CN114018155B - Method and system for detecting precision of chemical milling laser engraving profile - Google Patents

Method and system for detecting precision of chemical milling laser engraving profile Download PDF

Info

Publication number
CN114018155B
CN114018155B CN202111392053.9A CN202111392053A CN114018155B CN 114018155 B CN114018155 B CN 114018155B CN 202111392053 A CN202111392053 A CN 202111392053A CN 114018155 B CN114018155 B CN 114018155B
Authority
CN
China
Prior art keywords
point
data
actual
matching
module
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.)
Active
Application number
CN202111392053.9A
Other languages
Chinese (zh)
Other versions
CN114018155A (en
Inventor
毕庆贞
徐劲虎
唐新宇
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.)
Shanghai Jiaotong University
Original Assignee
Shanghai Jiaotong University
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 Shanghai Jiaotong University filed Critical Shanghai Jiaotong University
Priority to CN202111392053.9A priority Critical patent/CN114018155B/en
Publication of CN114018155A publication Critical patent/CN114018155A/en
Application granted granted Critical
Publication of CN114018155B publication Critical patent/CN114018155B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/24Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30Computing systems specially adapted for manufacturing

Abstract

The invention provides a method and a system for detecting the precision of a chemical milling laser engraving profile, which comprises the steps of importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving profile precision detection software; scanning all engraving lines on the part by line laser and importing data into laser engraving profile precision detection software; determining the pose relationship between the line laser and the part through the coordinate transformation of the five-axis machine tool, solving the coordinate of the position x of each frame of the notch groove in a workpiece coordinate system, and storing the coordinate as actual contour line point cloud data; matching the theoretical point cloud and the actual point cloud, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form; and calculating the contour precision evaluation indexes including centroid offset, the average value of the matching point errors, standard deviation and the maximum value. The method has the advantages of high efficiency, high precision and complete evaluation index, and greatly reduces the production cost and the cycle of chemical milling.

Description

Method and system for detecting precision of chemical milling laser engraving profile
Technical Field
The invention relates to the technical field of chemical milling, in particular to a method and a system for detecting the precision of a laser engraving profile of chemical milling.
Background
The large thin-wall parts in the aircraft structural parts have the characteristics of large diameter-thickness ratio and difficult processing, the milling of lightening grooves on the thin-wall parts becomes a difficult point in the processing process, and at present, aircraft manufacturers in China mostly adopt a chemical milling mode for processing. Firstly, coating a layer of glue on the surface of a part, determining a region needing chemical milling in a carving mode, and then immersing a workpiece into a chemical milling pool to carry out chemical corrosion on the region without the glue film.
The profile accuracy of the laser engraving line is an important evaluation standard for high and low quality of the chemically milled engraving line, and directly determines the profile accuracy of the final weight-reducing groove after chemically milling. The traditional manual engraving has the problems of poor profile precision and low efficiency, in recent years, laser engraving machines are gradually developed, patterns or shapes needing to be milled can be engraved on coatings with glue, with the continuous development of laser engraving technologies, how to evaluate the laser engraving profile precision becomes a problem to be solved, and a method capable of detecting the laser engraving profile precision is lacked in the prior art.
Patent document No. CN109483887a discloses an online detection method for the profile accuracy of a formed layer in a selective laser melting process. The online detection method comprises the following steps: s1, slicing a model of a part to be machined, and generating an auxiliary image; s2, powder paving is carried out, and then the powder is selectively melted and formed by laser; s3, acquiring an image of a basically formed area, and extracting the outline of the segmented image; s4, carrying out three-dimensional reconstruction on the image contour to obtain an actual image contour; s5, comparing the actual contour Cr of the image with the contour of the corresponding sliced layer, analyzing the precision, if the requirement is met, entering the step S6, and if the requirement is not met, finishing the processing; s6, detecting whether the part to be processed is processed.
At present, few detection methods for the precision of the chemical milling laser engraving profile are provided, such as Zhang Liyan and the like, an on-machine vision detection method for chemical milling film engraving is provided, and the precision of the chemical milling film engraving on a part to be detected can be detected by combining machine vision detection and a numerical control engraving process. The method can obtain the actual glue film engraving curve but does not obtain the groove width and the groove depth information of the engraving line and does not quantitatively evaluate the direct error of the theoretical engraving line and the actual engraving line. Therefore, a technical solution is needed to improve the above technical problems.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method and a system for detecting the precision of a chemical milling laser engraving profile.
According to the invention, the method for detecting the precision of the chemically-milled laser-engraved profile comprises the following steps:
step S1: importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving contour precision detection software;
step S2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position;
and step S3: controlling the machine tool to move along the laser engraving type track, scanning all engraving lines on the part by line laser and importing data into laser engraving type profile precision detection software;
and step S4: reading scanning data in a single frame, storing a cutter shaft data part of each frame, and directly processing line laser data by adopting a section parameter fitting step;
step S5: determining the pose relationship of the line laser and the part through the coordinate transformation of the five-axis machine tool according to the coordinate relationship between the part and the machine tool and the coordinate relationship between the installation position of the line laser and the machine tool, solving the coordinate of the position x of each frame of the notch groove in a workpiece coordinate system, and storing the coordinate as actual contour line point cloud data;
step S6: adopting an Euclidean clustering method to segment theoretical and actual point cloud data, randomly selecting an initial point P, searching a nearest neighbor point by using KDTree, putting the nearest neighbor point into a set { Qi } if the distance is less than a set threshold value, finishing primary clustering if elements in the set { Qi } are not increased any more, setting a new set { Qi +1}, and otherwise updating the initial point P to continue searching;
step S7: matching the theoretical point cloud and the actual point cloud according to the nearest point matching step, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form;
step S8: performing contour precision evaluation on the matched point cloud pair, wherein the contour precision evaluation is divided into an overall error and a local error, the overall error mainly comprises two types of expansion and deviation, and the local error mainly is an error of an actual reticle near a theoretical contour;
step S9: and calculating the contour precision evaluation indexes including centroid offset, the average value of the matching point errors, standard deviation and the maximum value.
Preferably, in the step S4, the step of fitting the section parameters fits the section of the notch groove by constructing a continuous function, and the parameters of the fitting are the groove width w, the groove depth d and the notch groove position x 0 And solving parameters to be determined by using a nonlinear least square fitting method based on Gauss-Newton iteration.
Preferably, the contour accuracy evaluation process in step S8 includes first calculating centroid positions of the theoretical point cloud and the actual point cloud, compensating a centroid offset, and performing closest point matching on the compensated point pair.
Preferably, the step of fitting the section parameters in step S4 includes the steps of:
step S4.1: the program pointer points to the head of the linear laser scanning data set, data of the groove part is eliminated through linear fitting, the remaining surface segment data are subjected to linear fitting, and the fitted linear is rotated to the horizontal plane to obtain actual surface data;
step S4.2: fitting actual surface data, and constructing by using a hyperbolic tangent function, wherein typically, the following functions are constructed:
Figure BDA0003364847190000031
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i The vertical coordinate of the ith data point of the line laser is represented;
step S4.3: solving the groove width w, the groove depth d and the notch groove position x of the parameters to be determined by applying a nonlinear least square fitting method based on Gauss-Newton iteration 0 The optimization objectives are as follows:
Figure BDA0003364847190000032
Figure BDA0003364847190000033
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i Represents the i-th data point ordinate, f (x) of the line laser i ) The deviation of the ith data point is represented, F represents a function to be optimized, and N represents the number of line laser data;
step S4.4: and restoring the actual surface data according to the rotation transformation relation, and programming a pointer +1.
Preferably, the closest point matching step in step S7 includes the steps of:
step S7.1: the program pointer points to the head of the point cloud pair, the theoretical outline centroid and the actual outline centroid are respectively calculated, and the actual carved line point cloud is compensated according to the deviation value of the theoretical outline centroid and the actual outline centroid;
step S7.2: generating a compensated actual engraving line point set { Pi }, and a theoretical engraving line point set { Ti };
step S7.3: inquiring the closest point from the actual engraving type line point set { Pi } to the theoretical engraving type line point set { Ti } and recording the point pair matching relationship, and inquiring the closest point from the theoretical engraving type line point set { Ti } to the actual engraving type line point set { Pi } and recording the point pair matching relationship;
step S7.4: judging the point pair matching relationship: if the matching relationship of the two point pairs is the same, the two points are matching points, and the distance between the two points is a contour error; if the matching relations of the two types of point pairs are different, the two types of matching relations are corrected, and the point pair with the larger distance is selected as the correct point pair.
The invention also provides a system for detecting the precision of the chemically milled laser engraving profile, which comprises the following modules:
a module M1: importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving contour precision detection software;
a module M2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position;
a module M3: controlling the machine tool to move along the laser engraving type track, scanning all engraving lines on the part by line laser and importing data into laser engraving type profile precision detection software;
a module M4: reading scanning data in a single frame, storing a cutter shaft data part of each frame, and directly processing line laser data by adopting a section parameter fitting module;
a module M5: determining the pose relationship of the line laser and the part through the coordinate transformation of the five-axis machine tool according to the coordinate relationship between the part and the machine tool and the coordinate relationship between the installation position of the line laser and the machine tool, solving the coordinate of the position x of each frame of the notch groove in a workpiece coordinate system, and storing the coordinate as actual contour line point cloud data;
a module M6: adopting an Euclidean clustering system to segment theoretical and actual point cloud data, randomly selecting an initial point P, searching a nearest neighbor point by using KDTree, putting the nearest neighbor point into a set { Qi } if the distance is less than a set threshold value, finishing primary clustering if elements in the set { Qi } are not increased any more, setting a new set { Qi +1}, and otherwise, updating the initial point P to continue searching;
a module M7: matching the theoretical point cloud and the actual point cloud according to a nearest point matching module, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form;
a module M8: performing contour precision evaluation on the matched point cloud pair, wherein the contour precision evaluation is divided into an overall error and a local error, the overall error mainly comprises two types of expansion and deviation, and the local error mainly is an error of an actual reticle near a theoretical contour;
a module M9: and calculating the contour precision evaluation indexes including centroid offset, the average value of the matching point errors, standard deviation and the maximum value.
Preferably, the section parameter fitting module in the module M4 fits the section of the notch groove by constructing a continuous function, and the fitting parameters are the groove width w, the groove depth d and the notch groove position x 0 And solving parameters to be determined by using a system based on nonlinear least square fitting of Gaussian Newton iteration.
Preferably, the contour accuracy evaluation process in the module M8 is to calculate centroid positions of the theoretical point cloud and the actual point cloud, compensate centroid offsets, and perform closest point matching on compensated point pairs.
Preferably, the section parameter fitting module in the module M4 includes the following modules:
module M4.1: the program pointer points to the head of the linear laser scanning data set, data of the groove part is eliminated through linear fitting, the remaining surface segment data are subjected to linear fitting, and the fitted linear is rotated to the horizontal plane to obtain actual surface data;
module M4.2: fitting actual surface data, and constructing by using a hyperbolic tangent function, wherein typically, the following functions are constructed:
Figure BDA0003364847190000051
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i The vertical coordinate of the ith data point of the line laser is represented;
module M4.3: solving the parameters to be determined, namely the groove width w, the groove depth d and the notch groove position x by using a nonlinear least square fitting system based on Gauss-Newton iteration 0 The optimization objectives are as follows:
Figure BDA0003364847190000052
Figure BDA0003364847190000053
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i Represents the i-th data point ordinate, f (x) of the line laser i ) The deviation of the ith data point is represented, F represents a function to be optimized, and N represents the number of line laser data;
module M4.4: and restoring the actual surface data according to the rotation transformation relation, and programming a pointer +1.
Preferably, the closest point matching module in the module M7 includes the following modules:
module M7.1: the program pointer points to the head of the point cloud pair, the theoretical outline centroid and the actual outline centroid are respectively calculated, and the actual carved line point cloud is compensated according to the deviation value of the theoretical outline centroid and the actual outline centroid;
module M7.2: generating a compensated actual engraving line point set { Pi }, and a theoretical engraving line point set { Ti };
module M7.3: inquiring the closest point from the actual engraving type line point set { Pi } to the theoretical engraving type line point set { Ti } and recording the point pair matching relationship, and inquiring the closest point from the theoretical engraving type line point set { Ti } to the actual engraving type line point set { Pi } and recording the point pair matching relationship;
module M7.4: judging the point pair matching relationship: if the matching relationship of the two point pairs is the same, the two points are matching points, and the distance between the two points is a contour error; if the matching relations of the two types of point pairs are different, the two types of matching relations are corrected, and the point pair with the larger distance is selected as the correct point pair.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention combines line laser scanning and a laser engraving machine, controls line laser to scan the surface characteristics of the part through a machine tool, and can quickly acquire the point cloud data of the engraved line on the surface of the part;
2. the method comprises the steps of obtaining actual point cloud of a scale line through single-frame section parameter fitting and coordinate transformation, and comparing and analyzing the actual point cloud with theoretical point cloud so as to quantitatively evaluate the contour accuracy of the scale line;
3. compared with the traditional method of manually engraving and manually comparing templates, the method for detecting the engraving profile precision of the chemical milling laser can evaluate the engraving profile precision more objectively and efficiently, and gives specific evaluation index results such as groove width, groove depth, errors and the like;
4. the method has the advantages of high efficiency, high precision and perfect evaluation index, and greatly improves the production cost and the cycle of chemical milling.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a flow chart of the detection steps of the present invention;
FIG. 2 is a flow chart of the cross-sectional parameter fitting step of the present invention;
FIG. 3 is a flowchart of the closest point matching procedure of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
The invention provides a method and a system for detecting profile precision of chemical milling laser engraving, which are used for detecting the profile precision of a chemical milling laser engraving type line based on a line laser and detecting the groove width and the groove depth of the engraving type line and the deviation of the engraving type line from a theoretical engraving type line.
The technical scheme includes that the surface of a part is scanned through a line laser, frame-by-frame processing is conducted on obtained data to obtain groove width, groove depth and position information of an engraving line, point clouds of actual engraving lines are obtained according to coordinate transformation and are segmented, and finally contour matching is conducted on theoretical point clouds and actual point clouds to obtain contour precision evaluation indexes; the method comprises a detection step, a section parameter fitting step and a closest point matching step; the detection step comprises the following steps:
step S1: importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving contour precision detection software; step S2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position; and step S3: controlling the machine tool to move along the laser engraving type track, scanning all engraving lines on the part by line laser and importing data into laser engraving type profile precision detection software; and step S4: reading scanning data in a single frame, storing a cutter shaft data part of each frame, and directly processing line laser data by adopting a section parameter fitting method; step S5: the section parameter fitting method is used for fitting the section of the notch groove by constructing a continuous function, and the fitting parameters are the groove width w, the groove depth d and the notch groove position x 0 Applying a non-linear least square fitting method based on Gauss-Newton iterationParameters to be determined can be solved; step S6: determining the pose relationship of the line laser and the part through the coordinate transformation of the five-axis machine tool according to the coordinate relationship between the part and the machine tool and the coordinate relationship between the installation position of the line laser and the machine tool, so as to solve the coordinate of the position x of each frame of the notch groove in a workpiece coordinate system, wherein the coordinate is stored as actual contour line point cloud data; step S7: segmenting theoretical and actual point cloud data by adopting an Euclidean clustering method, randomly selecting an initial point P, searching a nearest neighbor point by using KDTree, putting the nearest neighbor point into a set { Qi } if the distance is less than a set threshold value, finishing primary clustering if elements in the set { Qi } are not increased any more, setting a new set { Qi +1}, and otherwise, updating the initial point P and continuing searching; step S8: matching the theoretical point cloud and the actual point cloud, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form; step S9: performing contour precision evaluation on the matched point cloud pair, wherein the contour precision evaluation is divided into an overall error and a local error, the overall error mainly comprises two types of expansion and deviation, and the local error mainly is an error of an actual reticle near a theoretical contour; step S10: the outline precision evaluation process comprises the steps of firstly calculating the centroid positions of theoretical point cloud and actual point cloud, compensating the centroid offset, and performing closest point matching on compensated point pairs; step S11: calculating an outline precision evaluation index, comprising: centroid shift, mean, standard deviation, maximum of match point error.
The step of fitting the section parameters comprises the following steps:
step 1: the program pointer points to the head of the linear laser scanning data set, data of the groove part is eliminated through linear fitting, the remaining surface segment data are subjected to linear fitting, and the fitted linear is rotated to the horizontal plane to obtain actual surface data; step 2: fitting actual surface data, and constructing by using a hyperbolic tangent function, wherein typically, the following functions are constructed:
Figure BDA0003364847190000071
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i The vertical coordinate of the ith data point of the line laser is represented;
and step 3: the parameters to be determined, namely the groove width w, the groove depth d and the notch groove position x, can be obtained by applying a nonlinear least square fitting method based on Gauss-Newton iteration 0 . The optimization objectives are as follows:
Figure BDA0003364847190000072
Figure BDA0003364847190000073
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i Represents the i-th data point ordinate, f (x) of the line laser i ) The deviation of the ith data point is represented, F represents a function to be optimized, and N represents the number of line laser data;
and 4, step 4: and restoring the actual surface data according to the rotation transformation relation, and programming a pointer +1.
The closest point matching step comprises the following steps:
step a: the program pointer points to the head of the point cloud pair, the theoretical outline centroid and the actual outline centroid are respectively calculated, and the actual carved line point cloud is compensated according to the deviation value of the theoretical outline centroid and the actual outline centroid; step b: generating a compensated actual engraving line point set { Pi }, and a theoretical engraving line point set { Ti }; step c: inquiring the closest point from the actual engraving line point set { Pi } to the theoretical engraving line point set { Ti } and recording the point pair matching relation, and inquiring the closest point from the theoretical engraving line point set { Ti } to the actual engraving line point set { Pi } and recording the point pair matching relation; step d: judging the point pair matching relationship: if the matching relationship of the two point pairs is the same, the two points are matching points, and the distance between the two points is a contour error; if the matching relations of the two types of point pairs are different, the two types of matching relations are corrected, and the point pair with the larger distance is selected as the correct point pair.
The invention also provides a system for detecting the precision of the chemically milled laser engraving profile, which comprises the following modules: a module M1: importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving contour precision detection software; a module M2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position; a module M3: and controlling the machine tool to move along the laser engraving type track, scanning all engraving lines on the part by line laser and introducing data into laser engraving type profile precision detection software.
A module M4: reading scanning data in a single frame, storing a cutter shaft data part of each frame, and directly processing line laser data by adopting a section parameter fitting module; the section parameter fitting module fits the section of the notch groove by constructing a continuous function, and the fitting parameters are the groove width w, the groove depth d and the notch groove position x 0 And solving parameters to be determined by using a system based on Gaussian Newton iteration nonlinear least square fitting. Module M4.1: the program pointer points to the head of the linear laser scanning data set, data of the groove part is eliminated through linear fitting, the remaining surface segment data are subjected to linear fitting, and the fitted linear is rotated to the horizontal plane to obtain actual surface data; module M4.2: fitting actual surface data, and constructing by using a hyperbolic tangent function, wherein typically, the following functions are constructed:
Figure BDA0003364847190000081
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the position of the groove, x i Represents the i-th data point abscissa, z of the line laser i The vertical coordinate of the ith data point of the line laser is represented;
module M4.3: the method comprises the following steps of solving parameters to be determined, namely groove width w, groove depth d and notch groove position x0 by using a nonlinear least square fitting system based on Gauss-Newton iteration, wherein the optimization target is as follows:
Figure BDA0003364847190000091
Figure BDA0003364847190000092
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i Represents the i-th data point ordinate, f (x) of the line laser i ) The deviation of the ith data point is represented, F represents a function to be optimized, and N represents the number of line laser data;
module M4.4: and restoring the actual surface data according to the rotation transformation relation, and programming a pointer +1.
A module M5: determining the pose relationship of the line laser and the part through the coordinate transformation of a five-axis machine tool according to the coordinate relationship between the part and the machine tool and the coordinate relationship between the installation position of the line laser and the machine tool, solving the coordinate of the position x of each frame of the notch groove in a workpiece coordinate system, and storing the coordinate as actual contour line point cloud data; a module M6: adopting an Euclidean clustering system to segment theoretical and actual point cloud data, randomly selecting an initial point P, searching a nearest neighbor point by using KDTree, putting the nearest neighbor point into a set { Qi } if the distance is less than a set threshold value, finishing primary clustering if elements in the set { Qi } are not increased any more, setting a new set { Qi +1}, and otherwise, updating the initial point P to continue searching;
a module M7: matching the theoretical point cloud and the actual point cloud according to a nearest point matching module, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form; module M7.1: the program pointer points to the head of the point cloud pair, the theoretical outline centroid and the actual outline centroid are respectively calculated, and the actual carved line point cloud is compensated according to the deviation value of the theoretical outline centroid and the actual outline centroid; module M7.2: generating a compensated actual engraving line point set { Pi }, and a theoretical engraving line point set { Ti }; module M7.3: inquiring the closest point from the actual engraving line point set { Pi } to the theoretical engraving line point set { Ti } and recording the point pair matching relation, and inquiring the closest point from the theoretical engraving line point set { Ti } to the actual engraving line point set { Pi } and recording the point pair matching relation; module M7.4: judging the point pair matching relationship: if the matching relationship of the two point pairs is the same, the two points are matching points, and the distance between the two points is a contour error; if the matching relations of the two types of point pairs are different, the two types of matching relations are corrected, and the point pair with the larger distance is selected as the correct point pair.
A module M8: carrying out contour accuracy evaluation on the well matched point cloud pair, wherein the contour accuracy evaluation is divided into an overall error and a local error, the overall error mainly comprises two types of expansion and deviation, and the local error mainly comprises an error of an actual reticle near a theoretical contour; preferably, the contour accuracy evaluation process includes the steps of firstly calculating centroid positions of the theoretical point cloud and the actual point cloud, compensating centroid offset, and performing closest point matching on compensated point pairs.
A module M9: and calculating the profile precision evaluation indexes including centroid offset, the average value of the errors of the matching points, standard deviation, the minimum value and the maximum value.
The invention combines line laser scanning and a laser engraving machine, controls line laser to scan the surface characteristics of the part through a machine tool, and can quickly acquire engraving line point cloud data on the surface of the part; obtaining actual point cloud of the scale line through single-frame section parameter fitting and coordinate transformation, and comparing and analyzing the actual point cloud with theoretical point cloud so as to quantitatively evaluate the profile accuracy of the scale line; compared with the traditional method of manually engraving and manually comparing templates, the method for detecting the engraving profile precision of the chemical milling laser can evaluate the engraving profile precision more objectively and efficiently, and gives specific evaluation index results such as groove width, groove depth, errors and the like; the method has the advantages of high efficiency, high precision and complete evaluation index, and greatly improves the production cost and the cycle of chemical milling.
Those skilled in the art will appreciate that, in addition to implementing the system and its various devices, modules, units provided by the present invention as pure computer readable program code, the system and its various devices, modules, units provided by the present invention can be fully implemented by logically programming method steps in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units included in the system for realizing various functions can also be regarded as structures in the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.
The foregoing description has described specific embodiments of the present invention. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.

Claims (2)

1. A method for detecting the precision of a chemical milling laser engraving profile is characterized by comprising the following steps:
step S1: importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving contour precision detection software;
step S2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position;
and step S3: controlling the machine tool to move along the laser engraving type track, scanning all engraving lines on the part by line laser and importing data into laser engraving type profile precision detection software;
and step S4: reading the scanning data in a single frame, storing a cutter shaft data part of each frame, and directly processing line laser data by adopting a section parameter fitting step;
step S5: determining the line laser and the part through the coordinate transformation of the five-axis machine tool according to the coordinate relation between the part and the machine tool and the coordinate relation between the installation position of the line laser and the machine toolThe position and the attitude relation of each frame are solved to obtain the position x of the notch groove of each frame 0 Coordinates under a workpiece coordinate system are stored as actual contour line point cloud data;
step S6: segmenting theoretical and actual point cloud data by adopting an Euclidean clustering method, randomly selecting an initial point P, searching a nearest neighbor point by using KDTree, putting the nearest neighbor point into a set { Qi } if the distance is less than a set threshold value, finishing primary clustering if elements in the set { Qi } are not increased any more, setting a new set { Qi +1}, and otherwise, updating the initial point P and continuing searching;
step S7: matching the theoretical point cloud and the actual point cloud according to the nearest point matching step, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form;
step S8: performing contour precision evaluation on the matched point cloud pair, wherein the contour precision evaluation is divided into an overall error and a local error, the overall error mainly comprises two types of expansion and deviation, and the local error mainly is an error of an actual reticle near a theoretical contour;
step S9: calculating contour precision evaluation indexes including centroid offset, average value, standard deviation and maximum value of matching point errors;
the contour accuracy evaluation process in the step S8 comprises the steps of firstly calculating centroid positions of theoretical point cloud and actual point cloud, compensating centroid offset, and carrying out closest point matching on compensated point pairs;
the closest point matching step in step S7 includes the steps of:
step S7.1: the program pointer points to the head of the point cloud pair, the theoretical outline centroid and the actual outline centroid are respectively calculated, and the actual carved line point cloud is compensated according to the deviation value of the theoretical outline centroid and the actual outline centroid;
step S7.2: generating a compensated actual engraving line point set { Pi }, and a theoretical engraving line point set { Ti };
step S7.3: inquiring the closest point from the actual engraving line point set { Pi } to the theoretical engraving line point set { Ti } and recording the point pair matching relation, and inquiring the closest point from the theoretical engraving line point set { Ti } to the actual engraving line point set { Pi } and recording the point pair matching relation;
step S7.4: judging the point pair matching relationship: if the matching relationship of the two point pairs is the same, the two points are matching points, and the distance between the two points is a contour error; if the matching relations of the two point pairs are different, correcting the two matching relations, and selecting the point pair with the larger distance as a correct point pair;
in the section parameter fitting step in the step S4, the section of the notch groove is fitted by constructing a continuous function, and the fitting parameters are the groove width w, the groove depth d and the notch groove position x 0 Solving parameters to be determined by applying a nonlinear least square fitting method based on Gauss-Newton iteration;
the step of fitting the section parameters in the step S4 includes the steps of:
step S4.1: the program pointer points to the head of the linear laser scanning data set, data of the groove part is eliminated through linear fitting, the remaining surface segment data are subjected to linear fitting, and the fitted linear is rotated to the horizontal plane to obtain actual surface data;
step S4.2: fitting actual surface data, constructing by adopting a hyperbolic tangent function, and constructing the following function:
Figure FDA0003929918120000021
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i The vertical coordinate of the ith data point of the line laser is represented;
step S4.3: solving the groove width w, the groove depth d and the notch groove position x of the parameters to be determined by applying a nonlinear least square fitting method based on Gauss-Newton iteration 0 The optimization objectives are as follows:
Figure FDA0003929918120000022
Figure FDA0003929918120000023
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the position of the groove, x i Represents the i-th data point abscissa, z of the line laser i Represents the i-th data point ordinate, f (x) of the line laser i ) The deviation of the ith data point is represented, F represents a function to be optimized, and N represents the number of line laser data;
step S4.4: and restoring the actual surface data according to the rotation transformation relation, and programming a pointer +1.
2. A chemical milling laser engraving type profile precision detection system is characterized by comprising the following modules:
a module M1: importing a three-dimensional model of a part to be detected and theoretical contour line point cloud data into laser engraving contour precision detection software;
a module M2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position;
a module M3: controlling the machine tool to move along the laser engraving type track, scanning all engraving lines on the part by line laser and importing data into laser engraving type profile precision detection software;
a module M4: reading scanning data in a single frame, storing a cutter shaft data part of each frame, and directly processing line laser data by adopting a section parameter fitting module;
a module M5: determining the pose relationship of the line laser and the part through the coordinate transformation of the five-axis machine tool according to the coordinate relationship between the part and the machine tool and the coordinate relationship between the installation position of the line laser and the machine tool, and solving the position x of each frame of the notch groove 0 Coordinates under a workpiece coordinate system are stored as actual contour line point cloud data;
a module M6: adopting an Euclidean clustering system to segment theoretical and actual point cloud data, randomly selecting an initial point P, searching a nearest neighbor point by using KDTree, putting the nearest neighbor point into a set { Qi } if the distance is less than a set threshold value, finishing primary clustering if elements in the set { Qi } are not increased any more, setting a new set { Qi +1}, and otherwise, updating the initial point P to continue searching;
a module M7: matching the theoretical point cloud and the actual point cloud according to a nearest point matching module, calculating the centroid position of each point cloud set, determining a matching relation by applying KDTree neighbor search, and storing the matching relation in a point cloud pair form;
a module M8: carrying out contour accuracy evaluation on the well matched point cloud pair, wherein the contour accuracy evaluation is divided into an overall error and a local error, the overall error mainly comprises two types of expansion and deviation, and the local error mainly comprises an error of an actual reticle near a theoretical contour;
a module M9: calculating contour precision evaluation indexes including centroid offset, average value, standard deviation and maximum value of matching point errors;
the contour accuracy evaluation process in the module M8 comprises the steps of firstly calculating centroid positions of theoretical point cloud and actual point cloud, compensating centroid offset, and carrying out closest point matching on compensated point pairs;
the closest point matching module in the module M7 includes the following modules:
module M7.1: the program pointer points to the head of the point cloud pair, the theoretical outline centroid and the actual outline centroid are respectively calculated, and the actual carved line point cloud is compensated according to the deviation value of the theoretical outline centroid and the actual outline centroid;
module M7.2: generating a compensated actual engraving line point set { Pi }, and a theoretical engraving line point set { Ti };
module M7.3: inquiring the closest point from the actual engraving line point set { Pi } to the theoretical engraving line point set { Ti } and recording the point pair matching relation, and inquiring the closest point from the theoretical engraving line point set { Ti } to the actual engraving line point set { Pi } and recording the point pair matching relation;
module M7.4: judging the point pair matching relationship: if the matching relationship of the two point pairs is the same, the two points are matching points, and the distance between the two points is a contour error; if the matching relations of the two point pairs are different, correcting the two matching relations, and selecting the point pair with the larger distance as a correct point pair;
the section parameter fitting module in the module M4 is connected through constructionFitting the section of the notch groove by a continuous function, wherein the parameters of the fitting are the groove width w, the groove depth d and the notch groove position x 0 Solving parameters to be determined by using a nonlinear least square fitting system based on Gauss-Newton iteration;
the section parameter fitting module in the module M4 includes the following modules:
module M4.1: the program pointer points to the head of the linear laser scanning data set, data of the groove part is eliminated through linear fitting, the remaining surface segment data are subjected to linear fitting, and the fitted linear is rotated to the horizontal plane to obtain actual surface data;
module M4.2: fitting actual surface data, constructing by adopting a hyperbolic tangent function, and constructing the following function:
Figure FDA0003929918120000041
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i The vertical coordinate of the ith data point of the line laser is represented;
module M4.3: solving the parameters to be determined, namely the groove width w, the groove depth d and the notch groove position x by using a nonlinear least square fitting system based on Gauss-Newton iteration 0 The optimization objectives are as follows:
Figure FDA0003929918120000042
Figure FDA0003929918120000043
wherein tanh represents a hyperbolic tangent function, z 0 Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x 0 Indicating the location of the notch, x i Represents the i-th data point abscissa, z of the line laser i Represents the i-th data point ordinate of the line laser, f (x) i ) The deviation of the ith data point is represented, F represents a function to be optimized, and N represents the number of line laser data;
module M4.4: and restoring the actual surface data according to the rotation transformation relation, and programming a pointer +1.
CN202111392053.9A 2021-11-19 2021-11-19 Method and system for detecting precision of chemical milling laser engraving profile Active CN114018155B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111392053.9A CN114018155B (en) 2021-11-19 2021-11-19 Method and system for detecting precision of chemical milling laser engraving profile

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111392053.9A CN114018155B (en) 2021-11-19 2021-11-19 Method and system for detecting precision of chemical milling laser engraving profile

Publications (2)

Publication Number Publication Date
CN114018155A CN114018155A (en) 2022-02-08
CN114018155B true CN114018155B (en) 2023-02-17

Family

ID=80065761

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111392053.9A Active CN114018155B (en) 2021-11-19 2021-11-19 Method and system for detecting precision of chemical milling laser engraving profile

Country Status (1)

Country Link
CN (1) CN114018155B (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114689030A (en) * 2022-06-01 2022-07-01 中国兵器装备集团自动化研究所有限公司 Unmanned aerial vehicle auxiliary positioning method and system based on airborne vision
CN115846886B (en) * 2023-02-02 2023-05-16 中航西安飞机工业集团股份有限公司 Aircraft skin chemical milling accurate engraving method
CN117289651B (en) * 2023-11-24 2024-04-16 南通汤姆瑞斯工业智能科技有限公司 Numerical control machining method and control system for die manufacturing

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102706307A (en) * 2012-05-16 2012-10-03 中国商用飞机有限责任公司 Method for detecting actual scribed line of molded mould
TWM498647U (en) * 2013-12-18 2015-04-11 Univ St Johns Monitor and inspection integrated milling complex process machine
CN106841206A (en) * 2016-12-19 2017-06-13 大连理工大学 Untouched online inspection method is cut in heavy parts chemical milling
CN107133565A (en) * 2017-03-31 2017-09-05 大连理工大学 Laser incising molded line feature extracting method based on line laser
CN108907897A (en) * 2018-03-28 2018-11-30 南京航空航天大学 Milling glue film carve shape in machine visible detection method
CN112683191A (en) * 2020-11-30 2021-04-20 深圳市道通科技股份有限公司 Method and device for measuring depth of sipe based on line laser and computing equipment
CN112797918A (en) * 2021-01-29 2021-05-14 广东省特种设备检测研究院珠海检测院 Three-dimensional size detection device of elevator driving sheave race

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11370013B2 (en) * 2017-12-19 2022-06-28 Standex International Corporation Method for spin forming lipskins

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102706307A (en) * 2012-05-16 2012-10-03 中国商用飞机有限责任公司 Method for detecting actual scribed line of molded mould
TWM498647U (en) * 2013-12-18 2015-04-11 Univ St Johns Monitor and inspection integrated milling complex process machine
CN106841206A (en) * 2016-12-19 2017-06-13 大连理工大学 Untouched online inspection method is cut in heavy parts chemical milling
CN107133565A (en) * 2017-03-31 2017-09-05 大连理工大学 Laser incising molded line feature extracting method based on line laser
CN108907897A (en) * 2018-03-28 2018-11-30 南京航空航天大学 Milling glue film carve shape in machine visible detection method
CN112683191A (en) * 2020-11-30 2021-04-20 深圳市道通科技股份有限公司 Method and device for measuring depth of sipe based on line laser and computing equipment
CN112797918A (en) * 2021-01-29 2021-05-14 广东省特种设备检测研究院珠海检测院 Three-dimensional size detection device of elevator driving sheave race

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
航空零件化铣胶膜激光刻线的视觉检测技术研究;童康康等;《电气与自动化》;20191231;全文 *

Also Published As

Publication number Publication date
CN114018155A (en) 2022-02-08

Similar Documents

Publication Publication Date Title
CN114018155B (en) Method and system for detecting precision of chemical milling laser engraving profile
CN110069041B (en) Workpiece machining method and system based on-machine measurement
Chiou Accurate tool position for five-axis ruled surface machining by swept envelope approach
CN103777570B (en) Mismachining tolerance quick detection compensation method based on nurbs surface
CN108544181B (en) Repair method for damaged blades of blisk
CN110103071B (en) Digital locating machining method for deformed complex part
ElMaraghy et al. Integrated inspection and machining for maximum conformance to design tolerances
CN110286650A (en) A kind of blank based on numerical control macroprogram is in machine fast aligning method
CN110837715B (en) Complex curved surface machining error compensation method based on reverse engineering technology
CN111820545A (en) Method for automatically generating sole glue spraying track by combining offline and online scanning
CN108594764B (en) Equal-residual-height tool contact point track generation method for triangular mesh model
CN111060881B (en) Millimeter wave radar external parameter online calibration method
CN114115123B (en) Parameterized numerical control machining method and system for aviation large thin-wall non-rigid part
CN115016394A (en) Flaw cutter point identification method based on flaw type
CN105700471A (en) Secondary correction method of aircraft skin numerical control machining program
CN108710341B (en) Rapid registration method based on simplified segmentation of massive scanning point clouds
CN111610751B (en) Interpolation error multi-subdivision iterative calculation method for cross point set NURBS interpolation curve
Barari et al. Evaluation of geometric deviations in sculptured surfaces using probability density estimation
CN115056213A (en) Robot track self-adaptive correction method for large complex component
CN112347585B (en) Analytical calculation method for contact area between ball end mill and workpiece
CN114549521A (en) Carbon tube array honeycomb surface shape precision calculation method based on G code processing guidance
CN108776459B (en) Process method for improving machining precision of five-axis numerical control machine tool
Li Application of CAD Technology in Extracting Line Feature of Industrial Part Image
KR102641382B1 (en) Form error compensation apparatus for machining using on-machine measurement and method threreof
CN115035519B (en) Intelligent tolerance dimension marking method for two-dimensional engineering drawing

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