CN114018155A - 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 PDFInfo
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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
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. The chemical milling method comprises the steps of firstly coating a layer of glue on the surface of a part, then 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 profile accuracy of a shaping layer in a selective laser melting process. The online detection method comprises the following steps: s1, slicing the model of the part to be processed and generating an auxiliary image; s2, spreading powder, and then selectively melting and forming the powder by laser; s3, collecting the image of the 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, otherwise, ending the processing; s6, detecting whether the part to be processed is processed.
At present, the on-machine vision detection method for chemical milling and laser engraving profile precision is less, and the on-machine vision detection method for chemical milling and adhesive film engraving is proposed by Zhayan and the like. 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;
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;
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: 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: 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 step in step S4 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 x0And solving parameters to be determined by applying a nonlinear least square fitting method based on Gauss-Newton iteration.
Preferably, the contour accuracy evaluation process in step S8 is to calculate centroid positions of the theoretical point cloud and the actual point cloud, compensate for centroid offsets, and perform closest point matching on the compensated point pairs.
Preferably, the section parameter fitting step 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:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriThe 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 iteration0The optimization objectives are as follows:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriRepresents the i-th data point ordinate, f (x) of the line laseri) 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 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 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:
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;
module M2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position;
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;
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;
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;
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;
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 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;
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 parameter is the groove widthw, groove depth d and notch position x0And 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 the centroid offset, and perform closest point matching on the compensated point pair.
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:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriThe 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 iteration0The optimization objectives are as follows:
wherein tanh represents a hyperbolic tangent function，z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriRepresents the i-th data point ordinate, f (x) of the line laseri) 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 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.
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 engraving line point cloud data 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 complete 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; 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; 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 x0The parameters to be determined can be solved by applying a nonlinear least square fitting method based on Gauss-Newton iteration; 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 centroid positions of theoretical point cloud and actual point cloud, compensating centroid offset, and performing closest point matching on compensated point pairs; step S11: calculating an outline precision evaluation index, comprising: the amount of the shift of the centroid,mean, standard deviation, maximum of match point errors.
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:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriThe 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 iteration0. The optimization objectives are as follows:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriRepresents the i-th data point ordinate, f (x) of the line laseri) 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: 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; module M2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position; 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.
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 x0And solving parameters to be determined by using a system based on nonlinear least square fitting of Gaussian Newton iteration. 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 is subjected to linear fitting, and the fitted linear is rotated to waterObtaining actual surface data by the plane; module M4.2: fitting actual surface data, and constructing by using a hyperbolic tangent function, wherein typically, the following functions are constructed:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriThe vertical coordinate of the ith data point of the line laser is represented;
module M4.3: and (3) solving parameters to be determined, namely the groove width w, the groove depth d and the notch groove position x0 by using a nonlinear least square fitting system based on Gauss-Newton iteration, wherein the optimization target is as follows:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriRepresents the i-th data point ordinate, f (x) of the line laseri) 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.
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; 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;
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.
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; 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.
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 of specific embodiments of the present invention has been presented. 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 (10)
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;
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;
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: 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: and calculating the contour precision evaluation indexes including centroid offset, the average value of the matching point errors, standard deviation and the maximum value.
2. The method for detecting the precision of a chemical milling laser-engraved profile according to claim 1, wherein the method comprisesCharacterized in that the section parameter fitting step in the step S4 is to fit 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 x0And solving parameters to be determined by applying a nonlinear least square fitting method based on Gauss-Newton iteration.
3. The method for detecting the precision of the laser-engraved profile of the chemical milling machine as claimed in claim 1, wherein the profile precision evaluation process in step S8 is to calculate the centroid positions of the theoretical point cloud and the actual point cloud, compensate the centroid offset, and perform the closest point matching on the compensated point pairs.
4. The method for detecting the precision of the chemical milling laser engraving profile of claim 1, wherein the step of fitting the section parameters in the step S4 comprises the following steps:
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:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriThe 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 iteration0The optimization objectives are as follows:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriRepresents the i-th data point ordinate, f (x) of the line laseri) 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.
5. The method for detecting the precision of the chemical milling laser engraving profile of claim 1, wherein the closest point matching step in the step S7 comprises the following steps:
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 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.
6. A chemical milling laser engraving type profile precision detection system is characterized by comprising the following modules:
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;
module M2: installing a line laser on a swinging head of a laser etching type machine, and calibrating the installation position;
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;
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;
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;
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;
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 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;
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.
7. The system for detecting the precision of the laser-engraved profile of the chemical milling machine as claimed in claim 6, wherein the section parameter fitting module in the module M4 fits the section of the engraved groove by constructing a continuous function, and the parameters of the fitting are the groove width w, the groove depth d and the position x of the engraved groove0And solving parameters to be determined by using a system based on nonlinear least square fitting of Gaussian Newton iteration.
8. The system for detecting the profile precision of the chemical milling laser engraving type according to claim 6, wherein the profile precision evaluation process in the module M8 is to firstly calculate the centroid positions of the theoretical point cloud and the actual point cloud, compensate the centroid offset, and perform the closest point matching on the compensated point pair.
9. The system for detecting the precision of the chemically milled laser engraved profile according to claim 6, wherein the section parameter fitting module in the module M4 comprises 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:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriIndicating the ith number of line laserAccording to the vertical coordinate of the point;
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 iteration0The optimization objectives are as follows:
wherein tanh represents a hyperbolic tangent function, z0Denotes the baseline ordinate, k denotes the similarity coefficient, w denotes the groove width, d denotes the groove depth, x0Indicating the location of the notch, xiRepresents the i-th data point abscissa, z of the line laseriRepresents the i-th data point ordinate, f (x) of the line laseri) 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.
10. The system for detecting the precision of the chemically milled laser engraved profile according to claim 6, wherein the closest point matching module in the module M7 comprises 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 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.
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Cited By (4)
| 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 |
| CN114782315A (en) * | 2022-03-17 | 2022-07-22 | 清华大学 | Method, device and equipment for detecting shaft hole assembly pose precision and storage medium |
| CN115846886A (en) * | 2023-02-02 | 2023-03-28 | 中航西安飞机工业集团股份有限公司 | Chemical milling accurate carving method for aircraft skin |
| CN117289651A (en) * | 2023-11-24 | 2023-12-26 | 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 (8)
| 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 |
| US20190184443A1 (en) * | 2017-12-19 | 2019-06-20 | Standex International Corporation | Method for spin forming lipskins |
| 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 |
-
2021
- 2021-11-19 CN CN202111392053.9A patent/CN114018155B/en active Active
Patent Citations (8)
| 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 |
| US20190184443A1 (en) * | 2017-12-19 | 2019-06-20 | Standex International Corporation | Method for spin forming lipskins |
| 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 (2)
| Title |
|---|
| 沈萌红等: "基于Pro/E的三维参数化零件库的开发", 《中国制造业信息化》 * |
| 童康康等: "航空零件化铣胶膜激光刻线的视觉检测技术研究", 《电气与自动化》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114782315A (en) * | 2022-03-17 | 2022-07-22 | 清华大学 | Method, device and equipment for detecting shaft hole assembly pose precision and storage medium |
| CN114782315B (en) * | 2022-03-17 | 2024-07-09 | 清华大学 | Shaft hole assembly pose precision detection method, device, equipment and storage medium |
| 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 |
| CN115846886A (en) * | 2023-02-02 | 2023-03-28 | 中航西安飞机工业集团股份有限公司 | Chemical milling accurate carving method for aircraft skin |
| CN117289651A (en) * | 2023-11-24 | 2023-12-26 | 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 |
| 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 |
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