CN114719792A - Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface - Google Patents

Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface Download PDF

Info

Publication number
CN114719792A
CN114719792A CN202210300941.1A CN202210300941A CN114719792A CN 114719792 A CN114719792 A CN 114719792A CN 202210300941 A CN202210300941 A CN 202210300941A CN 114719792 A CN114719792 A CN 114719792A
Authority
CN
China
Prior art keywords
scanning
point
measurement
measuring
boundary
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202210300941.1A
Other languages
Chinese (zh)
Other versions
CN114719792B (en
Inventor
杨秀仁
林放
廖翌棋
黄美群
李天升
彭智勇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Urban Construction Design and Development Group Co Ltd
Original Assignee
Beijing Urban Construction Design and Development Group Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Urban Construction Design and Development Group Co Ltd filed Critical Beijing Urban Construction Design and Development Group Co Ltd
Priority to CN202210300941.1A priority Critical patent/CN114719792B/en
Priority to PCT/CN2022/083579 priority patent/WO2023178713A1/en
Priority to JP2023523264A priority patent/JP2024519633A/en
Publication of CN114719792A publication Critical patent/CN114719792A/en
Application granted granted Critical
Publication of CN114719792B publication Critical patent/CN114719792B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
    • G01B11/303—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces using photoelectric detection means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
    • G01B11/2518—Projection by scanning of the object
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8883—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges involving the calculation of gauges, generating models
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Signal Processing (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)

Abstract

A system and a method for intelligent scanning of manufacturing precision and automatic error identification of prefabricated part splicing surfaces are characterized in that a portal frame type walking structure is adopted, a multidirectional moving motor and a track are mounted on a portal frame, the measuring work of measuring surfaces in any shapes can be completed, various sensors are mounted on the portal frame, the temperature and the humidity of the track, the portal frame and air are monitored in real time, the measuring result is corrected through the temperature and humidity monitoring result, the system can work under the condition of complex climate without influencing the precision, and in addition, a theoretical model of a target scanning component is taken as reference, various influencing factors are processed from data, and the measured data are processed by an algorithm. Firstly, boundary data of a target scanning component is quickly found out by utilizing methods such as successive approximation, shadow shape following and the like, and then influence factors are eliminated step by utilizing algorithm means such as a correlation search algorithm, a theoretical model reference method, an overall trend deduction method and the like, so that the calculation of the manufacturing precision of the prefabricated component splicing surface is completed.

Description

Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface
Technical Field
The invention relates to the technical field of intelligent scanning of prefabricated parts with an assembled structure, in particular to an intelligent scanning and automatic error identification system and method for assembling surfaces of prefabricated parts.
Background
Aiming at some assembled ground structures such as box-shaped beams and T-shaped beams, the requirement on assembling quality is not high under the condition that most prefabricated parts are not required to be assembled, the requirement on manufacturing precision can be properly relaxed, and the requirement can be met by measuring the manufacturing precision of the prefabricated parts by using the traditional method such as a direct measuring method, a running rule, a clearance gauge and the like. For large-scale fabricated structures, such as fabricated subway station structures, large-size shield segments and the like, prefabricated parts of the fabricated structures generally have the characteristics of large volume, thick structure, inconsistent and irregular shape and the like. In addition, the assembled structure has high requirements on water resistance, seam splicing width and loading load, and the quality of the prefabricated part has great influence on the construction process, splicing quality, water resistance and the like of the assembled structure engineering. Moreover, the unevenness of the assembling surface of the prefabricated part can cause the assembling of the surface to be unsynchronized, and the part is easily damaged by larger local pressurizing load.
The prefabricated part production department pays more and more attention to the production quality of the prefabricated parts, and the quality of the prefabricated parts needs to be detected before leaving factories. However, the conventional prefabricated part cannot be completely implemented on a large part by using a fixture and a running rule measuring method, the problems that the traditional caliper is not enough in size, the abdomen of the part cannot be measured and the like, and the manual operation cannot be comprehensively detected often occur, so that the measuring precision and the purpose cannot be achieved. Under the condition that the assembly structure has high requirements on the flatness of the assembly surface of the prefabricated part, the prior art has no method for accurately measuring the manufacturing precision of the assembly surface of the large-sized part, so that the manufacturing precision of the assembly surface is influenced due to the deformation and bulging of a mould and other reasons after the early large-sized assembly type underground structure prefabricated part leaves a factory, manufacturing errors are caused, the conditions of the non-assembly of the prefabricated part, the non-tight pulling of joints and the like occur at a plurality of engineering assembly sites, and the member cannot be used on site. Therefore, it is urgently needed to develop an intelligent detection system and method for prefabricated parts to detect errors of assembled surfaces of the prefabricated parts and identify error areas.
The prefabricated part assembling surface manufacturing error mainly refers to an error influencing assembling of an assembled structure, such as a component bulge area, and the problems of untight assembling and tension of joints of the assembling surface are easily caused. Although the assembly surface has local bulges, the edge contour of the assembly surface of the whole component still keeps accurate, and the edge contour can be used as a reference condition and a basic step of intelligent scanning to further judge whether the component bulges and accurately find a bulge area. Because large-scale prefabricated component has characteristics such as bulky, heavy, boundary profile is irregular, can't accurate control component arrange in hoist and mount on intelligent scanning platform put the angle. Therefore, under the conditions of uncertain component placement postures and irregular boundary profiles, the conventional identification method is too slow to be used on large-volume components, so that the requirement cannot be met, and an efficient boundary capture method which can be suitable for arbitrary placement and an algorithm of coupling a theoretical model with an actual placement posture are urgently needed.
In addition, when the precast concrete member is produced, phenomena such as pitted surface, honeycombs, holes, particles and the like may occur on the surface of the precast concrete member due to untight joints of the formwork, unclean surface of the formwork, adhesion during formwork demolding, insufficient vibration, no discharge of air bubbles and the like. The defects are different from the manufacturing errors of the assembling surfaces of the prefabricated parts of the assembled structure concrete, the fitting and the splicing among the prefabricated parts on the assembling site of the assembled structure are not influenced, the defects are used without hindrance, but the large influence is generated when the manufacturing precision of the assembling surfaces of the prefabricated parts is detected in an intelligent scanning mode, so that the inaccuracy of analysis data and the misleading of the whole analysis result are caused, and the local concrete defects are called. And for local defect points, directly removing the local defect points from the measured data set. The effective elimination of local defects is the key for ensuring that the detection work of the assembling surface of the concrete prefabricated part is completed quickly, accurately and efficiently in an intelligent scanning mode.
In addition, because large prefabricated components are large in size and complex in structure, a detection device can be placed outdoors, and the deformation of a large scanning device and other problems can be caused due to the influence of factors such as temperature change, humidity change and the like, so that errors are generated in measurement results under different climatic conditions, and the requirements of field practical application cannot be met. Need research and development special check out test set, can detect large-scale prefabricated assembled structure prefabricated component concatenation face preparation precision to can adapt to different environmental condition and not influence and equip the detection precision.
Therefore, the assembly surface manufacturing precision detection has the difficulty of the equipment and the system algorithm at present, and the assembly surface manufacturing precision is ensured, so that the method is the key for implementing the construction of the assembled underground structure.
Therefore, in view of the above drawbacks, the designer of the present invention develops and designs a system and a method for intelligent scanning and automatic error identification of a splicing surface of a prefabricated component by taking into account experience and achievement of related industries for many years through careful research and design, so as to overcome the above drawbacks.
Disclosure of Invention
The invention aims to provide a system and a method for intelligently scanning the splicing surface of a prefabricated part and automatically identifying an error, which have the advantages of simple structure, convenience in operation, capability of effectively overcoming the defects of the prior art, automatic identification and scanning of the prefabricated part, high precision, high efficiency and more innovation.
In order to achieve the purpose, the invention discloses a method for intelligently scanning the manufacturing precision of a prefabricated part assembling surface and automatically identifying errors, which is characterized by comprising the following steps of:
the method comprises the following steps: a preparation step, namely hoisting a target scanning component into a measurement area on a component scanning table;
step two: starting, namely opening an electric roller shutter door of a warehouse, starting a scanning gantry, and starting scanning detection;
step three: adjusting the height of the vertical walking tray to make the light of the laser measuring equipment close to the height of the upper surface of the component scanning table;
step four: scanning the gantry to move forwards from the warehouse along the horizontal walking track, and acquiring the laser measurement value of the laser range finder and the monitoring values of the scanning gantry temperature and humidity sensor, the vertical track temperature and humidity sensor and the horizontal track temperature and humidity sensor in real time in the walking process;
step five: acquiring a laser measurement value of the laser range finder in real time during walking, judging whether a light spot of the laser range finder hits on a target scanning component, and if so, stopping horizontal advance of the scanning gantry;
step six: determining the boundary profile of the measurement surface in the target scanning member, all boundary points forming a boundary point data set Q0；
Step seven: completing data acquisition of the measuring surface to form a laser point cloud data set Q1；
Step eight: correcting the placing posture of the target scanning component to an ideal placing posture;
step nine: analyzing the corrected measurement data of the measurement surface of the target scanning component, and eliminating abnormal measurement values of the measurement surface of the target scanning component;
step ten: determining the manufacturing precision of the assembled surface of the target scanning component, and spraying marks on the surface of the target scanning component in the error area;
step eleven: and generating a detection report, and finishing all detections on the target scanning component.
Wherein: the concrete method of the step five is as follows: left laser rangefinder measurement L when laser rangefinder spot strikes target scanning memberl+ right laser rangefinder measurement LrWhen the current measured value is less than or equal to L, the target scanning component 2 is judged to be detected, and the current measured values of the two laser range finders are recorded as
Figure BDA0003565415540000051
And
Figure BDA0003565415540000052
wherein: in the sixth step, the stopping point in the fifth step is taken as a starting point, a circuitous half and step-by-step approximation method is utilized to search the boundary point of the target scanning component corresponding to the current height in the horizontal direction, and the boundary point is marked as target scanningFirst boundary point P of member0Taking the forward direction of the horizontal walking track as the positive direction of an x axis, the upward direction of the vertical walking track as the positive direction of a y axis, the measured value of the laser range finder as the coordinate value of a z axis and the first boundary point P of the target scanning component0Establishing an xyz coordinate system for the origin of coordinates, from the origin of coordinates P0Starting from the above, capturing the rest boundary points of the peripheral outline of the boundary of the measuring surface of the target scanning component in the clockwise direction, combining the theoretical data model of the target scanning component in the process, continuously reducing the searching times of the subsequent boundary points by using a fast iteration method, accelerating the capturing speed of the rest boundary points, and finally forming a boundary point data set Q by all the boundary points0。
The method also comprises the following steps:
step 6.1: when the gantry is scanned and walks forward one step, the measurement values of the laser range finders at two sides of the current position are collected and recorded as
Figure BDA0003565415540000053
And
Figure BDA0003565415540000054
calculating the change rate of the laser range finder measurement values at the two sides of the current position and the previous step position, wherein the change rate of the left measurement value is
Figure BDA0003565415540000055
The rate of change of the right-hand measurement value is
Figure BDA0003565415540000056
Comparison of
Figure BDA0003565415540000057
And
Figure BDA0003565415540000058
size:
when in use
Figure BDA0003565415540000059
When the laser range finder light spots on two sides are measured twice and then are respectively alignedOn the corresponding measuring surface, the detection of the target measuring surface is completed;
when in use
Figure BDA00035654155400000510
During measurement, the light spot of the laser range finder on one side does not completely hit a corresponding measuring surface after twice measurement; the scanning gantry 1 continues to move horizontally forward along the horizontal travel track 5 by a step S until
Figure BDA00035654155400000511
Step 6.2: continuing to move the laser range finder corresponding to the target measuring surface in the step 6.1 upwards by a step length S along the vertical moving track, and determining the change rate of the measured value in the y-axis direction;
step 6.3: the mobile laser range finder retreats to the first measuring point in the current measuring surface and starts to acquire a first scanning boundary point P in a winding and semi-walking mode0；
Step 6.4: obtaining a first scanning boundary point P0Then, with P0Taking the horizontal advancing direction of a scanning gantry as the positive direction of an x axis, the scanning vertical upward direction of a laser range finder as the positive direction of a y axis, and the measurement value of the laser range finder as the coordinate value of a z axis as the origin of coordinates, establishing an xyz coordinate system to obtain P0Point coordinates (x)0,y0,z0) I.e., (0,0, 0);
step 6.5: and performing subsequent boundary point capture on the basis of the first scanning boundary point, and completing capture of all boundary points of the target scanning component.
Wherein: the concrete steps of the step eight are as follows:
step 8.1: putting the theoretical model into the coordinate system established in the step six, and measuring the bottom left corner point P 'of the surface of the theoretical model'0P of measuring plane with target scanning member0Point superposition, the theoretical model measurement surface bottom boundary is superposed with the x axis, and the theoretical model measurement surface left boundary is superposed with the y axis to obtain a theoretical model measurement surface data set Q'1；
Step 8.2: the measuring surface and the theory in the actual placementThe measurement surfaces of the theory model are coupled to finish the posture inversion correction of the target scanning component, and a corrected laser point cloud data set Q is obtained1_3And a boundary point data set Q0_3。
Wherein: the concrete steps of the ninth step are as follows:
step 9.1: traversing corrected laser point cloud data set Q1_3And a boundary point data set Q0_3Comparing the laser point cloud data set Q1_3And a boundary point data set Q0_3Middle measured value and theoretical model data set Q'1Whether the measured values of the middle-identical xy coordinate positions are identical or not and the difference exceeds the minimum precision delta S of the measurement dotting0Coordinate points of (2) are stored in an abnormal point data set Q△0Performing the following steps;
step 9.2: abnormal point data set Q△0Eliminating abnormal points reasonably existing in the abnormal point data set, and defining the abnormal point data set after eliminating the abnormal points reasonably existing in the abnormal point data set as Q△1；
Step 9.3: abnormal point data set Q with abnormal points reasonably existing after traversal elimination△1Taking out the measuring points in the data set one by one, and comparing the relation between the current point and the measuring values of the peripheral measuring points on the measuring surface by using a correlation search method with the current point as the center; obtaining a laser point cloud data set Q of the current point after correction1_3And comparing the measured values of all the measuring points in the 5-by-5 point area of the middle square circle with the measured values of the current measuring point in sequence, and if the measured values of all the peripheral measuring points are greater than or less than the measured values of the current measuring point, judging that the current measuring point is a local defect point.
Still disclose a prefabricated component assembly face intelligent scanning and error automatic identification system, including workstation, storehouse, scanning longmen, horizontal walking track and component scanning platform, its characterized in that:
the warehouse is located at one end of the workbench and is provided with a containing space for containing a scanning gantry and an electric gate, the horizontal walking tracks are two tracks and extend along two sides of the workbench, one end of the horizontal walking tracks extends into the warehouse, the framework scanning table is located on the workbench and is arranged in the middle of the horizontal walking tracks so as to be used for placing a target scanning component, the scanning gantry is slidably arranged on the horizontal walking tracks and is a gantry-shaped walking mechanism, the scanning gantry walks on the horizontal walking tracks on two sides of the framework scanning table, two inner sides of the scanning gantry are respectively provided with a vertical walking track, a vertical walking tray is respectively arranged on the vertical walking tracks so as to move up and down along the vertical walking tracks, and the vertical walking tray is provided with a laser measuring device and a mounting seat for a point painting mechanical telescopic arm.
Wherein: the laser measuring equipment is fixed at the upper end of the mounting seat and is a single-point laser range finder, and the telescopic arm of the dot printing machine is fixed at the lower end of the mounting seat and can be controlled to print color spots on the designated surface through telescopic control.
Wherein: the scanning gantry comprises a scanning gantry body, a horizontal walking limiting device, a horizontal walking motor and a horizontal walking encoder, wherein the scanning gantry body is arranged on the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, and the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, two sides of the scanning gantry body, the scanning gantry body of the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, two sides of the scanning gantry body, the scanning gantry body of the scanning gantry body, two sides of the scanning gantry body, two sides of the scanning gantry body, two ends of the scanning gantry body, and the scanning gantry body.
Wherein: and a vertical walking motor and a vertical walking encoder are arranged at the lower end of the connecting point of the vertical walking track and the scanning gantry bottom beam to drive the vertical walking tray to move up and down and record the position of the vertical walking tray.
According to the above content, the system and the method for intelligent scanning and automatic error identification of the splicing surface of the prefabricated part have the following effects:
1. the gantry type walking structure is adopted, the multidirectional moving motor and the track are loaded on the gantry, the measurement work of a measurement surface in any shape can be completed, various sensors are loaded on the gantry, the temperature and the humidity of the track, the gantry and air are monitored in real time, the measurement result is corrected through the monitoring result of the temperature and the humidity, and the system can work under the complex climate condition without influencing the precision.
2. In the actual measurement process, various factors influencing manufacturing precision scanning such as concave-convex mortises, rubber channels, air bubble pits, stone particles and slight edge breakage can exist on the measuring surface of the target scanning component. Firstly, the boundary data of the target scanning component is quickly found out by using methods such as successive approximation, shadow shape following and the like, and then influence factors are eliminated step by using algorithm means such as a correlation search algorithm, a theoretical model reference method, an overall trend deduction method and the like, so that the calculation of the manufacturing precision of the prefabricated component splicing surface is completed.
3. After the scanning measurement of a component is accomplished, the system calculates the regional boundary point coordinate data set of swell, and the control portal carries the air brushing device to walk the corresponding position of boundary point in each swell region one by one, with swell boundary point air brushing on the component surface, the workman compares the detection report can be quick when convenient later stage is polished and is restoreed and find out the swell position, greatly reduces the degree of difficulty and the work load of polishing.
The details of the present invention can be obtained from the following description and the attached drawings.
Drawings
Fig. 1 shows a schematic diagram of the intelligent scanning and automatic error identification system for the splicing surface of the prefabricated part.
Figure 2 shows a perspective view of a scanning gantry of the present invention.
Figure 3 shows a side view of a scanning gantry of the present invention.
Fig. 4 shows a front view along the horizontal walking direction of the scanning gantry during the scanning process of the target scanning component of the present invention.
Fig. 5A, 5B and 5C show examples of application of the present invention to various types of irregularly shaped prefabricated parts.
FIG. 6 shows the position of the target scanning member of the present invention in a coordinate system at a desired pose
FIG. 7 shows a dense scan data point bitmap of a target scanning component of the present invention.
Fig. 8 shows a schematic position diagram of the target measurement plane of the present invention in the coordinate system after being corrected to the xy-plane and translated.
Fig. 9 shows a front view of the dotting point and the measuring surface in the process of determining the target measuring surface according to the present invention.
FIG. 10 shows a schematic view of the measurement of the target scanning member of the present invention with the limit biased to one side.
FIGS. 11A and 11B are top views showing the ideal placement and extreme tilt placement, respectively, of a target scanning member of the present invention within a measurement region
Fig. 12A, 12B and 12C respectively show schematic position diagrams of the target scanning component of the present invention, in the scanning process of the laser range finder, in different posture scenes, from the point of the laser range finder not striking the component to the point of the laser range finder striking the component measuring surface on both sides.
FIG. 13 is a schematic diagram showing the relationship between the actual boundary points and the estimated boundary points in the xy-plane during the process of capturing the boundary points.
Figure 14 shows a flow chart of the method of the present invention.
Reference numerals are as follows:
1: scanning the gantry; 101: scanning the gantry bottom beam; 102: scanning a gantry temperature and humidity sensor; 103: a vertical track temperature and humidity sensor; 104: a horizontal rail temperature and humidity sensor; 105: limiting vertically walking downwards; 106: a horizontal traveling motor; 107: a horizontal walking encoder; 108: a vertical traveling motor; 109: a vertical walking encoder; 110: limiting before horizontal walking; 111: limiting after horizontal walking; 112: vertically walking and upper limiting; 2: a target scanning member; 20: a front end face; 202: a target scanning member bottom surface; 21: the measured splicing surface is the measuring surface; 211: measuring the projection of the vertical boundary of the surface on an xy-plane in an ideal placing posture; 212: projecting the vertical boundary of the measuring surface presumed by the captured boundary points on an xy-plane; 213: projecting the vertical boundary of the actual placing attitude measurement surface on an xy-plane; 22: measuring a face boundary; 23: tensioning the hole by the target scanning component; 24: a target scan component rebate; 25: measuring a surface boundary by the theoretical model; 26: a left measuring surface; 27: a right measurement plane; 3: a component scanning stage; 4: a warehouse; 5: a horizontal walking track; 6: a vertical walking track; 7: a laser range finder; 71: a left laser rangefinder; 72: a right laser rangefinder; 73: measuring light rays by a laser range finder; 8: a vertical walking tray; 9: drawing points and spraying mechanical telescopic arms; 10: a control cabinet.
Detailed Description
Referring to fig. 1 to 6, the system for intelligent scanning and automatic error identification of the splicing surface of the prefabricated part is shown.
As shown in fig. 1, the system for intelligent scanning of the assembly surface of the prefabricated part and automatic error identification comprises a workbench, a warehouse 4, a target scanning member 2, an intelligent scanning device, a horizontal walking track 5 and a member scanning table 3, wherein the warehouse 4 is positioned at one end of the workbench, can accommodate a scanning gantry 1 of the intelligent scanning device and is provided with an electric gate, the horizontal walking track 5 is two parallel tracks and extends along two sides of the workbench, one end of the horizontal walking track 5 extends into the warehouse 4, the member scanning table 3 is positioned on the workbench and is arranged in the middle of the horizontal walking track 5 for placing the target scanning member 2, the scanning gantry 1 is arranged on the horizontal walking track 5 and can walk along the horizontal track, and the target scanning member 2 usually is a large prefabricated member and occupies a large area, so that the scanning gantry 1 of the intelligent scanning device can occupy a large space, The horizontal walking track 5 and the component scanning platform 3 are always arranged in the open environment for stacking components, but the scanning gantry 1 belongs to precision equipment and cannot be in a wind and rain environment for a long time, the scanning gantry needs to be placed in the warehouse 4 for protection when not in work, the electric gate of the warehouse 4 is opened when in work, and the scanning gantry 1 can automatically run out of the warehouse 4 to start working.
The scanning gantry 1 is a portal-shaped travelling mechanism and travels on horizontal travelling rails 5 on two sides of a component scanning table 3, referring to fig. 2, fig. 3 and fig. 4, two inner sides of the scanning gantry 1 are respectively provided with a vertical travelling rail 6, each vertical travelling tray 6 is provided with a vertical travelling tray 8, the vertical travelling trays 8 can move up and down along the vertical travelling rails 6, and the vertical travelling trays 8 are provided with mounting seats of a laser range finder 7 and a drawing point painting mechanical telescopic arm 9, wherein the laser range finder 7 is fixed at the upper end of the mounting seat, and the drawing point painting mechanical telescopic arm 9 is fixed at the lower end of the mounting seat and can be telescopic to perform color spot painting and the like on a specified surface.
The scanning gantry crane comprises a scanning gantry crane, a horizontal walking limiting device, a horizontal walking motor 106 and a horizontal walking encoder 107, wherein the scanning gantry crane comprises two scanning gantry crane bottom beams 101 respectively arranged at the bottoms of two sides of the scanning gantry crane 1, the two ends of each scanning gantry crane bottom beam 101 are provided with the horizontal walking limiting devices, each horizontal walking limiting device comprises a horizontal walking front limiting device 110 and a horizontal walking rear limiting device 111 which are used for limiting the walking range of the scanning gantry crane 1 on a horizontal walking track 5, and the middle area of each scanning gantry crane bottom beam 101 is provided with the horizontal walking motor 106 and the horizontal walking encoder 107 so as to drive the scanning gantry crane 1 to move forwards and backwards and record the accurate position of the scanning gantry crane 1.
The lower end of the connection point between the vertical walking track 6 and the scanning gantry bottom beam 101 is provided with a vertical walking motor 108 and a vertical walking encoder 109 for driving the vertical walking tray 8 to move up and down and recording the position of the vertical walking tray 8, the upper end and the lower end of the vertical walking track 6 are provided with vertical walking limiting devices, and the vertical walking limiting devices comprise a vertical walking upper limiting 112 and a vertical walking lower limiting 105 so as to limit the walking range on the vertical walking track 6 of the vertical walking tray 8.
The scanning gantry type automatic spot drawing machine is characterized in that a control cabinet 10 is arranged on a vertical structure on one side of the scanning gantry 1, and a horizontal walking motor 106, a vertical walking motor 108, a horizontal walking front limit 110, a horizontal walking rear limit 111, a vertical walking upper limit 112, a vertical walking lower limit 105, a horizontal walking encoder 107, a vertical walking encoder 109 and a controller of a spot drawing mechanical telescopic arm 9 are arranged in the control cabinet 10.
The scanning gantry temperature and humidity sensor 102, the vertical track temperature and humidity sensor 103 and the horizontal track temperature and humidity sensor 104 are respectively arranged on the outer side of the vertical structure of the scanning gantry 1, the side surface of the vertical walking track 6 and the side surface of the horizontal walking track 5 and used for measuring temperature and humidity changes of the positions, compensating measurement and control results and improving measurement and control precision.
Before measurement, the target scanning component 2 is placed in a measurement area on the component scanning table 3, so that the component is as close to an ideal placement position as possible (i.e., the target scanning component is placed in the middle of the measurement table, and splicing surfaces on two sides are close to the direction of a horizontal walking track), and the target scanning component 2 can be provided with a target scanning component tensioning hole 23 and a target scanning component tenon and tenon 24.
Wherein, two tracks of horizontal walking track 5 are level and parallel, and its inboard is equipped with the rack track to provide advantages such as low noise, moving speed are fast, the walking precision is high through the rack track.
Wherein, the upper surface of the component scanning platform 3 and the horizontal walking rails 5 at two sides are in a parallel state, the upper surface of the component scanning platform 3 is provided with a rectangular measuring area, and the target scanning component 2 is placed in the measuring area for detection before scanning.
As shown in fig. 7 to 14, the present invention also discloses a method for intelligently scanning the manufacturing accuracy of the prefabricated part assembling surface and automatically identifying the error, which comprises the following steps:
the method comprises the following steps: a preparation step, namely hoisting the target scanning component 2 into a measurement area on the component scanning table 3, and in the hoisting process, enabling the measurement surface 21 of the target scanning component 2 to be close to the direction parallel to the horizontal walking track 5 as much as possible.
Step two: and a starting step, namely selecting the type of the target scanning component 2 to be scanned (at the moment, the system automatically loads theoretical model data corresponding to the target scanning component 2), and configuring scanning precision and other parameters (self-configuration or system default) according to the production quality requirement of the spliced surface of the target scanning component 2. And (3) opening the electric roller shutter door of the warehouse 4, starting scanning detection by one key, and starting the intelligent scanning equipment (the gantry 1 runs and scans horizontally along the horizontal walking track 5 to the target scanning component 2, and simultaneously starting the laser range finder 7).
Step three: and an adjusting step, namely adjusting the height of the vertical walking tray 8 to enable the light of the laser range finder 7 to be close to the height of the upper surface of the component scanning table 3.
Step four: the scanning gantry 1 moves forwards from the warehouse 4 along the horizontal walking track 5, the laser measurement value of the laser range finder 7 and the monitoring values of the scanning gantry temperature and humidity sensor 102, the vertical track temperature and humidity sensor 103 and the horizontal track temperature and humidity sensor 104 are acquired in real time in the walking process, the laser measurement value and the walking distance can be compensated by utilizing deformation data of a steel structure in different temperature and humidity environments, and the measurement and control accuracy in complex climate environments is guaranteed.
Step five: and acquiring the laser measurement value of the laser range finder 7 in real time during walking, judging whether the light spot of the laser range finder 7 is irradiated on the target scanning component 2, and if so, stopping the horizontal advance of the scanning gantry 1. Specifically, as shown in fig. 10, since the distance between the laser range finders 7 arranged in pairs is L, the sum of the measurement values of the pair of laser range finders 7 is inevitably larger than the distance therebetween, and thus, when the light spot of the laser range finder 7 does not impinge on the target scanning member 2, the left-side laser range finder measurement value L is measuredl+ right laser rangefinder measurement Lr＞L。
Because each pair of laser range finders is just to the installation, so the measuring light that two laser range finders jetted out should be in same straight line, no matter how the target scanning component was put, when one of them laser range finders measuring light struck on the component, another measuring light also can strike on the component. Therefore, the left laser range finder measurement L is taken when the laser range finder spot hits the target scanning memberl+ right laser rangefinder measurement LrL or less to judge whether the target scanning component 2 is detected or not and record the current measurement values of the two laser range finders as
Figure BDA0003565415540000151
And
Figure BDA0003565415540000152
wherein: taking the respective scenarios in fig. 12A, 12B and 12C as an example, when the target scanning member 2 is detected, it is possible that both laser range finder spots hit on the respective corresponding measuring surfaces 21, or only one of the laser range finder spots hits on the corresponding measuring surface 21 and the other laser range finder spot hits on the front face 20 as shown in fig. 11A, 11B.
Step six: the boundary profile of the measuring surface 21 in the target scanning member 2 is determined (as indicated by the measuring surface boundary 22 in fig. 2). Using the current position as the starting point, using the method of zigzag half, successive approximation, etc. to search the boundary point of the target scanning component 2 corresponding to the current height in the horizontal direction, and recording as the first boundary point P of the target scanning component 20. The forward direction of the horizontal walking track 5 is the positive direction of the x axis, the upward direction of the vertical walking track 6 is the positive direction of the y axis, the measured value of the laser range finder 7 is the coordinate value of the z axis, and the first boundary point P of the target scanning component 2 is used0For the origin of coordinates, an xyz coordinate system is established. From the origin of coordinates P0Starting from the above, capturing the rest boundary points of the peripheral outline of the measuring surface boundary 22 of the target scanning component 2 in the clockwise direction, combining the theoretical data model of the target scanning component 2 in the process, continuously reducing the search times of the subsequent boundary points by using a fast iteration method, accelerating the capture speed of the rest boundary points, and finally forming a boundary point data set Q by all the boundary points0。
Specifically, the method may further include the steps of:
step 6.1: when the gantry 1 is scanned and walks forwards one step each time, the measurement values of the laser range finders at two sides of the current position are collected and recorded as
Figure BDA0003565415540000161
And
Figure BDA0003565415540000162
calculating the change rate of the laser range finder measurement values at the two sides of the current position and the previous step position, wherein the change rate of the left measurement value is
Figure BDA0003565415540000163
The rate of change of the right-hand measurement value is
Figure BDA0003565415540000164
Comparison of
Figure BDA0003565415540000165
And
Figure BDA0003565415540000166
size:
when in use
Figure BDA0003565415540000167
During the measurement, the laser range finder light spots on the two sides are respectively projected on the corresponding measuring surfaces 21 in the two times of measurement. And finishing the detection of the target measuring surface.
When in use
Figure BDA0003565415540000168
During the measurement, the light spot of the laser range finder on one side does not completely hit the corresponding measuring surface in the two measurements before and after. The scanning gantry 1 continues to move horizontally forward along the horizontal travel track 5 by a step S until
Figure BDA0003565415540000169
Wherein: the minimum step is taken from the moment the laser range finder spot hits the target scanning member 2 to the moment the detection of the target measurement surface is completed. As illustrated by three scenes in fig. 12A, 12B, and 12C, the two-sided laser rangefinder measures the trend of the change in the measurement value and the measurement plane 21 of the target scanning member 2 at different pose each step.
Wherein:
Figure BDA00035654155400001610
during the process, the change rate of the dotting measurement value of the measurement surface in the direction corresponding to the x axis can be determined, and whether the change rate of the measurement value of the laser range finder is equal to the change rate can be continuously calculated in the horizontal walking process of the scanning gantry 1 by taking the change rate as a reference, so that the component can be judged to be dotted on the measurement surface. In a specific embodiment, the change rate of the dotting measurement value of the measurement surface in the y-axis direction can be further determined as required to further determine whether the laser range finder 7 hits on the measurement surface of the component when walking vertically, and the specific method is similar to that in the x-axis direction, and will not be described in detail herein.
Step 6.2: the laser range finder corresponding to the target measuring surface in the step 6.1 is arranged along the vertical walking track 6 in step lengthS continues to walk one step upwards, and the change rate of the measured value in the y-axis direction is determined. Wherein, at the end of step 6.1
Figure BDA0003565415540000171
Recording the measured value as the reference change rate of the measured value of the horizontal walking direction of the target measuring plane
Figure BDA0003565415540000172
Namely, it is
Figure BDA0003565415540000173
Taking the current measurement surface as the right measurement surface in fig. 12 as an example, the measurement value of the laser range finder at the current position is collected and recorded as
Figure BDA0003565415540000174
Calculating the reference change rate of the vertical walking direction measurement value of the current measurement plane as
Figure BDA0003565415540000175
Wherein: measured value
Figure BDA0003565415540000176
The correspondence between the numbers of (a) and the dotting measurement positions on the measurement plane 21 is shown in fig. 9.
Wherein: the left side measurement surface is calculated by changing the subscript r into l through the change rate calculation, and the subsequent steps are the same in the invention.
Step 6.3: the mobile laser range finder 7 retreats to the first measuring point in the current measuring surface and starts to acquire the first scanning boundary point P in a winding and half-walking mode0The specific judgment method is as follows:
step 6.3.1: when the mobile laser range finder 7 is retreated to the first measuring point in the current measuring plane, the current laser range finder 7 is located in fig. 9
Figure BDA0003565415540000177
Corresponding to the position, firstly, the laser range finder 7 continues to vertically and downwards walk by one step length S along the vertical walking track 6 to reach
Figure BDA0003565415540000178
Corresponding position, i.e. in step 6.1
Figure BDA0003565415540000179
The position of the laser rangefinder 7. All the measured values numbered from 1 to n-1 after the target scanning member 2 is detected are respectively compared with
Figure BDA00035654155400001710
Passing through type
Figure BDA00035654155400001711
And calculating the change rate, wherein i is the serial number of the measured value, namely the subscript number of the measured value, and the value range is 1 to (n-1). Sequentially taking out corresponding change rates from i-n-1 to 1
Figure BDA00035654155400001712
Judgment of
Figure BDA00035654155400001713
Whether or not equal to
Figure BDA00035654155400001714
Record the last one
Figure BDA00035654155400001715
The point position of (1), which is the first measurement point P in the current measurement plane00The corresponding measured value is noted as L00And recording the value of the current i.
And controlling the scanning gantry to walk backwards for n-i steps along the horizontal walking track by the step length S, wherein the current light spot position of the laser range finder 7 is the first measuring point in the current measuring plane.
Step 6.3.2: the gantry is scanned along the horizontal walking track 5 by a step length StempWalking backwards one step horizontally as S/2;
step 6.3.3: the measurement value of the laser range finder 7 at the current position is acquired and recorded as LtempCalculating the position and the measurement point P00Has a measured value change rate of
Figure BDA0003565415540000181
Wherein: when the current measuring position is horizontally retreated/vertically downward compared with the last measuring position, StempValue of-Stemp(i.e., taking a negative value when the directions are reversed).
Step 6.3.4: judgment of KtempWhether or not to be equal to
Figure BDA0003565415540000182
If not, the scanning gantry 1 moves along the horizontal walking track 5 by the step length StempOne step is walked forwards horizontally by half of the current step length, and the step 6.3.3 is returned; if yes, judging whether the current step length is smaller than the minimum walking precision delta S of the scanning gantry 1 or not0(according to the scanning accuracy requirement of the target scanning member 2, the user can set by himself, Δ S0Far smaller than the walking step S), if so, successfully acquiring a first scanning boundary point, and recording as P0Record the corresponding measured values L0Ending the current step; if not, the scanning gantry 1 moves along the horizontal walking track 5 by the step length StempStep 6.3.3 is skipped to when the current step size is half of the step size and one step is walked horizontally backwards.
Step 6.4: obtaining a first scanning boundary point P0Then, with P0Taking the horizontal advancing direction of the scanning gantry 1 as the positive direction of an x axis, the scanning vertical upward direction of the laser range finder 7 as the positive direction of a y axis, the measured value of the laser range finder as the coordinate value of a z axis, establishing an xyz coordinate system to obtain P0Point coordinates (x)0,y0,z0) I.e., (0,0, 0).
Step 6.5: and based on the first scanning boundary point, performing subsequent boundary point capture, and completing capture of all boundary points of the target scanning component 2.
The method can greatly reduce the search range and gradually accelerate the capture speed of subsequent boundary points by continuously accumulating and learning data and utilizing a mode like image formation, and finally completes the capture of all boundary points of the target scanning component 2, and the specific implementation method is as follows:
step 6.5.1: from the origin of coordinates, a second boundary point is captured.
Taking the target scanning component 2 as an ideal placing posture (taking the position of the target scanning component model in the xyz coordinate system in fig. 6 as an example) as a standard, P is calculated0Adjacent boundary point P above the point1Theoretical position P '(i.e. second boundary point)'1(taking the second boundary point on the vertical boundary in FIG. 13 as an example): p'1Y-axis coordinate value of P0Y-axis coordinate value of + S, i.e. y0+ S; calculating y ═ y0+ S and theoretical target measurement plane model intersection point (P)0Point the closest clockwise, P 'in FIG. 14'1Position) is P'1Point, coordinate corresponding to xy-plane is (x'1,y′1) The z-coordinate value thereof is
Figure BDA0003565415540000191
Move laser rangefinder 7 to P'1The point position is that the laser range finder continues to move upwards by a step S along the vertical walking track 6, then the gantry 1 is scanned and the step S is further moved along the horizontal walking track 5temp＝x′1-x0Walk one step horizontally (if StempIf the walking speed is more than 0, the walking is forward; if S istempIf the walking speed is less than 0, the walking is backward walking; if S istemp0, no walk is needed), the acquisition of the actual scanning boundary point P is started1。
Wherein: for the vertical boundary, if the next boundary point is located in the vertical upward direction of the current boundary point, the laser range finder 7 is controlled to continue to move upward by a step length S along the vertical moving track 6, then the gantry 1 is scanned and then moved by the step length S along the horizontal moving track 5temp＝x′1-x0Walk one step horizontally (if StempIf the walking speed is more than 0, the walking is carried out horizontally and forwards; if S istempIf the walking speed is less than 0, the walking is carried out horizontally backwards; if S istemp0, no walk is needed), the acquisition of the actual scanning boundary points is started. If the next boundary point is in the vertical downward direction of the current boundary point, the laser range finder 7 is firstly controlled to walk along the vertical walking track6, continuously walking downwards by step S, then scanning the gantry 1 and then walking along the horizontal walking track 5 by step Stemp＝x′1- x0Walking one step horizontally.
Wherein: for the horizontal boundary, if the next boundary point is located in the horizontal forward direction of the current boundary point, the scanning gantry 1 is controlled to walk forward by one step S along the horizontal walking track 5, and then the laser range finder 7 is controlled to walk forward by one step S along the vertical walking track 6temp＝y′1- y0Go on one step (if S)tempIf the height is more than 0, the walking is vertically upward; if S istempIf the walking speed is less than 0, the walking is vertically downward walking; if S istemp0, no walk is needed), the acquisition of the actual scanning boundary points is started. If the next boundary point is in the horizontal backward direction of the current boundary point, the scanning gantry 1 is controlled to walk backward by the step S along the horizontal walking track 5, and then the laser range finder 7 is controlled to walk backward by the step S along the vertical walking track 6temp＝y′1-y0And continuing to walk by one step, and starting to acquire actual scanning boundary points. The above rules are followed in the whole process of searching for the boundary points, and are not described in detail below.
Step 6.5.1.1: the measured value of the laser range finder at the current position is acquired and recorded as LtempCalculating the position and theoretical boundary point P'1Has a measured value change rate of
Figure BDA0003565415540000201
Step 6.5.1.2: judgment of KtempWhether or not equal to
Figure BDA0003565415540000202
If not, the scanning gantry 1 moves along the horizontal walking track 5 by the step length StempStep 6.5.1.1 is returned to when the current step size is half of the step size and one step is horizontally moved forward; if yes, judging whether the current step length is smaller than the minimum walking precision delta S of the scanning gantry 1 or not0If yes, successfully acquiring a second scanning boundary point, and marking as P1(x1,y1,z1) Recording the corresponding measured valuesL1Ending the current step; if not, the scanning gantry 1 moves along the horizontal walking track 5 by the step length StempOne step back horizontally for half the current step size, go to step 6.5.1.1.
Step 6.5.2: from the second boundary point P1Starting, the subsequent boundary points are captured.
Calculating P1Adjacent boundary point P above the point2Theoretical position P'2(for example, as shown in fig. 13, the vertical boundaries of the rectangular member show the xy-plane projection 211 of the vertical boundary of the measurement plane in the ideal pose, the xy-plane projection 212 of the vertical boundary of the measurement plane estimated from the captured boundary points, and the vertical boundary 213 of the measurement plane in the actual pose, respectively): p'2Y-axis coordinate value of P1Y-axis coordinate value of (2) + S, i.e. y1+ S; calculating y ═ y1The function intersection point formed by + S and the first two boundary points captured in the xy-plane is P'2For the third boundary point, the function formed by the first two boundary points on the xy-plane is a straight line (i.e. the projection 212 of the vertical boundary of the measurement plane presumed by the captured boundary points on the xy-plane), and for other prefabricated parts of the same type, the function formed by the captured boundary points on the xy-plane may be a curve, and the curve function can be obtained by a theoretical measurement plane model. According to the method, the subsequent boundary point theoretical position P 'can be obtained'nThe coordinate corresponding to xy-plane is (x'n,y′n) The z-coordinate value thereof is
Figure BDA0003565415540000211
Figure BDA0003565415540000212
Move laser rangefinder 7 of current position to P'nThe point position is that the laser range finder 7 continues to move upwards by a step S along the vertical walking track 6, then the gantry 1 is scanned and then moves by the step S along the horizontal walking track 5temp＝x′n-xn-1Walk one step horizontally (if StempIf the walking speed is more than 0, the walking is forward; if S istempIf the walking speed is less than 0, the walking is backward walking; if S istemp0, no walk is needed), the acquisition of the actual scanning boundary point P is startedn。
Step 6.5.2.1: the measured value of the laser range finder at the current position is acquired and recorded as LtempCalculating the position and a theoretical boundary point P'nHas a measured value change rate of
Figure BDA0003565415540000221
Wherein: l is a radical of an alcoholn-1For the last captured boundary point Pn-1Corresponding to the laser measurement.
Step 6.5.2.2: judgment of KtempWhether or not to be equal to
Figure BDA0003565415540000222
If not, the scanning gantry 1 moves along the horizontal walking track 5 by the step length StempStep 6.5.2.1 is returned to when the current step size is half of the step size and one step is horizontally moved forward; if yes, judging whether the current step length is smaller than the minimum walking precision delta S of the scanning gantry 1 or not0If yes, successfully acquiring the nth scanning boundary point, and marking as Pn(xn,yn,zn) Recording the corresponding measured values LnEnding the current step; if not, scanning the gantry 1 along the horizontal walking track 5 by the step length StempOne step back horizontally for half the current step size, go to step 6.5.2.1.
Wherein: wherein: as the captured boundary points increase, the actual boundary of the measurement plane increasingly approaches the theoretical boundary inferred by the captured boundary points, i.e., StempAnd are getting smaller and smaller. And when the vertical boundary of the measuring surface captures a second boundary point in the xy-plane projection 211 in the ideal placing posture, Stemp＝S1(i.e., P)1And P'1Difference in x-axis direction), a third boundary point is captured, Stemp＝S2(i.e. P)2And P'2Difference in x-axis direction), S2＜S1I.e. Sn≤Sn-1. With more and more boundary points being captured, the method of continuously reducing the search range in the form of image-following can be used to achieve the purpose of accelerating the capture speed. Until finding the current measuring planeWith boundary points, forming a set of boundary points Q0。
Step seven: completing data acquisition of the measuring surface to form a laser point cloud data set Q1。
And controlling the scanning gantry 1 to walk at equal intervals in the x-axis direction, and controlling the vertical walking tray 8 to walk along the vertical walking track 6 at equal interval step length every time the scanning gantry walks by one step, so as to finish dotting measurement on the measuring surface 21 of the target scanning component 2 corresponding to the current vertical line. In this way, the scanning of the measurement surface 21 of the target scanning member 2 is completed (all the measurement points are in a grid-like distribution as shown in fig. 7).
Wherein: from P, based on the boundary data of the measuring surface 21 of the target scanning member 20Starting from the starting point, the laser range finder 7 is controlled to move gradually on the vertical walking track 6 in a system set step length along the vertical direction, and a laser measurement value is acquired after each step of movement. Until the laser range finder 7 moves to the upper boundary point of the target scanning component 2, completing the scanning of the vertical line on the origin of coordinates; then controlling the scanning gantry 1 to walk for one step along the horizontal walking track 5 in a system setting step length to complete the scanning of the vertical line corresponding to the current horizontal position; the method is used for completing the scanning of all vertical lines in the boundary range of the measuring surface of the whole component to form dense scanning data, and recording all scanning results to form a laser point cloud data set Q1。
Step eight: the placing posture of the target scanning component can be corrected by utilizing a prefabricated component space posture inversion correction algorithm based on laser scanning point cloud. When the target scanning component 2 is placed, it cannot be guaranteed that the measuring surface 21 of the target scanning component is completely parallel to the horizontal walking track 5 (i.e. the ideal placing posture in fig. 6), and the target scanning component 2 with unknown placing posture is corrected to the ideal placing posture (i.e. the measured value of the measuring surface under the current placing posture is projected to the plane of the measuring surface under the ideal placing posture) by combining the theoretical model data and the actual measurement data of the target scanning component 2 and using space geometry conversion.
Specifically, the detailed steps of the correction are as follows:
step 8.1: the theoretical model of the target scanning member 2 has been imported into the system before the start of the scanPutting the theoretical model into the coordinate system established in the step six, and measuring the bottom left corner point P 'of the surface of the theoretical model in the graph 6'0P of the measuring surface 21 of the target scanning member 2 in the actual measurement in FIG. 70Point superposition, the theoretical model measurement surface bottom boundary is superposed with the x axis, the theoretical model measurement surface left boundary is superposed with the y axis, and a theoretical model measurement surface data set Q 'is obtained'1。
Step 8.2: and coupling the measurement surface in actual placement with the measurement surface of the theoretical model to finish the posture inversion correction of the target scanning component 2, so as to judge the abnormal point in the subsequent steps.
In actual measurement, the target scanning component 2 cannot be completely arranged along the coordinate axis direction like a theoretical model before measurement, and included angles may be generated in the x, y and z directions.
Step 8.2.1: from the set of boundary point data Q0Extracting points with maximum and minimum values in x and y axis directions and coordinate origin, taking three points which are not on the same straight line as characteristic points, wherein the coordinates of the three characteristic points are A (x)1，y1，z1)、B(x2，y2，z2)、C(x3，y3，z3). The equation for calculating the plane ABC where the measuring surface of the target scanning member 2 is located, that is, the characteristic point plane, by using the characteristic points is expressed by formula 1:
Figure BDA0003565415540000241
step 8.2.2: the measurement plane is first corrected to the xy-plane, equation 2:
z＝0；2)
combining the equation of the characteristic point plane in the step 8.2.1, obtaining an intersection line L between the characteristic point plane and the xy-plane as formula 3:
ax+by+d＝0；3)
wherein: a. b and c are function constants;
an included angle alpha between the two planes can be obtained by the intersection line L of the characteristic point plane, the xy-plane and the plane;
wherein: plane ABC upper fetchingAny point of the three characteristic points which is not positioned on the intersecting line L makes a perpendicular line to the plane intersecting line L, and the foot is a point P⊥At a point P⊥For the foot, making a perpendicular line of a plane intersecting line L on an xy-plane, wherein an included angle between the two perpendicular lines is a plane included angle alpha;
step 8.2.3: the laser point cloud data set Q1And a boundary point data set Q0All the measurement points in (1) are corrected to the xy-plane, and the corrected plane is recorded as the plane ABC'.
From the laser point cloud data set Q1And a boundary point data set Q0Sequentially taking measurement point data and recording the measurement point data as a measurement point Pi，PiMaking a perpendicular line to the intersecting line L, then taking the intersecting line L as a rotating axis, taking the foot as a rotating center and taking alphaxFor rotation of the angle to xy-plane, finally PiRotation of a point to a new point P on the xy-planeiIs' i.e. PiThe corrected position of the point.
Until the laser point cloud data set Q1And a boundary point data set Q0All the measurement points are corrected to form a corrected laser point cloud data set Q1_1And a boundary point data set Q0_1And the corrected characteristic point surface is a plane ABC ', and the plane ABC' is superposed with the xy-plane.
Step 8.2.4: the corrected plane ABC' has already been coincident with the xy-plane, but the attitude of the target scanning member 2 is unknown in the actual measurement, and the left bottom corner point of the measurement plane thereof is not necessarily coincident with the origin of coordinates P after the correction, by step 8.2.30The (0,0,0) points coincide. From corrected boundary point data set Q'0Extracting the corrected left base angle point P of the measuring surfaceAngle l(xl,yl,zl) Translation point PAngle lMake it at the origin of coordinates P0Point coincidence, i.e. point PAngle lThe point being translated along the x-axis by xlIs translated along the y-axisl. According to the method, the corrected measuring surface laser point cloud data set Q1_1And measurement plane boundary point data set Q0_1All points in (A) are translated along the x-axis by xlIs translated along the y-axislSo far, the translated measuring surface is in the same plane with the measuring surface in the ideal placing posture, and the two measurements are carried outThe left base points of the faces coincide. Translated laser point cloud data set Q1_1And a boundary point data set Q0_1Are respectively denoted as Q1_2And Q0_2。
Step 8.2.5: through step 8.2.4, the translated measuring surface is already in the same plane with the measuring surface in the ideal placing posture, the left bottom angle points of the two measuring surfaces are overlapped, an included angle beta (shown in fig. 8) possibly exists between the connecting line of the left bottom angle point and the right bottom angle point of the measuring surface and the x axis, and the plane ABC' can be formed by taking the coordinate origin P as the coordinate origin0Centered at the point, rotation along the z-axis causes the target scanning component to coincide the two base angles with the x-axis. From the translated boundary point data set Q0_2Extracted left base angle point P of measuring surfaceAngle l(0,0,0) (translated to origin of coordinates) and a bottom right angle point PAngle r(xr,yr,zr) Slope K of the line in which the two bottom corner points are located relative to the x-axis1Is composed of
Figure BDA0003565415540000261
Because the slope K of the straight line where the two base angle points are located relative to the x axis when the target scanning component is ideally placed2The corrected boundary point data set Q is obtained as 00_2The included angle between the straight line of the two bottom angle points and the straight line of the two bottom angle points when the two bottom angle points are ideally placed is
Figure 1
Step 8.2.6: the translated laser point cloud data set Q1_2And a boundary point data set Q0_2The middle measurement point values are respectively rotated around the z-axis direction by taking beta as a rotation angle, and the left bottom angle point P of the component measurement surface is takenAngle lRotating towards the x axis for the center to obtain a final correction value, repeating the operations until all the measurement points are finally corrected to obtain a laser point cloud data set Q after rotation correction1_3And a boundary point data set Q0_3And the posture inversion correction of the target scanning member 2 is completed.
Step nine: the local defect identification method of the splicing surface of the prefabricated part based on the dense scanning data can be used for analyzing the measurement data of the corrected measurement surface 21 of the target scanning member 2, and the measurement values corresponding to the small bubble pits, stone particles and other influencing factors of the measurement surface 21 of the target scanning member 2 are removed. The method comprises the following specific steps:
step 9.1: traversing corrected laser point cloud data set Q1_3And a boundary point data set Q0_3Comparison of measurements from set to set with theoretical model data set Q 'can be performed using theoretical model comparison'1Whether the measured values of the middle-identical xy coordinate positions are identical or not and the difference exceeds the minimum precision delta S of the measurement dotting0(according to the scanning precision requirement of the target scanning component 2, the user can set by himself in the second step) the coordinate points are stored into the abnormal point data set Q△0Until the corrected laser point cloud data set Q1_3And a boundary point data set Q0_3And traversing once.
Step 9.2: abnormal point data set Q△0The reasonably existing abnormal points are eliminated, the reasonably existing abnormal points comprise the measurement points of the areas corresponding to the target scanning component tensioning hole 23 and the target scanning component tenon 24 shown in fig. 6, and the specific operation is as follows:
and obtaining a corresponding xy coordinate range according to the region where the abnormal points (namely the target scanning member tensioning hole 23 and the target scanning member tenon and mortise 24) reasonably exist in the structural model of the target scanning member 2. Traversal of the outlier data set Q△0Eliminating the data in the region with the reasonable abnormal points without analysis, and defining the abnormal point data set after eliminating the reasonable abnormal points as Q△1。
Step 9.3: abnormal point data set Q with abnormal points reasonably existing after traversal elimination△1And taking out the measuring points in the data set one by one, and comparing the relation between the current point and the measuring values of the peripheral measuring points on the measuring surface by using a correlation search method with the current point as the center. Obtaining a laser point cloud data set Q of the current point after correction1_3Comparing the measured values of all the measured points in the 5-5 point region with the measured values of the current measured points, and if the measured values of all the peripheral measured points are greater than or less than the measured values of the current measured pointsIf the quantity value is greater than the preset value, judging that the current measuring point is a local defect point, and removing an abnormal point data set Q with abnormal points from the traversal of the point△1And (5) removing. Repeating the steps until all the local defect point data of the target scanning component 2 are removed, and obtaining an abnormal point data set Q after the local defect points are removed△1Is expressed as a final outlier data set Q△。
For example, the local depression measurement matrix is as follows:
Figure BDA0003565415540000271
for example, the local bump measurement matrix is as follows:
Figure BDA0003565415540000281
step ten: and determining the manufacturing precision of the assembled surface of the target scanning component, and spraying marks on the surface of the component in the error area.
Wherein: the assembling surface manufacturing errors are divided into two forms of bulges and pits, wherein the pit area does not influence the assembling of the prefabricated parts, and the bulge area can cause the conditions that the prefabricated parts cannot be assembled in the assembling process, the joints cannot be pulled tightly and the like, so that the field use of the prefabricated parts is influenced, and the bulge area needs to be polished.
Eliminating final abnormal point data set Q△The final abnormal point data set Q is calculated according to the non-bulge points in the△The method comprises the following steps of (1) spraying marks on a corresponding bulge area in a target component according to the bulge area boundary and the bulge height in the target component, wherein the steps are as follows:
step 10.1: comparing the theoretical models to eliminate the final abnormal point data set Q△The non-bulging points of the component assembly are not influenced.
From the final outlier data set Q△In which the points P are selected one by onen(xn,yn,zn) The face data set Q 'is measured from the theoretical model according to the position of the current point location in the xy-plane'1In obtaining equivalenceTheoretical point position P 'corresponding to position'n(x′n,y′n,z′n) Namely: x is the number ofn＝x′n，yn＝y′n。
Determine whether the outlier is a non-bulge point (take the measurement plane near the xy-plane in fig. 7 as an example): comparison znAnd z'nSize: when z isn≥z′nWhen the current outlier is a non-bump point (a pit point or a flat point), otherwise, it is a bump point.
If it is a non-bulging point: the current point data is separated from the final abnormal point data set Q△Removing, selecting the next measuring point, and continuing to execute the step 10.1;
if it is a drum wrap point: calculating the height h of the current bulgenIs hn＝z′n-zn。
Calculating the heights of all the bulge points in the current measuring surface according to the method, and storing the heights of the bulge points in the current measuring surface into a bulge height data set QΔh。
Step 10.2: final abnormal point data set Q after traversing and eliminating non-drum pointsΔ(after the non-bulging points are removed in the step 10.1, only the bulging abnormal points are left in the data set), the other 8 measuring points of the current point in the x-axis and y-axis direction squared figures are searched by using the correlation search method and taking the current point as the center, and whether the current point is also the bulging abnormal point is checked (namely, the final abnormal point data set Q exists in the other eight points)ΔMeasurement point of (1):
if so, searching whether the bulge abnormal point exists in the range of the nine-square grid by taking the newly found bulge abnormal point as the center. Repeating the steps until the adjacent measuring points have no bulge abnormal points, and forming a bulge area data set by all bulge abnormal points in the process. And recording the point position P with the maximum height of the bulge in the bulge area data setmaxAnd a bump height value hmax。
If not, marking the current abnormal point of the bulge as interference data and obtaining a final abnormal point data set QΔAnd (5) removing.
And repeating the current step until the searching and recording of the bulge area of the measuring surface are completed.
Step 10.3: and controlling the scanning gantry 1 and the vertical walking tray 8 to convey the dot painting mechanical telescopic arm 9 to the corresponding position of the edge of the bulge area of the measuring surface, controlling the dot painting mechanical telescopic arm 9 to extend to the measuring surface 21 of the target scanning component 2, completing the description of one point, walking the whole error area boundary one by one, and completing the marking of the error area.
Step eleven: according to the above steps, the detection of all the measurement surfaces of the target scanning member 2 is completed. And generating an electronic detection report, and making clear identification on the measurement head bulge area which influences the assembly of the components and the data of the area in the report to finish all detection on the target scanning component 2.
Therefore, the invention has the advantages that:
1. the gantry type walking structure is adopted, the multidirectional moving motor and the track are loaded on the gantry, the measurement work of the assembled surface in any shape can be completed, various sensors are loaded on the gantry, the temperature and the humidity of the track, the gantry and air are monitored in real time, the measurement result is corrected through the temperature and humidity monitoring result, and the system can work under the complex climate condition without affecting the precision.
2. In the actual measurement process, various factors influencing manufacturing precision scanning such as concave-convex mortises, rubber channels, air bubble pits, stone particles and slight edge breakage can exist on the splicing surface of the target scanning component. Firstly, the boundary data of the target scanning component is quickly found out by using methods such as successive approximation, shadow shape following and the like, and then influence factors are eliminated step by using algorithm means such as a correlation search algorithm, a theoretical model reference method, an overall trend deduction method and the like, so that the calculation of the manufacturing precision of the prefabricated component splicing surface is completed.
3. After the scanning measurement of a component is completed, the system calculates the boundary point coordinate data set of the bulge area, the portal frame is controlled to carry the painting device to move to the corresponding position of each boundary point one by one, the bulge boundary point painting is carried on the surface of the component, workers can quickly find out the bulge position by comparing detection reports when the later stage is convenient to polish and repair, and the polishing difficulty and the workload are greatly reduced.
It should be apparent that the foregoing description and illustrations are by way of example only, and are not intended to limit the present disclosure, application or uses. While embodiments have been described in the embodiments and depicted in the drawings, the present invention is not limited to the particular examples illustrated by the drawings and described in the embodiments as the best mode presently contemplated for carrying out the teachings of the present invention, and the scope of the present invention will include any embodiments falling within the foregoing description and the appended claims.

Claims (10)

1. A method for intelligently scanning manufacturing accuracy and automatically identifying errors of a prefabricated part assembling surface is characterized by comprising the following steps of:
the method comprises the following steps: a preparation step, namely hoisting a target scanning component into a measurement area on a component scanning table;
step two: starting, namely opening an electric roller shutter door of a warehouse, starting a scanning gantry, and starting scanning detection;
step three: adjusting the height of the vertical walking tray to make the light of the laser measuring equipment close to the height of the upper surface of the component scanning table;
step four: scanning the gantry to move forwards from the warehouse along the horizontal walking track, and acquiring the laser measurement value of the laser range finder and the monitoring values of the scanning gantry temperature and humidity sensor, the vertical track temperature and humidity sensor and the horizontal track temperature and humidity sensor in real time in the walking process;
step five: acquiring a laser measurement value of the laser range finder in real time during walking, judging whether a light spot of the laser range finder hits on a target scanning component, and if so, stopping horizontal advance of the scanning gantry;
step six: determining the boundary profile of the measurement surface in the target scanning member, all boundary points forming a boundary point data set Q0；
Step seven: completing data acquisition of the measuring surface to form a laser point cloud data set Q1；
Step eight: correcting the placing posture of the target scanning component to an ideal placing posture;
step nine: analyzing the measurement data of the corrected measurement surface of the target scanning component, and eliminating abnormal measurement values of the measurement surface of the target scanning component;
step ten: determining the manufacturing precision of the assembled surface of the target scanning component, and spraying marks on the surface of the target scanning component in the error area;
step eleven: and generating a detection report, and finishing all detections on the target scanning component.
2. The intelligent scanning and automatic error identification method for the assembling surface of the prefabricated part as claimed in claim 1, wherein the method comprises the following steps: the concrete method of the step five is as follows: left laser rangefinder measurement L when laser rangefinder spot strikes target scanning memberl+ right laser rangefinder measurement LrWhen the current measured value is less than or equal to L, the target scanning component 2 is judged to be detected, and the current measured values of the two laser range finders are recorded as
Figure FDA0003565415530000021
And
Figure FDA0003565415530000022
3. the intelligent scanning and automatic error identification method for the splicing surface of the prefabricated part as claimed in claim 1, wherein the method comprises the following steps: in the sixth step, the stopping point in the fifth step is taken as a starting point, the boundary point of the target scanning component corresponding to the current height in the horizontal direction is searched by utilizing a tortuous semi-gradual approximation method, and the boundary point is marked as the first boundary point P of the target scanning component0Taking the forward direction of the horizontal walking track as the positive direction of an x axis, the upward direction of the vertical walking track as the positive direction of a y axis, the measured value of the laser range finder as the coordinate value of a z axis and the first boundary point P of the target scanning component0Establishing an xyz coordinate system for the origin of coordinates, from the origin of coordinates P0Start along a clockwise timeCapturing the rest boundary points of the peripheral outline of the measuring surface of the target scanning component in the needle direction, combining the theoretical data model of the target scanning component in the process, continuously reducing the searching times of the subsequent boundary points by using a rapid iteration method, accelerating the capturing speed of the rest boundary points, and finally forming a boundary point data set Q by all the boundary points0。
4. The intelligent scanning and automatic error identification method for the splicing surface of the prefabricated part as claimed in claim 3, characterized by further comprising the following steps:
step 6.1: when the gantry is scanned and walks forward one step each time, the measurement values of the laser range finders at two sides of the current position are collected and recorded as
Figure FDA0003565415530000023
And
Figure FDA0003565415530000024
calculating the change rate of the laser range finder measurement values at the two sides of the current position and the previous step position, wherein the change rate of the left measurement value is
Figure FDA0003565415530000031
The rate of change of the right-hand measurement value is
Figure FDA0003565415530000032
Comparison KlnAnd KrnSize:
when the temperature is higher than the set temperature
Figure FDA0003565415530000033
During the measurement, the laser range finder light spots on the two sides are respectively projected on the corresponding measuring surfaces in the front and back two times of measurement, so that the detection of the target measuring surface is completed;
when in use
Figure FDA0003565415530000034
During measurement, the light spot of the laser range finder on one side does not completely hit a corresponding measuring surface after twice measurement; scanning dragonThe door 1 continues to travel horizontally forward along the horizontal travel rail 5 by the step S until
Figure FDA0003565415530000035
Step 6.2: continuing to walk the laser range finder corresponding to the target measuring surface in the step 6.1 upwards by a step length S along the vertical walking track, and determining the change rate of the measured value in the y-axis direction;
step 6.3: the mobile laser range finder retreats to the first measuring point in the current measuring surface and starts to acquire a first scanning boundary point P in a winding and semi-walking mode0；
Step 6.4: obtaining a first scanning boundary point P0Then, with P0Taking the horizontal advancing direction of a scanning gantry as the positive direction of an x axis, the scanning vertical upward direction of a laser range finder as the positive direction of a y axis, and the measurement value of the laser range finder as the coordinate value of a z axis as the origin of coordinates, establishing an xyz coordinate system to obtain P0Point coordinates (x)0,y0,z0) I.e., (0,0, 0);
step 6.5: and performing subsequent boundary point capture on the basis of the first scanning boundary point, and completing capture of all boundary points of the target scanning component.
5. The intelligent scanning and automatic error identification method for the splicing surface of the prefabricated part as claimed in claim 3, wherein the method comprises the following steps: the concrete steps of the step eight are as follows:
step 8.1: putting the theoretical model in the coordinate system established in the sixth step, and measuring the bottom left corner point P of the surface of the theoretical model0 ′P of measuring plane with target scanning member0Point coincidence, the bottom boundary of the theoretical model measuring surface is coincided with the x axis, and the left boundary of the theoretical model measuring surface is coincided with the y axis to obtain a data set Q of the theoretical model measuring surface′ 1；
Step 8.2: coupling the measuring surface in actual placement with the measuring surface of the theoretical model to complete the posture inversion correction of the target scanning component to obtain a corrected laser point cloud data set Q1_3And a boundary point data set Q0_3。
6. The intelligent scanning and automatic error identification method for the splicing surface of the prefabricated part as claimed in claim 5, wherein the method comprises the following steps: the concrete steps of the ninth step are as follows:
step 9.1: traversing corrected laser point cloud data set Q1_3And a boundary point data set Q0_3Comparing the laser point cloud data set Q1_3And a boundary point data set Q0_3Intermediate measurement and theoretical model data set Q′ 1Whether the measured values of the middle-identical xy coordinate positions are identical or not and the difference exceeds the minimum precision delta S of the measurement dotting0Coordinate points of (2) are stored in an abnormal point data set Q△0Performing the following steps;
step 9.2: abnormal point data set Q△0Eliminating abnormal points reasonably existing in the abnormal point data set, and defining the abnormal point data set after eliminating the abnormal points reasonably existing in the abnormal point data set as Q△1；
Step 9.3: abnormal point data set Q with abnormal points reasonably existing after traversal elimination△1Taking out the measuring points in the data set one by one, and comparing the relation between the current point and the measuring values of the peripheral measuring points on the measuring surface by using a correlation search method with the current point as the center; obtaining a laser point cloud data set Q of the current point after correction1_3And comparing the measured values of all the measuring points in the 5-by-5 point area of the middle square circle with the measured values of the current measuring point in sequence, and if the measured values of all the peripheral measuring points are greater than or less than the measured values of the current measuring point, judging that the current measuring point is a local defect point.
7. The utility model provides a face intelligent scanning and error automatic identification system are assembled to prefabricated component, includes workstation, storehouse, scanning longmen, horizontal walking track and component scanning platform, its characterized in that:
the warehouse is located at one end of the workbench and is provided with a containing space for containing the scanning gantry and an electric gate, the horizontal walking tracks are two tracks and extend along two sides of the workbench, one end of the horizontal walking track extends into the warehouse, the framework scanning table is located on the workbench and is arranged in the middle of the horizontal walking track so as to be used for placing a target scanning component, the scanning gantry is slidably arranged on the horizontal walking track and is a portal-shaped walking mechanism which walks on the horizontal walking tracks on two sides of the framework scanning table, two inner sides of the scanning gantry are respectively provided with a vertical walking track, a vertical walking tray is respectively arranged on the vertical walking track to move up and down along the vertical walking track, and the vertical walking tray is provided with a laser measuring device and a mounting seat of a stretching arm of a drawing point painting machine.
8. The system for intelligent scanning and automatic error identification of assembled surfaces of prefabricated parts according to claim 7, wherein: the laser measuring equipment is fixed at the upper end of the mounting seat and is a single-point laser range finder, and the telescopic arm of the dot printing machine is fixed at the lower end of the mounting seat and can be controlled to print color spots on the designated surface through telescopic control.
9. The system for intelligent scanning and automatic error identification of assembled surfaces of prefabricated parts according to claim 7, wherein: the scanning gantry comprises a scanning gantry body, a horizontal walking limiting device, a horizontal walking motor and a horizontal walking encoder, wherein the scanning gantry body is arranged on the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, and the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, two sides of the scanning gantry body, the scanning gantry body of the scanning gantry body, the scanning gantry body is arranged in the scanning gantry body, two sides of the scanning gantry body, the scanning gantry body of the scanning gantry body, two sides of the scanning gantry body, two sides of the scanning gantry body, two ends of the scanning gantry body, and the scanning gantry body.
10. The system for intelligent scanning and automatic error identification of assembled surfaces of prefabricated parts according to claim 9, wherein: and a vertical walking motor and a vertical walking encoder are arranged at the lower end of the connecting point of the vertical walking track and the scanning gantry bottom beam to drive the vertical walking tray to move up and down and record the position of the vertical walking tray.
CN202210300941.1A 2022-03-25 2022-03-25 Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface Active CN114719792B (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CN202210300941.1A CN114719792B (en) 2022-03-25 2022-03-25 Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface
PCT/CN2022/083579 WO2023178713A1 (en) 2022-03-25 2022-03-29 Intelligent scanning and automatic error identification system and method for assembly surface of prefabricated member
JP2023523264A JP2024519633A (en) 2022-03-25 2022-03-29 System and method for intelligent scanning of prefabricated component assembly surfaces and automatic error identification

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210300941.1A CN114719792B (en) 2022-03-25 2022-03-25 Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface

Publications (2)

Publication Number Publication Date
CN114719792A true CN114719792A (en) 2022-07-08
CN114719792B CN114719792B (en) 2022-12-13

Family

ID=82240057

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210300941.1A Active CN114719792B (en) 2022-03-25 2022-03-25 Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface

Country Status (3)

Country Link
JP (1) JP2024519633A (en)
CN (1) CN114719792B (en)
WO (1) WO2023178713A1 (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117092114A (en) * 2023-10-16 2023-11-21 苏州德机自动化科技有限公司 Appearance detection system based on AI
TWI823567B (en) * 2022-09-15 2023-11-21 財團法人工業技術研究院 Object volume measurement system and method thereof

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118139391B (en) * 2024-05-07 2024-06-25 通号信息产业有限公司 Assembled building BIM module management device and management method thereof

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010060556A (en) * 2008-09-04 2010-03-18 Samsung Heavy Industries Co Ltd System and method for measuring curved member
EP2998727A1 (en) * 2014-09-19 2016-03-23 Asahi Glass Company, Limited Ceramic member and defect test system
US20160264163A1 (en) * 2015-03-12 2016-09-15 Mi-Jack Products, Inc. Profile detection system and method
CN106127770A (en) * 2016-06-27 2016-11-16 感知控股集团有限公司 Contour measuring method and system
CN106706666A (en) * 2017-03-28 2017-05-24 温馨 Detecting and marking device for large cement component surface defects
CN108253896A (en) * 2018-03-06 2018-07-06 大连理工大学 A kind of car dimension measuring device based on laser sensor
JP2018179889A (en) * 2017-04-20 2018-11-15 Ｊｆｅスチール株式会社 Calibration piece, calibration method, shape measurement system and shape measurement method
CN111536901A (en) * 2020-05-21 2020-08-14 南京航空航天大学 Combined three-dimensional laser scanning measurement method based on field gantry and robot
CN215572719U (en) * 2021-08-04 2022-01-18 深圳大学 Detection apparatus for vertical prefabricated component

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106996758A (en) * 2017-05-13 2017-08-01 朱嘉懿 A kind of Large Precast Members surface defects detection and indication device
CN112097070A (en) * 2020-07-22 2020-12-18 南京工业大学 Auxiliary device and method for producing prefabricated parts of assembly type building with movable portal frame
CN113450379B (en) * 2021-07-02 2022-05-27 湖南国天电子科技有限公司 Method and device for extracting and analyzing profile line of section of special-shaped workpiece

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010060556A (en) * 2008-09-04 2010-03-18 Samsung Heavy Industries Co Ltd System and method for measuring curved member
EP2998727A1 (en) * 2014-09-19 2016-03-23 Asahi Glass Company, Limited Ceramic member and defect test system
US20160264163A1 (en) * 2015-03-12 2016-09-15 Mi-Jack Products, Inc. Profile detection system and method
CN106127770A (en) * 2016-06-27 2016-11-16 感知控股集团有限公司 Contour measuring method and system
CN106706666A (en) * 2017-03-28 2017-05-24 温馨 Detecting and marking device for large cement component surface defects
JP2018179889A (en) * 2017-04-20 2018-11-15 Ｊｆｅスチール株式会社 Calibration piece, calibration method, shape measurement system and shape measurement method
CN108253896A (en) * 2018-03-06 2018-07-06 大连理工大学 A kind of car dimension measuring device based on laser sensor
CN111536901A (en) * 2020-05-21 2020-08-14 南京航空航天大学 Combined three-dimensional laser scanning measurement method based on field gantry and robot
CN215572719U (en) * 2021-08-04 2022-01-18 深圳大学 Detection apparatus for vertical prefabricated component

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
张立斌等: "基于激光点云的车辆外廓尺寸动态测量方法", 《华南理工大学学报（自然科学版）》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI823567B (en) * 2022-09-15 2023-11-21 財團法人工業技術研究院 Object volume measurement system and method thereof
CN117092114A (en) * 2023-10-16 2023-11-21 苏州德机自动化科技有限公司 Appearance detection system based on AI
CN117092114B (en) * 2023-10-16 2023-12-29 苏州德机自动化科技有限公司 Appearance detection system based on AI

Also Published As

Publication number Publication date
WO2023178713A1 (en) 2023-09-28
CN114719792B (en) 2022-12-13
JP2024519633A (en) 2024-05-21

Similar Documents

Publication Publication Date Title
CN114719792B (en) Intelligent scanning and automatic error identification system and method for prefabricated part assembling surface
US11188688B2 (en) Advanced automated process for the wing-to-body join of an aircraft with predictive surface scanning
CN111268530B (en) Method and apparatus for measuring, positioning and installing elevator shaft
CN109367693B (en) Allowance-free installation method for large equipment base for ship
CN108896014B (en) Tunnel section measuring device and measuring method thereof
CN110500955B (en) Image modeling track inspection vehicle and detection method for straddle type monorail
CN206056503U (en) A kind of point source scans the detection means of weld seam
CN113902799A (en) Intelligent robot dust removal system and method based on machine vision
CN117612753B (en) Automatic detection device and method for gap between fuel rods of nuclear fuel assembly
CN114646263B (en) Intelligent scanning and automatic error identification system for manufacturing precision of prefabricated part assembling surface
CN113916214A (en) Multi-algorithm fusion positioning method and purging method for rail transit vehicle bottom dust removal
WO2020042777A1 (en) Intelligent quality detection and evaluation system and method for supporting structure accessories
CN116921948A (en) Automatic acquisition method and automatic acquisition system for welding line of ship structural plate
CN114674226B (en) Method for scanning and rapidly capturing boundary of prefabricated component
CN114674225B (en) Prefabricated component assembling surface manufacturing error identification algorithm
CN114663403B (en) Prefabricated part assembling surface local defect identification method based on dense scanning data
CN113375598A (en) Self-datum plane-based high-precision matching method for three-dimensional profile of blade
KR101738855B1 (en) Construction method for grinding the surface of concrete guideway
CN114707100B (en) Prefabricated assembly component space attitude inversion correction method based on laser scanning point cloud
CN110841271A (en) Intelligent basketball court line drawing method and system
CN216440971U (en) Automatic curtain wall gluing system
CN111366086B (en) Carriage pose measurement system and method for automatic loading
KR102361824B1 (en) Image acquisition apparatus for lower surface of bridge deck and method for automatically evaluating condition of bridge deck using the same
CN117470127B (en) Unmanned aerial vehicle building wall surface detection system and method based on coordinate correction
CN220322295U (en) Automatic detection equipment for spot welding of two-piece type panel

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant