] S19, select the point cloud farthest from the base plane within the range of the deformation contour, and read the Z direction distance value Z from the base plane imax , which is the depth value of the concave deformation of the horizontal container.

[0182] In one embodiment, a small container (such as an oxygen, nitrogen, or helium cylinder) is used as a container to be tested, and a method for detecting the deformation of a container provided by the present invention is used to detect the degree of deformation after being squeezed. The steps are as follows:

[0183] First, the gas cylinder to be tested is divided according to the structural area: the part above the bottle hoop is defined as sub-area 1; the cylindrical part below the bottle hoop is defined as sub-area 2; and the bottom surface of the bottle bottom is defined as sub-area 3. Among them, for the bottle bottom sub-area 3, its area does not need to be further divided, and it does not need to be expanded circumferentially, so it can be directly executed according to steps S12-S19 of the embodiment of the horizontal salt mixer.

[0184] For the sub-area 2 of the cylindrical part below the bottle hoop, the deformation degree detection process is specifically described as follows:

[0185] S1, dividing the sub-area 2 below the hoop of the small gas cylinder into three equal parts along the circumferential direction;

[0186] S2, dividing the sub-area 2 below the hoop of the small gas cylinder into three equal parts along the height direction;

[0187] S3. After division, the surface of the gas buffer tank to be tested is divided into 9 sub-areas in total;

[0188] S4. A marking point is arranged at a distance of 0.1m between the splicing identification points in each sub-area along the circumferential direction;

[0189] S5. A marking point is arranged at every 0.1m interval of the splicing identification points in the axial direction of each sub-area;

[0190] S6, using stripe structured light at a certain distance from the surface of the gas buffer tank, scanning from sub-area (M1, N1) to sub-area (M3, N3) in sequence;

[0191] S7, obtaining a point cloud data set of the entire circumference of the cylindrical surface of the gas bottle area 2;

[0192] S8, sequentially trimming the point cloud data of the sub-regions (M1, N1) to (M3, N3), and trimming the point cloud data of the sub-regions outside the X and Y directions;

[0193] S9. Let the deformation in the sub-region perpendicular to the central axis O be Δd, and optimize the farthest point cloud data in the Z direction of each sub-region:

[0194] S9.1, take K=10, S=1;

[0195] S9.2 If

[0196] S9.3, remove the point cloud data within the radius of Δd / 10;

[0197] S9.4, the remaining point cloud data is the optimized point cloud data set;

[0198] S10, stitching the cropped and optimized 9 sub-area point cloud data, with a cumulative stitching error of 0.1 mm;

[0199] S11, unfolding the three-dimensional gas cylinder model along the circumferential direction into a rectangular shape;

[0200] S12, taking the average value of the Z-direction coordinates of all point cloud data of the rectangle, and recording it as the base plane of the unfolded rectangle;

[0201] S13, the parts above and below the base plane are recorded as convex deformation and concave deformation, and the traversal starts from the point cloud data farthest from the base plane until the Z coordinate of the traversed point cloud data satisfies: Z i -Z O ≤0.01, then stop traversal;

[0202] S14, recording the projection contour shape enclosed by the point cloud where the traversal stops, and the shape is the range where the deformation occurs;

[0203] S15. Different from any of the above embodiments, this embodiment adopts a method of fitting a rectangle, a circle and a triangle to fit the projection contour shape, and the image area obtained after fitting is the projection size where the deformation occurs;

[0204] S16, marking the centroid position of the deformed area based on the shape contour;

[0205] S17, the sub-region where the centroid is located is the location where the deformation occurs;

[0206] S18, based on the unfolded rectangular three-dimensional point cloud surface, selecting a deformation contour range of the concave part;

[0207] S19, select the point cloud farthest from the base plane within the range of the deformation contour, and read the Z direction distance value Z from the base plane imax , which is the depth value where the concave deformation occurs.

[0208] In summary, the present invention provides a method for detecting the deformation of a container, which has the following advantages compared with the prior art:

[0209] 1) In order to solve the problem that deformation parts of containers in the petrochemical and refining fields, especially small deformations, are difficult to accurately identify and locate, the present invention adopts a method of first dividing the area and then dynamically splicing it, so as to first realize the deformation position identification in each divided sub-area, and then realize the identification of the deformation parts in the overall area of ​​the container through dynamic splicing of the sub-areas.

[0210] 2) In order to solve the problem that it is difficult to accurately quantify the deformation parts of containers in the petrochemical and refining fields, the present invention proposes a three-dimensional measurement method of laser structured light for measuring the surface deformation of containers, which quantifies the degree of deformation from two aspects: the projection area parameter of the deformation area and the deformation depth parameter.

[0211] It should be understood that the embodiments disclosed in the present invention are not limited to the specific structures, processing steps or materials disclosed herein, but should be extended to equivalent substitutions of these features understood by ordinary technicians in the relevant field. It should also be understood that the terms used herein are only used for the purpose of describing specific embodiments and are not meant to be limiting.

[0212] In the description of the present invention, unless otherwise specified, "plurality" means two or more than two; the orientations or positional relationships indicated by the terms "upper", "lower", "left", "right", "inner", "outer", "front end", "rear end", "head", "tail", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0213] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0214] Certain terms are used throughout this application document to indicate specific system components. As those skilled in the art will recognize, different names can usually be used to indicate the same components, so this application document is not intended to distinguish those components that are only different in name but not in function. In this application document, the terms "comprise", "include" and "have" are used in an open form, and therefore should be interpreted as meaning "including but not limited to...". In addition, the terms "substantially", "substantially" or "approximately" that may be used in this article relate to the tolerances of the corresponding terms accepted by the industry. The term "coupling" as may be used in this article includes direct coupling and indirect coupling via other components, elements, circuits, or modules, wherein for indirect coupling, the components, elements, circuits, or modules between them do not change the information of the signal but can adjust its current level, voltage level, and / or power level. Inferred coupling (for example, one of the elements is coupled to another element by inference) includes direct and indirect coupling between two elements in the same way as "coupling".

[0215] The "one embodiment" or "embodiment" mentioned in the specification means that the specific features, structures or characteristics described in conjunction with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrases "one embodiment" or "embodiment" appearing in various places throughout the specification do not necessarily refer to the same embodiment.

[0216] The embodiments of the present invention are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0217] Although the embodiments disclosed in the present invention are as above, the contents described are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A method for detecting the deformation of a container, characterized in that: The method comprises: S1. Divide the container around the entire perimeter of the container according to the structural characteristics of the container to be tested, and obtain the sub-area division result of the container to be tested; S2. Based on the sub-region division result, perform three-dimensional laser scanning on each sub-region in turn to obtain a three-dimensional point cloud model of the container to be tested; S3. For the three-dimensional point cloud model, respectively perform projection area fitting and depression depth measurement on the deformation region to obtain projection area parameters and deformation depth parameters of the deformation region.

2. A method for detecting the deformation of a container according to claim 1, characterized in that: Step S1 comprises: Acquiring original structural data of the container to be tested to obtain the structural features of the container to be tested; Let the diameter of the container to be tested be D, and divide the container to be tested into M equal parts along the circumferential direction, satisfying Among them, m is the circumferential division coefficient; Let the height of the container to be tested be H, and divide the container to be tested into N equal parts along the height direction, satisfying Where n is the height direction division coefficient; After the circumferential division and the height division, the cylindrical surface of the container to be tested is divided into Q sub-areas, where Q = M × N; The sub-regions at the same horizontal height are numbered in a clockwise order in the circumferential direction, and the sub-regions at the same vertical line are numbered in a bottom-up order in the height direction to obtain the sub-region division result of the container to be tested, wherein each sub-region on the circumferential surface of the container to be tested is numbered as (M i , N k ), i=1~M, k=1~N.

3. A method for detecting the deformation of a container as claimed in claim 2, characterized in that: Step S1 further includes, based on the sub-region division result, setting a splicing identification point at the boundary of each sub-region, which includes: Along the circumferential direction of each sub-area, a splicing identification point is set at a first distance interval, wherein the first distance q is the landmark coefficient; Along the height direction of each sub-area, a splicing identification point is set at every second distance, wherein the second distance When setting the splicing identification points, only one set of splicing identification points needs to be set at the boundary between every two adjacent sub-areas.

4. A method for detecting the deformation of a container as claimed in claim 3, characterized in that: Step S2 comprises: Based on the sub-region division result, three-dimensional laser scanning is performed on each sub-region in turn to obtain a sub-region point cloud data set of the container to be tested; According to the sub-region point cloud data set and in combination with the splicing identification points, the container to be tested is dynamically spliced ​​around the entire circumference to obtain the three-dimensional point cloud model of the container to be tested.

5. A method for detecting the deformation of a container as claimed in claim 4, characterized in that: The sub-region point cloud data set of the container to be tested is obtained by the following steps: a. For the sub-area to be scanned, set the scanning device and scan the sub-area in the order from bottom to top and from left to right; b. Adjust the relative angle between the scanning field of view and the surface of the sub-area to be scanned, and return to step a after each adjustment; c. After the scanning is completed, a point cloud data set of the sub-region of the container to be tested is obtained.

6. A method for detecting the deformation of a container as claimed in claim 4 or 5, characterized in that: Perform full-circle dynamic splicing by following the steps below: Based on the sub-region point cloud data set, the point cloud data of each sub-region is clipped, and the point cloud data outside each sub-region is clipped to obtain clipping result data of each sub-region; For each sub-region, performing point cloud data optimization on the clipping result data to obtain optimized result data of each sub-region; According to the optimization result data and in combination with the splicing identification points, the point cloud data between the sub-areas are dynamically spliced ​​to obtain the three-dimensional point cloud model of the entire circumference of the container to be tested.

7. A method for detecting the deformation of a container as claimed in claim 6, characterized in that: The clipping result data of each sub-area is obtained by the following steps: The point cloud data set corresponding to the current sub-region is recorded as Q all ; The splicing identification point corresponding to the current sub-region is taken as the boundary, and the point cloud data set outside the marked boundary is Q out , the point cloud data set within the boundary is Q in ; Execute the point cloud dataset operation Q of the current sub-area out =Q all -Q in , trim the point cloud data outside the current sub-region to obtain the trimming result data corresponding to the current sub-region.

8. A method for detecting the deformation of a container according to claim 6 or 7, characterized in that: The optimization result data of each sub-area is obtained through the following steps: Let the central axis of the container to be tested be O, then the deformation amount of the container to be tested perpendicular to the central axis O is Δd, where Δd is the convex height or concave depth of the container to be tested; For the convex deformation, the point cloud at the farthest vertical distance from the central axis O is recorded as The number of convex tip point clouds is recorded as R1. If R1 satisfies the formula: S is the point cloud number threshold, then it is determined In the range, The data within the radius are accidental point cloud data and are deleted, and K is the radius coefficient; For the concave deformation, the point cloud at the closest vertical distance from the central axis O has a distance from the central axis O of The number of concave tip point clouds is recorded as R2. If R2 satisfies the formula: It is determined In the range, The data within the radius is considered as accidental point cloud data and is deleted.

9. A method for detecting the deformation of a container according to any one of claims 6 to 8, characterized in that: The three-dimensional point cloud model of the entire circumference of the container to be tested is obtained by splicing the following steps: Record sub-area (M i , N k ) and sub-region (M i+1 , N k ) between each circumferential splicing identification point is Δe i , then the cumulative error of the two regions in the circumferential direction is Record sub-area (M i , N k ) and sub-region (M i , N k+1 ) between each height splicing recognition point is Δe k , then the cumulative error of the two regions in the height direction is Calculate the sub-area (M i , N k )’s cumulative error of splicing recognition points is like δ is the stitching error threshold, then the sub-region (M i , N k ) is successfully spliced ​​with the adjacent sub-region; Sub-area (M i , N k ) After successful splicing, move to the next splicing sub-area (M i+1 , N k ) or (M i , N k+1 ), determine the sub-region (M i+1 , N k ) or (M i , N k+1 ) is successfully spliced ​​with the adjacent sub-regions, and so on, until all sub-regions are successfully spliced ​​to obtain the three-dimensional point cloud model.

10. A method for detecting the deformation of a container according to any one of claims 1 to 9, characterized in that: In step S3, the projection area fitting of the deformation occurrence area is performed through the following steps: The three-dimensional point cloud model is expanded along the circumferential direction, and the long side of the expanded rectangle is the perimeter of the container, marked as the X-axis, and the short side of the expanded rectangle is the height of the container, marked as the Y-axis; Calculate the average value of all point cloud data of the unfolded rectangle on the Z axis and mark it as the base plane of the unfolded rectangle; The parts above and below the base plane are recorded as convex deformation and concave deformation respectively, and the traversal starts from the point cloud data farthest from the base plane until the Z coordinate value of the traversed point cloud data satisfies: Z i -Z O ≤∈, then stop traversal, where Z i is the Z coordinate value of the i-th point cloud data, Z O is the Z coordinate value of the point cloud data at the base plane, ∈ is the deformation threshold; Record the projection contour surrounded by the point cloud where traversal stops, and the projection contour is the range where the deformation occurs; The projection contour is fitted by using geometric figures, and the deformation contour image area obtained after fitting is the projection size of the deformation occurrence area.

11. A method for detecting a container deformation amount according to any one of claims 1 to 10, characterized in that: Step S3 further includes: based on the projection area parameter of the deformation area, identifying the position of the deformation occurrence area, which includes: Determine the shape contour of the deformation area by using the projection area parameter, and mark the centroid position of the shape contour of the deformation area; The sub-region where the centroid is located is marked as the deformation occurrence position.

12. A method for detecting a container deformation amount according to any one of claims 10 to 11, characterized in that: In step S3, the depression depth of the deformation occurrence area is measured by the following steps: Selecting a deformation contour range of a concave portion in the deformation contour image; Determine the point cloud farthest from the base plane within the deformation contour range of the concave part, and read the distance Z between the point cloud and the base plane in the Z-axis direction. imax , record Z imax is the depth of the depression in the deformation area.

13. A storage medium, characterized in that: It contains a series of instructions for executing the method steps as claimed in any one of claims 1-12.

14. A device for detecting the deformation of a container, characterized in that: The method according to any one of claims 1 to 12 is performed, wherein the device comprises: A sub-region division module is used to divide the container into full-circle regions according to the structural characteristics of the container to be tested, and obtain a sub-region division result of the container to be tested; A three-dimensional point cloud model module, which is used to perform three-dimensional laser scanning on each sub-area in turn based on the sub-area division result to obtain a three-dimensional point cloud model of the container to be tested; The projection area parameter and deformation depth parameter module is used to perform projection area fitting and depression depth measurement of the deformation area for the three-dimensional point cloud model, so as to obtain the projection area parameter and deformation depth parameter of the deformation area.

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