CN105043259A - Numerical control machine tool rotating shaft error detection method based on binocular vision - Google Patents
Numerical control machine tool rotating shaft error detection method based on binocular vision Download PDFInfo
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Abstract
The invention discloses a numerical control machine tool rotating shaft error detection method based on binocular vision, belongs to the machine tool precision detection technology field and relates to a double rotating shaft geometry error detection and identification method of a five-axes numerical control machine tool. The method adopts a high-resolution binocular vision system. Position information of a marking point which is pasted on a machine tool rotation table surface is collected. Through camera calibration, image segmentation, marking point extraction and a machine tool rotating shaft error identification model, detection acquisition of a two-position error and a two-angle error of a machine tool rotating shaft is realized. Rapid measurement of a geometrical parameter is completed. A circular marking point is used. An image processing program is simple, feature extraction precision is high, robustness is good and measurement is rapid and convenient. Simultaneously, a problem that numerical control machine tool rotating shaft installation error detection and identification are difficult is solved and a new direction is provided for a machine tool error detection and identification technology.
Description
Technical field
The invention belongs to machine tool accuracy detection technique field, relate to a kind of two rotating shaft geometric error detection and identification methods of five-axle number control machine tool.
Background technology
In the field such as Aeronautics and Astronautics and national defense industry, the requirement manufactured efficient, high precision is more and more higher.Especially for parts such as baroque engine impeller, Making mold, five-axle number control machine tool can realize the flexible control in position and direction, is current Application comparison technology widely.But compare three axis numerically controlled machine, five-axle number control machine tool not only has the error of three linear axis, also add the error of two turning axles simultaneously, this causes machine tool error item to increase, and unavoidably.And turning axle is as the important composition component of five-axle number control machine tool, because of the method that it lacks precision calibration and error compensation, it is the main source of lathe quasistatic error and dynamic error.Therefore, the precision that can not only maintain lathe with the error of demarcating turning axle is made regular check on, simultaneously for precision manufactureing is laid a good foundation.
At present, the technology that NC Machine Error detects mainly comprises: material standard mensuration, laser interferometer, ball bar, laser tracker etc.The patent No. that Dalian Chuan Da Technology Co., Ltd. Dong Hai invents is that CN102476323A " Novel numerical control machine tool error detector " has invented a kind of error-detecting instrument based on Circular test, by analyzing the error of Circular test interpolation, and assessment machine tool capability.But this method is not easy to the identification realizing every error, cause error compensation difficulty.University Of Chongqing Tao Gui treasured waits the patent No. of people's invention to be the real-time detection technique of machine tool error that CN103143984A " the machine tool error dynamic compensation method based on laser tracker " has invented based on laser tracker, although this method is simple, convenient, cost is higher.Laser interferometer measurement precision is higher, but operation more complicated.In sum, current method is used for the error-detecting of linear axis, and cost is higher, and is not suitable for the detection and identification of turning axle error.Therefore, turning axle error-detecting and the identification technique of studying a kind of convenient, fast, low cost is necessary.
Summary of the invention
The technical barrier that the present invention will solve is the problem overcoming prior art, invents a kind of rotary axis of machine tool alignment error measuring method based on binocular vision.Be affixed on rotating shaft surface to be measured by organizing reflective encoder gauge point, digital control system controls rotary axis of machine tool and determines angle rotation, and utilizes binocular vision to gather reflective encoder gauge point in each angle, and obtains coded markings point three dimensional local information more.Based on above-mentioned gauge point positional information, adopt least square fitting space circle, and obtain the position coordinates of space circle, compare with desired axis center and obtain rotating shaft center to be measured linear error; Meanwhile, utilize gauge point position matching space plane, the normal vector of this plane and desirable shaft axis vector ratio comparatively, can record the angular error that rotating shaft is installed.The method adopts circular markers, and not only image processing program is simple, feature extraction precision is high, and robustness good, measure quick, convenient.Meanwhile, the problem of the detection of numerically-controlled machine turning axle alignment error, identification difficulty is this method solved, for machine tool error detection and identification technology provides new direction.
The technical solution adopted in the present invention is a kind of numerically-controlled machine turning axle error detection method based on binocular vision, it is characterized in that, the present invention adopts high resolving power binocular vision system, gather the positional information being affixed on lathe turntable surface annulus coded markings point, turntable often turns over certain angle, vision system collection once, until rotate a circle.Eventually pass camera calibration, Iamge Segmentation, gauge point extraction, two site errors of rotary axis of machine tool error identification model realization rotary axis of machine tool and the detection collection of two angular errors, obtain 4 alignment errors of rotary axis of machine tool, complete the Quick Measurement of geometric parameter; Detection method concrete steps are as follows:
(1) demarcation of video camera
The binocular vision calibration method based on high precision gridiron pattern target that the present invention adopts the people such as Zhang Zhengyou to propose;
First use Zhang Shi scaling method to determine the inside and outside parameter of two cameras, then three-dimensional reconstruction is carried out to gridiron pattern target angle point, and rebuild the deviation of coordinate and actual coordinate according to angle point, set up function f (x), global optimization is carried out to inside and outside parameter; As follows:
f(x)＝(x
p-x
i)
2+(y
p-y
i)
2+(z
p-z
i)
2(1)
Wherein: x
p, y
p, z
pfor the actual coordinate of each angle point, and x
i, y
i, z
ifor rebuilding each angular coordinate obtained, then set up objective function F (x) as follows:
Wherein,
for have the quadratic sum of a departure function, application LM method is optimized this objective function F (x), obtains the globally optimal solution of inside and outside parameter;
(2) characteristics of image segmentation
First noise reduction, filtering process are carried out to image, utilize Gray-scale value method by all target signatures and background initial gross separation subsequently, Gray-scale value method respective formula:
Wherein, g (x, y) corresponding to image (x, y) pixel gray-scale value, T represents selected Gray-scale value, G
1, G
2for background set, signature set; Then, carry out connected component labeling to signature set, and utilize region area to remove uninterested connected region in image as threshold value, respective formula is as follows:
Wherein, i=1,2....n are n connected region, g
i(x, y) is the area of i-th connected region, and S is connected region area threshold value; If connected region area is less than S, then this connected region is set to background;
(3) extraction of signature
1) encoded point center extraction:
First adopt the connected region in 8 connected component labeling images, utilize curvature limitation subsequently, the connected region of loseing interest in that curvature is comparatively large and less is removed, and respective formula is as follows:
Wherein, i=1,2....n are n connected region, and gt (i) is the eccentricity of i-th connected region, e
1, e
2for eccentricity threshold value, i-th connected domain is set to background by L (i)=0 expression; So, coded markings dot image accurately can just be obtained; Subsequently, utilize centroid algorithm, obtain coded markings dot center coordinate;
2) encoded point identification:
The present invention adopts annulus coded markings point, and annulus encoding centre is circle mark point 1, is concentric segmentation circle ring area around gauge point, for characterizing the identity information of annulus coding, is called coding-belt 2; This annulus is equally divided into 15 parts according to angle, 24 degree every part, is equivalent to bit; Each gets foreground for white, and rear scenery is black, and corresponding binary coding is " 1 ", " 0 "; From the gauge point center of circle, according to the solid and hollow coding-belt of certain orientation scanning, white represents solid, and black represents hollow, and scan solid code band and be designated as 1, hollow code band is designated as 0; If do not scan coding-belt, Ze Cong center starts to rescan; After run-down, namely the code value sequence of whole encoded point is all read, and forms a binary sequence, and each binary sequence is corresponding with a decimal integer again, thus obtains the identity information of each encoded point;
After decoding, according to the identity information that different coding gauge point is sent out, under the pixel coordinate of the same encoded point of each angle is stored in a file, obtain successively the pixel coordinate of even gauge point left images; The inside and outside parameter of the video camera that recycling Zhang Shi standardization obtains, rebuilds the three-dimensional coordinate of each gauge point;
(4) rotary axis of machine tool error identification
Numerically-controlled machine turning axle error mainly contains two kinds of error sources, is respectively to connect error and volumetric errors; The former with to have nothing to do with lathe command position, usually because turning axle installation deviation causes, the latter is relevant with lathe command position, affects by machine tool element machining precision; The present invention is directed to the connection error of rotary axis of machine tool, invent a kind of rotary axis of machine tool error-detecting discrimination method based on binocular vision; Connect error and have 4, comprise 2 linear position errors, 2 angular errors;
According to the three-dimensional coordinate of encoded point under visual coordinate system under the different angles obtained, utilize least square fitting plane, set up plane equation:
Ax+By+Cz+D＝0(6)
Wherein, A, B, C, D are plane equation coefficient; Can obtain after simplifying:
For realizing plane fitting, set up objective function F (x):
Wherein,
(x
i, y
i, z
i) (i=1,2,3...n) be the three-dimensional coordinate of n coded markings point under visual coordinate system; The plane of matching can be obtained thus, and obtain the normal vector of this plane.Relatively the normal vector of fit Plane and the normal vector of ideal plane, solve 2 angular errors of the connection error of turning axle;
For identification turning axle connects the linear position error of error, according to encoded point position relationship, every two points draw a straight line L
1; When turning axle rotates according to certain angle, this straight line can be followed rotating shaft and be carried out rotary and to be in line L
2, and straight line L
1with straight line L
2intersect at a P
1; Successively, turning axle rotates a circle, and form n bar straight line altogether, every two straight lines meet at a P
i, i=1,2 ... .n/2, to average P to coordinates of these points, P is considered as the center of circle of actual circle; The actual center of circle and the coordinate in the desirable center of circle can obtain the linear position error that rotary axis of machine tool is connected error:
er(x)＝P(x)-P
ideal(x)(9)
er(y)＝P(y)-P
ideal(y)(10)
Wherein, er (x), er (y) are respectively turning axle in X, Y-direction linear position error, X, Y-coordinate that P (x), P (y) are the actual center of circle of turning axle, P
ideal(x), P
idealy () is X, the Y-coordinate in the desirable turning axle center of circle;
The invention has the beneficial effects as follows that the method utilizes reflective encoder gauge point to realize 4, numerically-controlled machine turning axle and connects the detection and identification of error, have convenient, fast, robustness good, anti-noise ability is strong, without the need to the advantage such as cooperation of laser alignment and other axles.The method effectively improves the efficiency of rotary axis of machine tool error-detecting, avoids loaded down with trivial details measuring process and the identification model of complexity, for NC Machine Error detect provide one fast, method easily; Provide the foundation and direction for other error-detectings of lathe simultaneously.
Accompanying drawing explanation
Fig. 1 is machine tool error pick-up unit illustraton of model.Wherein, 1 ?left video camera, 2 ?right video camera, 3 ?reflective encoder gauge point, 4 ?rotation worktable of machine tool, 5 ?numerically-controlled machine.
Fig. 2 is annulus coded markings point diagram.Wherein, 1 ?circle mark point, 2 ?coding-belt.
Fig. 3 is lathe anglec of rotation axis error identification principle figure.1 ?desirable turntable plane, 2 ?actual turntable plane, 3 ?actual turntable normal vector, 4 ?coded markings point, ε
1?the angular error of rotary axis of machine tool and actual turntable normal vector 3, ε
2?the angular error of rotary axis of machine tool and Z axis.
Fig. 4 is rotary axis of machine tool site error identification principle figure.1 ?desirable turntable, 2 ?actual turntable, 3 ?actual turntable center, 4 ?coded markings point, 5 ?ideal turntable center, δ
1?the linear position error of rotary axis of machine tool and X-axis, δ
2?the linear position error of rotary axis of machine tool and Y-axis.
Embodiment
The specific embodiment of the present invention is described in detail below in conjunction with technical scheme and accompanying drawing.Accompanying drawing 1 is the machine tool error pick-up unit illustraton of model based on binocular vision.This method gathers the coordinate information of the coded markings point of tested turntable surface by left and right two video cameras 1,2, treated solution identification turning axle link error.
First install and measure device, left and right video camera 1,2 is arranged on above turning axle, and left and right high-speed camera 1,2 is fixed, adjustment position makes to measure visual field in the public view field of left and right high-speed camera 1,2, regulates light-source brightness to improve the brightness of measurement space; Subsequently, reflective marker point 3 is affixed on arbitrarily turntable 4 surface, and controls lathe and rotate by certain angle, often rotate once, left and right camera 1,2 is taken once, until turntable 4 rotates a circle; Finally, the work such as binocular camera demarcation, Iamge Segmentation, feature extraction, error identification are carried out by graphics workstation.
The present invention adopts two high-resolution cameras 1,2 shot object motion conditions, two video camera models be VA ?29M video camera, resolution: 6576 × 4384, target surface size: 35mm, frame frequency: 5fps.Camera lens model is Canon EF24 ?70mmf/2.8LIIUSM zoom lens, and parameter is as follows, lens focus: f=24 ?70, maximum ring: F2.8, camera lens weight: 805g, Lens: 88.5mm × 113mm.Shooting condition is as follows:, picture pixels is 6576 × 4384, and lens focus is 50mm, and object distance is 460mm, and visual field is about 200mm × 200mm.
(1) demarcation of high-speed camera is carried out
The present invention adopts based on the camera marking method based on two dimensional surface gridiron pattern target of people's propositions such as Zhang Zhengyou, carry out demarcating the intrinsic parameter K obtaining two high speed cameras, outer parameter [RT], distortion factor δ, apply Levenberg-Marquardt (LM) method to be again optimized formula (2), can obtain the globally optimal solution of each camera interior and exterior parameter of binocular vision system, calibration result is as shown in table 1:
Table 1 calibration result
(2) characteristics of image segmentation
Gray-scale value method is utilized to carry out pre-service to collected image, according to formula (3), by gray threshold, by coded markings point and background initial gross separation.Subsequently, connected component labeling is carried out to coded markings set, and utilize region area to remove uninterested connected region in image as threshold value, finally realize Iamge Segmentation.
(3) extraction of signature
Adopt the connected region in 8 connected component labeling images, utilize curvature limitation subsequently, the connected region of loseing interest in that curvature is comparatively large and less is removed, and gets a distinct image.Utilize centroid algorithm simultaneously, obtain coded markings dot center coordinate; Fig. 2 is circle codification mark point diagram, and indicate circle mark point 1 for white, peripheral circular region representation coded markings point identity information is coding-belt 2.From the circle mark point center of circle, according to clockwise direction, scan solid and hollow coding-belt.Wherein, white represents solid, and black represents hollow, and scan solid code band and be designated as 1, hollow code band is designated as 0.After run-down, read the code value sequence of whole encoded point, form a binary sequence 001100111011111, and change into a decimal integer 6607, thus obtain the identity information of each encoded point.In addition, rebuild through binocular, the three-dimensional coordinate of coded markings point can be obtained.
(4) rotary axis of machine tool error identification
In the present invention, control every 5 ° of lathe and turn once, dynamic 360 ° of corotation, and each angle acquisition left images, and reconstruct encoded point three-dimensional coordinate.Connecting the detection and identification of error for realizing rotary axis of machine tool, carrying out plane fitting respectively and the center of circle is asked for.First, shown in accompanying drawing 3, according to the three-dimensional coordinate of encoded point 4 under visual coordinate system under the different angles obtained, utilize formula (6), (7), (8), by least square fitting gauge point plane 2, and through calculating the normal vector 3 obtaining this plane.The relatively normal vector 3 of fit Plane and the normal vector of ideal plane, Z axis vector is considered as ideal plane normal vector, solves the angular error ε of rotary axis of machine tool and actual turntable normal vector 3
1, the angular error ε of rotary axis of machine tool and Z axis
2two angular errors.
For identification turning axle connects the linear position error of error, according to encoded point position relationship, select 2 encoded points, form 1 straight line, be designated as initial straight L
1.Every 5 ° of lathe rotates once, does not have rotation capital to form new straight line, rotates one week successively, every bar initial straight all can form 71 new straight lines, and the intersection point of these straight lines is considered as center of circle O, as shown in Figure 4, average eventually through three groups of experiments, determine the accurate center of circle.Utilize formula (9), (10) actual center of circle 3 and the coordinate in the desirable center of circle 5, finally obtain the linear position error delta of rotary axis of machine tool and X-axis
1, rotary axis of machine tool and Y-axis linear position error delta
2.
The present invention utilizes binocular vision to detect coded markings dot information, and by setting up better simply error identification model, realizes rotary axis of machine tool error-detecting and identification.The method have convenient, fast, robustness good, anti-noise ability is strong, effectively improve the efficiency of rotary axis of machine tool error-detecting without the need to the advantage such as cooperation of laser alignment and other axles, provide the foundation and direction for other error-detectings of lathe simultaneously.
Claims (1)
1. the numerically-controlled machine turning axle error detection method based on binocular vision, it is characterized in that, the present invention adopts high resolving power binocular vision system, gather the positional information being affixed on lathe turntable surface annulus coded markings point, turntable often turns over certain angle, vision system collection once, until rotate a circle.Eventually pass camera calibration, Iamge Segmentation, gauge point extraction, two site errors of rotary axis of machine tool error identification model realization rotary axis of machine tool and the detection collection of two angular errors, complete the Quick Measurement of geometric parameter; Detection method concrete steps are as follows:
(1) demarcation of video camera
The binocular vision calibration method based on high precision gridiron pattern target that the present invention adopts the people such as Zhang Zhengyou to propose;
First use Zhang Shi scaling method to determine the inside and outside parameter of two cameras, then three-dimensional reconstruction is carried out to gridiron pattern target angle point, and rebuild the deviation of coordinate and actual coordinate according to angle point, set up function f (x), global optimization is carried out to inside and outside parameter; As follows:
f(x)＝(x
p-x
i)
2+(y
p-y
i)
2+(z
p-z
i)
2(1)
Wherein: x
p, y
p, z
pfor the actual coordinate of each angle point, and x
i, y
i, z
ifor rebuilding each angular coordinate obtained, then can set up objective function F (x) as follows:
Wherein,
for have the quadratic sum of a departure function, application LM method is optimized this objective function F (x), obtains the globally optimal solution of inside and outside parameter;
(2) characteristics of image segmentation
First noise reduction, filtering process are carried out to image, utilize Gray-scale value method by all target signatures and background initial gross separation, Gray-scale value method respective formula:
Wherein, g (x, y) corresponding to image (x, y) pixel gray-scale value, T represents selected Gray-scale value, G
1, G
2for background set, signature set; Carry out connected component labeling to signature set, and utilize region area to remove uninterested connected region in image as threshold value, respective formula is as follows:
Wherein, i=1,2....n are n connected region, g
i(x, y) is the area of i-th connected region, and S is connected region area threshold value; If connected region area is less than S, then this connected region is set to background;
(3) extraction of signature
1) encoded point center extraction:
First adopt the connected region in 8 connected component labeling images, utilize curvature limitation subsequently, the connected region of loseing interest in that curvature is comparatively large and less is removed, and respective formula is as follows:
Wherein, i=1,2....n are n connected region, and gt (i) is the eccentricity of i-th connected region, e
1, e
2for eccentricity threshold value, i-th connected domain is set to background by L (i)=0 expression; So, coded markings dot image accurately is just obtained; Utilize centroid algorithm, obtain coded markings dot center coordinate;
2) encoded point identification:
The present invention adopts annulus coded markings point, and annulus encoding centre is circle mark point (1), is concentric segmentation circle ring area around gauge point, for characterizing the identity information of annulus coding, is called coding-belt (2); This annulus is equally divided into 15 parts according to angle, 24 degree every part, is equivalent to bit; Each gets foreground for white, and rear scenery is black, and corresponding binary coding is " 1 ", " 0 "; From the gauge point center of circle, according to certain orientation, scan solid and hollow coding-belt, scan solid code band and be designated as 1, hollow code band is designated as 0, if do not scan coding-belt, Ze Cong center starts to rescan; After run-down, namely the code value sequence of whole encoded point is all read, and forms a binary sequence, and each binary sequence is corresponding with a decimal integer again, thus obtains the identity information of each encoded point;
After decoding, according to the identity information that different coding gauge point is sent out, under the pixel coordinate of the same encoded point of each angle is stored in a file, obtain successively the pixel coordinate of even gauge point left images; The inside and outside parameter of the video camera that recycling Zhang Shi standardization obtains, rebuilds the three-dimensional coordinate of each gauge point;
(4) rotary axis of machine tool error identification
The connection error that the present invention is directed to rotary axis of machine tool carries out detection and identification, comprises 2 linear position errors, 2 angular errors;
According to the three-dimensional coordinate of encoded point under visual coordinate system under the different angles obtained, utilize least square fitting plane, set up plane equation:
Ax+By+Cz+D＝0(6)
Wherein, A, B, C, D are plane equation coefficient; Can obtain after simplifying:
For realizing plane fitting, set up objective function F (x):
Wherein,
(x
i, y
i, z
i) (i=1,2,3...n) be the three-dimensional coordinate of n coded markings point under visual coordinate system; The plane of matching can be obtained thus, and obtain the normal vector of this plane.Relatively the normal vector of fit Plane and the normal vector of ideal plane, solve 2 angular errors of the connection error of turning axle;
For identification turning axle connects the linear position error of error, according to encoded point position relationship, every two points draw a straight line L
1; When turning axle rotates according to certain angle, this straight line can be followed rotating shaft and be carried out rotary and to be in line L
2, and straight line L
1with straight line L
2intersect at a P
1; Successively, turning axle rotates a circle, and form n bar straight line altogether, every two straight lines meet at a P
i, i=1,2,3 ... n/2, to average P to coordinates of these points, P is considered as the center of circle of actual circle; The actual center of circle and the coordinate in the desirable center of circle can obtain the linear position error that rotary axis of machine tool is connected error:
er(x)＝P(x)-P
ideal(x)(9)
er(y)＝P(y)-P
ideal(y)(10)
Wherein, er (x), er (y) are respectively turning axle in X, Y-direction linear position error, X, Y-coordinate that P (x), P (y) are the actual center of circle of turning axle, P
ideal(x), P
idealy () is X, the Y-coordinate in the desirable turning axle center of circle.
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