CN113048886B - Method and apparatus for measuring size of irregular body of workpiece - Google Patents
Method and apparatus for measuring size of irregular body of workpiece Download PDFInfo
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/04—Indexing scheme for image data processing or generation, in general involving 3D image data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
Abstract
The invention discloses a measuring method and a device for measuring the size of an irregular body of a workpiece, and the measuring method is characterized by comprising the following steps: fixing a workpiece to be measured at a specific position of a tool, scanning the workpiece to be measured by a multi-joint three-dimensional laser scanner, and acquiring point cloud data of the workpiece; processing point cloud data of a workpiece obtained by scanning; constructing a space model based on the processed point cloud data; the volume of the spatial model is calculated. The apparatus is characterized by comprising: a scanning device, one or more processors, and a storage device; the invention solves the problem of measuring the size of the irregular body of the workpiece, and has higher measurement precision compared with the traditional method.
Description
Technical Field
The invention relates to the technical field of volume measurement of mechanical workpieces, in particular to a measuring method and measuring equipment for measuring the size of an irregular body of a mechanical workpiece.
Background
When machining machine parts with numerically controlled machines, it is often required to accurately measure the dimensions of irregularities on a workpiece to determine whether the machining of the workpiece irregularities meets design requirements.
At present, a three-coordinate measuring machine is generally used for measuring point coordinates of the workpiece irregular body, then data are transmitted to a computer to obtain space discrete points of the workpiece irregular body, a space model is built in a triangular net building mode according to the space discrete points, and the computer calculates the volume of the irregular body according to the built space model.
The methods adopted at present are a square grid method, a DTM method or a contour method, but the methods have some defects, such as inaccurate calculation, narrow application range and the like.
Disclosure of Invention
The invention aims to provide a measuring method and measuring equipment for measuring the size of an irregular body of a workpiece.
In a first aspect, the present invention provides a measuring method for measuring the size of an irregular body of a workpiece, which is characterized by comprising:
step 1: fixing a workpiece to be measured at a specific position of a tool, scanning the workpiece to be measured by a multi-joint three-dimensional laser scanner, and acquiring point cloud data of the workpiece;
step 2: processing point cloud data of a workpiece obtained by scanning of a multi-joint three-dimensional laser scanner;
and step 3: constructing a space model based on the processed point cloud data;
and 4, step 4: the volume of the spatial model is calculated.
Optionally, in an embodiment of the present invention, step 1: the workpiece to be measured is fixed at a specific position of the tool, and is scanned by the multi-joint three-dimensional laser scanner to obtain point cloud data of the workpiece, wherein the point cloud data comprises:
in the scanning step of the workpiece to be detected, scanning the appointed profile or area of the workpiece by adopting an optical measuring probe to obtain point cloud data of the workpiece;
in the scanning step of the workpiece to be detected, a non-contact measuring probe is adopted to scan the appointed profile or area of the workpiece to obtain point cloud data of the workpiece;
step 1, before scanning operation, determining the layout position of the controllable points and reasonably arranging a scanning and measuring station route, wherein the controllable points can control the whole measuring area and are uniformly distributed, and the multi-joint three-dimensional laser scanner scans according to the scanning and measuring station route to ensure that adjacent measuring stations have a certain proportion of overlapping degree.
Optionally, in an embodiment of the present invention, step 2: processing point cloud data obtained by scanning with a multi-joint three-dimensional laser scanner, comprising:
carrying out point cloud registration on the point cloud data, and minimizing the space position difference between the point cloud data through the point cloud registration, specifically: 1/2, performing point cloud registration by selecting a target ball target and adopting not less than 3 homonymous points, wherein the accuracy of the homonymous points after registration is not lower than the error in the characteristic point interval required by the specification;
converting coordinate systems of the point cloud data after registration, converting coordinate systems of a plurality of scanners into a unified coordinate system through the coordinate system conversion, specifically, converting the coordinate systems through a seven-parameter model by adopting at least 3 uniformly distributed homonymous points, preferably fixing a scale factor during conversion, and enabling a conversion residual to be smaller than 1/2 of an error of a point location allowed by a specification relative to an adjacent control point;
the point cloud data after conversion is subjected to point cloud classification, so that the point cloud data can be conveniently separated and a surface model can be conveniently constructed in the later stage, and the method specifically comprises the following steps: dividing the point cloud data into different categories according to the electromagnetic wave reflection intensity information characteristics of different target objects, and classifying and labeling the point cloud data according to the different categories;
the classified point cloud data is divided and rarefied so as to be beneficial to carrying out three-dimensional curved surface reconstruction on huge point cloud data, and the method specifically comprises the following steps: the detailed characteristics of the point cloud data model are fully considered, a non-uniform grid method is adopted for the point cloud data model, the detailed characteristics are kept not to be deleted, and the maximum point distance after the point cloud data is diluted meets the minimum distance requirement of the calculation volume.
Optionally, in an embodiment of the present invention, step 3: constructing a space model based on the processed point cloud data, wherein the space model comprises a point processing stage and a finite element processing stage:
the point processing stage: processing the point cloud data to remove isolated points, non-connection points and noise points in vitro; sampling the removed point cloud data so as to keep the accuracy of the space model;
the finite element processing stage: processing the point cloud data after sampling processing by a finite element method; the method specifically comprises the following steps: packaging the point cloud data into a polygonal model, and editing the polygonal model, wherein the editing comprises nail removal, hole filling and boundary filling; the edited polygon model is divided into a limited number of virtual small cube elements with equal shape and size.
Optionally, in an embodiment of the present invention, step 4: calculating a volume of the spatial model, comprising:
fitting the external curved surface of the small cubic element by using an integral principle;
and calculating the normal vector of the curved surface according to the known point cloud data on the curved surface, and calculating the volume of the space model by using a cylindrical integration principle.
The calculation step of the space model comprises the following steps:
calculating the maximum X in the X-axis direction of a space rectangular coordinate system according to a point cloud space data modelmaxAnd minimum value XminMaximum value Y in Y-axis directionmaxAnd minimum value Ymin；
Further, a space rectangular coordinate system is established according to the single small cubic elementO-XYZThe X ' axis, the Y ' axis and the Z ' axis are respectively parallel to the X axis, the Y axis and the Z axis, the number of points in a single small cubic unit is taken as a reference, the fitting method suitable for the small cubic unit is judged, the surfaces are fitted one by one, and the normal vector of a certain point is taken as
Calculating the normal vector
The minimum value of the included angle delta between the X axis, the Y axis, the Z axis and the opposite directions, the plane vertical to the corresponding coordinate axis at the moment is used as the calculation surface of the integral, and the X axis, the Y axis, the Z axis and the opposite directions are alignedThe normal vector direction should be taken as the integration direction.
Further, the quadratic surface fitting of the small cubic unit formed by dividing the space model is a surface fitting by using a least square method, and specifically comprises the following steps: the method includes the steps of firstly, selecting data points which basically reflect the shape of a curved surface and are uniformly distributed, generating a curved surface which basically reflects the shape of a molded surface and is good in performance by utilizing a curved surface skin technology, and calling the curved surface as an initial curved surface, then finding corresponding points of the data points on the initial curved surface according to a certain mapping relation, calling parameter values of the points as parameter values of the data points on the initial curved surface, simultaneously establishing an overdetermined linear equation set, and finally solving the overdetermined linear equation set by utilizing a least square method to obtain the best fit curved surface of the data points.
According to the formula (1), the equation of the quadric of the ten-parameter surface fitting principle is given, wherein the normal vectors are in the z-axis direction.
Ax2+Bx2+Cx2+D+Exy+Fxz+Gx+Hyz+Jy+kz=0 (1)
Formula (2) is a three-dimensional spaceR 3A normal vector.
Wherein:
further, the curved surface characteristic parameters of the small cubic unit are obtained, the volume of each small cubic unit is calculated by a double integral method, and then the volume of the measured workpiece is obtained.
In a second aspect, the present invention further provides a measuring apparatus for measuring the size of an irregular body of a workpiece based on the above measuring system, which is characterized in that the measuring apparatus comprises:
the scanning device is three or more multi-joint three-dimensional laser scanners;
one or more processors;
a storage device to store one or more programs.
After the three or more multi-joint three-dimensional laser scanners acquire point cloud data of the workpiece, the one or more programs are executed by the one or more processors to cause the one or more processors to implement the method for measuring the size of the irregular body of the workpiece as provided by any of the embodiments of the invention.
The method comprises the steps of obtaining point cloud data of the surface of a workpiece by using a multi-joint three-dimensional laser scanner, denoising and filtering the point cloud data, constructing the point cloud data into a space model, and then dividing the space model into a plurality of finite elements; and performing quadratic surface fitting on the units of the space model to obtain surface characteristic parameters, and calculating the volume of the space model by using an integral method to further obtain the volume of the workpiece. Compared with the result of the traditional method, the measurement method for the size of the irregular body of the workpiece provided by any embodiment of the invention has the advantages that the volume precision of the measured workpiece is higher by one order of magnitude than the traditional calculation precision, and the relative precision reaches 1:20 ten thousand.
Compared with the traditional processing mode, the point cloud data processing method added in the point cloud data processing process has the advantages that when the point cloud data is used for building a space model, the reconstruction time of the space model can be saved, and a large amount of system resources are saved; meanwhile, the point cloud data of the surface of the workpiece are correctly and fully scanned through technical means such as point cloud registration and coordinate system conversion, the noise condition of the point cloud is fully considered in a point cloud data modeling module, reasonable finite elements are divided, compared with the traditional processing mode, the method has the advantages that the number of points on a fitting surface and the size of a divided cubic element are reasonably processed, and the volume is calculated through a finite element integration method, so that the measurement precision of the volume of the workpiece is greatly improved, and reliable data are provided for engineering budget.
Drawings
FIG. 1 is a flow chart of a method for measuring the size of an irregularity in a workpiece according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of processing modules in a measurement method for measuring the size of an irregularity in a workpiece according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for processing point cloud data according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a measurement apparatus for measuring the size of an irregular body of a workpiece according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
The present embodiment provides a measurement method for measuring the size of an irregular body of a workpiece, and referring to the flowchart of fig. 1, the measurement method includes:
101. fixing a workpiece to be measured at a specific position of the tool, determining the layout position of the controllable points, reasonably arranging a scanning survey station route, and scanning the workpiece to be measured by the multi-joint three-dimensional laser scanner of the scanning module 201.
Further, in this embodiment, determining the layout position of the controllable point specifically includes: the control points can control the whole measuring workpiece and are uniformly distributed, at least 3 points are arranged on the controllable points to meet the requirement of coordinate conversion, and the multi-joint three-dimensional laser scanner scans according to the scanning measuring station route to ensure that a certain proportion of overlapping degree exists between adjacent scanning measuring stations.
Further, in this embodiment, the multi-joint three-dimensional laser scanner scans the workpiece to be measured, and includes:
and scanning the appointed profile or area of the workpiece by adopting an optical measuring probe to obtain point cloud data of the measured workpiece, or scanning the appointed profile or area of the workpiece by adopting a non-contact measuring probe to obtain point cloud data of the measured workpiece.
102. The point cloud data processing module 202 processes the point cloud data of the workpiece to be measured, which is obtained by scanning the multi-joint three-dimensional laser scanner.
Specifically, the processing of the point cloud data in this embodiment includes:
performing point cloud registration on the point cloud data to minimize spatial location differences between the point cloud data; the method specifically comprises the following steps: by selecting a target ball target and adopting not less than 3 homonymous points to carry out point cloud registration, the internal conforming precision of the homonymous points after registration is not lower than 1/2 of the error in the characteristic point spacing required by the specification.
Converting the coordinate system of the point cloud data after registration to convert the coordinate systems of the plurality of scanners into a unified coordinate system; the method specifically comprises the following steps: at least 3 uniformly distributed homonymous points are adopted, coordinate system conversion is carried out through a seven-parameter model, a scale factor is preferably fixed during conversion, and the conversion residual error is smaller than 1/2 of the error of a point position relative to an adjacent control point allowed by a specification.
The converted point cloud data is subjected to point cloud classification, so that the point cloud data can be separated and a surface model can be constructed conveniently in the later period; the method specifically comprises the following steps: and classifying the point cloud data into different categories according to the electromagnetic wave reflection intensity information characteristics of different targets (for example, classifying according to the material of the workpiece), and classifying and labeling the point cloud data according to the different categories.
Dividing and thinning the classified point cloud data so as to be beneficial to carrying out three-dimensional curved surface reconstruction on huge point cloud data; the method comprises the following steps: and fully considering the detail characteristics of the point cloud data model, adopting a non-uniform grid method for the point cloud data model, keeping the detail characteristics from being deleted, and enabling the maximum point distance after the point cloud data is diluted to meet the minimum distance requirement of the calculated volume.
103. The point cloud data modeling module 203 constructs a spatial model for the processed point cloud data, and the specific steps of modeling the point cloud data in this embodiment include a point processing stage and a finite element processing stage:
performing point processing on the point cloud data, specifically: removing in-vitro isolated points, non-connection points and noise points, judging and deleting point clouds with larger offset distances in the model by calculating the distance between the point clouds and the model, and sampling the point cloud data after removing, thereby keeping the accuracy of the space model and avoiding generating larger deformation.
Carrying out finite element processing on the point cloud data, specifically: and encapsulating the point cloud data to generate a polygonal model, editing the polygonal model, namely deleting nails, filling holes and repairing boundaries, and dividing the polygonal model into a limited number of virtual small cubic elements with equal shapes and sizes.
104. Performing quadratic surface fitting on the small cube element unit formed by dividing the polygonal model by a calculating module 204, and fitting out an external surface of the small cube element by using an integral principle; and calculating the normal vector of the curved surface according to the known point cloud data on the curved surface, and calculating the volume of the space model by using a cylindrical integration principle.
The calculation step of the space model volume comprises the following steps:
calculating the maximum X in the X-axis direction of a space rectangular coordinate system according to a point cloud space data modelmaxAnd minimum value XminMaximum value Y in Y-axis directionmaxAnd minimum value Ymin。
Further, a space rectangular coordinate system is established according to the single small cubic elementO-XYZAnd the X ' axis, the Y ' axis and the Z ' axis are respectively parallel to the X axis, the Y axis and the Z axis, and the fitting method suitable for the axes is judged and the curved surfaces are fitted one by taking the number of the inner points of a single small cubic unit as a reference. Let the normal vector of a certain point be
Calculating the normal vector
The minimum value of included angles delta between the X axis, the Y axis, the Z axis and the respective opposite directions, and the plane vertical to the corresponding coordinate axis is taken as the starting point of integralAnd the corresponding normal vector direction is taken as an integral direction.
Further, the quadratic surface fitting of the small cubic unit obtained by the division is a surface fitting by using a least square method, and specifically comprises the following steps: the method comprises the steps of firstly selecting data points which basically reflect the shape of a curved surface and are uniformly distributed, generating a curved surface which basically reflects the shape of a molded surface and is good in performance by using a curved surface skin technology, and calling the curved surface as an initial curved surface, then finding corresponding points of the data points on the initial curved surface according to a certain mapping relation, calling parameter values of the points as parameter values of the data points on the initial curved surface, simultaneously establishing an overdetermined linear equation set, and finally solving the overdetermined linear equation set by using a least square method to obtain the best fit curved surface of the data points.
According to the formula (1), the equation of the quadric of the ten-parameter surface fitting principle is given, wherein the normal vectors are in the z-axis direction.
Ax2+Bx2+Cx2+D+Exy+Fxz+Gx+Hyz+Jy+kz=0 (1)
Formula (2) is a three-dimensional spaceR 3A normal vector.
Wherein the content of the first and second substances,
further, the curved surface characteristic parameters of the small cubic unit are obtained, the volume of each small cubic unit is calculated by a double integral method, and then the space model, namely the volume of the measured workpiece, is obtained.
Illustratively, taking the integration along the z-direction as an example, equation (3) is given as a ten-parameter fitting surface volume integral equation.
Where Ω represents the solid volume and x in the formula2、x1Respectively the maximum value and the minimum value in the x-axis direction of a space rectangular coordinate system, y2、y1The maximum value and the minimum value in the y-axis direction of the space rectangular coordinate system are respectively.
Example two
Based on the above embodiments, fig. 3 is a flowchart of a point cloud data processing method provided in this embodiment, and this embodiment discloses a specific processing flow of the point cloud data processing module 202 in the previous embodiment, which includes point cloud registration 301, coordinate transformation 302, point cloud classification 303, and segmentation rarefaction 304.
Wherein point cloud registration 301 is used to minimize spatial location differences between point cloud data; coordinate transformation 302 is used to transform multiple scanner coordinate systems into a unified coordinate system; the point cloud classification 303 facilitates later point cloud data separation and surface model construction; the segmentation thinning 304 facilitates three-dimensional surface reconstruction of large point cloud data.
In this embodiment, the method for point cloud registration 301 includes:
by selecting a target ball target and adopting not less than 3 homonymous points to carry out point cloud registration, the internal conforming precision of the homonymous points after registration is not lower than 1/2 of the error in the characteristic point spacing required by the specification.
In this embodiment, the method for coordinate transformation 302 includes:
at least 3 uniformly distributed homonymous points are adopted, coordinate system conversion is carried out through a seven-parameter model, a scale factor is preferably fixed during conversion, and the conversion residual error is smaller than 1/2 of the error of a point position relative to an adjacent control point allowed by a specification.
In this embodiment, the method for point cloud classification 303 includes:
and classifying the point cloud data into different categories according to the electromagnetic wave reflection intensity information characteristics of different target objects (for example, classifying according to the material of the workpiece to be detected), and classifying and labeling the point cloud data according to the different categories.
In this embodiment, the method for splitting the rarefaction 304 includes:
and (3) performing segmentation and thinning on the point cloud data, fully considering the detail characteristics of the point cloud data model, adopting a non-uniform grid method for the point cloud data model, keeping the detail characteristics from being deleted, and enabling the maximum point distance after thinning of the point cloud data to meet the minimum distance requirement of the calculated volume.
EXAMPLE III
The present embodiment provides a measuring apparatus for measuring the irregular body size of a workpiece, as shown in fig. 4, the apparatus includes a scanning device 401, a processor 402, a memory 403, an input device 404, and an output device 405; the number of the processors 402 in the device may be one or more, and one processor 402 is taken as an example in fig. 4; the scanning means 401, the processor 402, the memory 403, the input means 404 and the output means 405 of the device may be connected by a bus or other means, as exemplified by the bus connection in fig. 4.
The scanning device 401 is configured to scan a designated profile or area of a workpiece, obtain point cloud data of the measured workpiece, and store the scanned point cloud data in the memory 403 through the input device 404. In addition, the scanning device 401 employs a multi-joint three-dimensional laser scanner, and may employ an optical measurement probe or a non-contact measurement probe to acquire point cloud data of a measurement workpiece.
The memory 403 is used as a computer readable storage medium for storing the point cloud data generated by the scanning device 401, software programs, computer executable programs, and modules, such as program instructions/modules corresponding to the measuring method of the irregular body size of the workpiece in the embodiment of the present invention (for example, the scanning module 201, the point cloud data processing module 202, the point cloud data modeling module 203, and the calculating module 204 in the measuring device of the irregular body size of the workpiece). The processor 402 executes various functional applications of the apparatus and data processing by executing software programs, instructions and modules stored in the memory 403, namely, the above-mentioned method for measuring the size of the irregular body of the workpiece is realized.
The memory 403 mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system and an application program required by at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 403 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 403 may further include memory located remotely from processor 402, which may be connected to devices through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 404 may be used to receive scan data input by the scanning means 401 and to generate key signal inputs relating to user settings and function control of the apparatus. The output device 405 may include a display device such as a display.
From the above description of the embodiments, it is obvious for a person skilled in the art that the present invention can be implemented by software and necessary hardware, and certainly by hardware, but the former is a better embodiment in many cases. It should be understood that although the present invention has been described with respect to the above preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention, and therefore, the scope of the invention is to be defined by the appended claims.
Claims (4)
1. A measuring method for measuring the size of an irregular body of a workpiece is characterized by comprising the following steps:
step 1: fixing a workpiece to be measured at a specific position of a tool, scanning the workpiece to be measured by a multi-joint three-dimensional laser scanner, and acquiring point cloud data of the workpiece;
step 2: processing point cloud data of a workpiece obtained by scanning;
and step 3: constructing a space model based on the processed point cloud data;
and 4, step 4: calculating the volume of the spatial model;
wherein, step 2 includes:
carrying out point cloud registration on the point cloud data, and minimizing the space position difference between the point cloud data through the point cloud registration, specifically: 1/2, performing point cloud registration by selecting a target ball target and adopting not less than 3 homonymous points, wherein the accuracy of the homonymous points after registration is not lower than the error in the characteristic point interval required by the specification;
converting coordinate systems of the point cloud data after registration, converting coordinate systems of a plurality of scanners into a unified coordinate system through the coordinate system conversion, specifically, converting the coordinate systems through a seven-parameter model by adopting at least 3 uniformly distributed homonymous points, preferably fixing a scale factor during conversion, and enabling a conversion residual to be smaller than 1/2 of an error of a point location allowed by a specification relative to an adjacent control point;
the point cloud data after conversion is subjected to point cloud classification, so that the point cloud data can be conveniently separated and a surface model can be conveniently constructed in the later stage, and the method specifically comprises the following steps: dividing the point cloud data into different categories according to the electromagnetic wave reflection intensity information characteristics of different target objects, and classifying and labeling the point cloud data according to the different categories;
the classified point cloud data is divided and rarefied so as to be beneficial to carrying out three-dimensional curved surface reconstruction on huge point cloud data, and the method specifically comprises the following steps: the detailed characteristics of the point cloud data model are fully considered, a non-uniform grid method is adopted for the point cloud data model, the detailed characteristics are kept not to be deleted, and the maximum point distance after the point cloud data is diluted meets the minimum distance requirement of the calculation volume;
and step 3, comprising:
a point processing stage: removing isolated points, non-connection points and noise points in vitro; sampling the removed point cloud data so as to keep the accuracy of the space model;
and (3) a finite element processing stage: packaging the point cloud data into a polygonal model, and editing the polygonal model; dividing the edited polygonal model into a limited number of virtual small cubic elements with equal shape and size;
in the step 4, point cloud data model calculation is to use an integral principle, firstly fit out the small cubic element external curved surface, calculate a normal vector of the curved surface according to known point cloud data on the curved surface, and then use a cylindrical surface integral principle to calculate the volume of a space model;
the specific calculation steps include:
calculating the maximum X in the X-axis direction of a space rectangular coordinate system according to a point cloud space data modelmaxAnd minimum value XminMaximum value Y in Y-axis directionmaxAnd minimum value Ymin；
Establishing a spatial rectangular coordinate system according to a single small cubic elementO-XYZThe X ' axis, the Y ' axis and the Z ' axis are respectively parallel to the X axis, the Y axis and the Z axis;
based on the number of the inner points of a single small cubic unit, judging the fitting method suitable for the inner points and fitting the curved surfaces one by one, and setting the normal vector of a certain point as
Calculating the normal vector
The minimum value of the included angle delta between the X axis, the Y axis, the Z axis and the respective opposite directions, the plane vertical to the corresponding coordinate axis at this time is used as the starting surface of the integral, and the corresponding normal vector direction is used as the integral direction;
and carrying out double integration on the area under the inner curved surface of the small cubic element to obtain the volume of the measured workpiece.
2. The method of measuring the dimensions of irregularities in a metrology workpiece of claim 1,
step 1, scanning a designated profile or area of a workpiece by the multi-joint three-dimensional laser scanner by using an optical measuring probe or a non-contact measuring probe.
3. The method of measuring the dimensions of irregularities in a metrology workpiece of claim 2,
step 1, before scanning operation, determining the layout position of controllable points and reasonably arranging a scanning and measuring station route, wherein the controllable points can control the whole measuring area and are uniformly distributed, and the multi-joint three-dimensional laser scanner scans according to the scanning and measuring station route to ensure that adjacent measuring stations have a certain proportion of overlapping degree.
4. A measuring apparatus for measuring the size of irregularities on a workpiece based on the measuring method according to any one of claims 1 to 3, comprising:
the scanning device is three or more multi-joint three-dimensional laser scanners;
one or more processors;
storage means for storing one or more programs;
when three or more of the multi-jointed three-dimensional laser scanners acquire point cloud data of a workpiece, the one or more programs are executed by one or more processors, so that the one or more processors implement the measurement method according to any one of claims 1 to 3.
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