CN114102256A - Machine tool rotating shaft geometric error identification method and device and storage medium - Google Patents

Machine tool rotating shaft geometric error identification method and device and storage medium Download PDF

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CN114102256A
CN114102256A CN202111299886.0A CN202111299886A CN114102256A CN 114102256 A CN114102256 A CN 114102256A CN 202111299886 A CN202111299886 A CN 202111299886A CN 114102256 A CN114102256 A CN 114102256A
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machine tool
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visual target
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geometric error
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CN114102256B (en
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陈炜铧
李炳燃
张辉
赵彤
叶佩青
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Tsinghua University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/24—Arrangements for observing, indicating or measuring on machine tools using optics or electromagnetic waves
    • B23Q17/248—Arrangements for observing, indicating or measuring on machine tools using optics or electromagnetic waves using special electromagnetic means or methods
    • B23Q17/249—Arrangements for observing, indicating or measuring on machine tools using optics or electromagnetic waves using special electromagnetic means or methods using image analysis, e.g. for radar, infrared or array camera images
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The machine tool rotating shaft geometric error identification method, device and storage medium provided by the present disclosure comprise: installing a visual target and a monocular camera, and calibrating installation errors of the visual target and the monocular camera; identifying the geometric error of the C axis: measuring the knife length and Y offset of the visual target; randomly selecting a plurality of machine tool program coordinates, controlling an A axis to be static, controlling a C axis to do RTCP motion and stop at equal intervals at each machine tool program coordinate, and acquiring a mark C sequence image to obtain the three-dimensional coordinate deviation of the visual target of each machine tool program coordinate at each stop so as to calculate the geometric error of the C axis; and (3) identifying the geometric error of the A axis: randomly selecting a plurality of machine tool program coordinates, controlling the C axis to be static at each machine tool program coordinate, controlling the A axis to do RTCP motion and stop at equal intervals, collecting mark A sequence images, obtaining the three-dimensional coordinate deviation of the visual target of each machine tool program coordinate at each stop, and calculating the geometric error of the A axis. The measurement efficiency and the precision of the method are high.

Description

Machine tool rotating shaft geometric error identification method and device and storage medium
Technical Field
The disclosure belongs to the field of machine tool geometric error measurement, and relates to a geometric error identification method and device for a rotating shaft of a five-axis numerical control machine tool and a storage medium.
Background
According to the error definition of the machine tool, the difference value of the ideal response and the actual response of the machine tool is the error of the machine tool, the error sources of the machine tool are many, the machine tool error can be divided into a geometric error, a thermal error, a force error, a control error and the like according to the difference of the source generated by the machine tool error, the first three error sources are called quasi-static error sources, the quasi-static error sources are the sources of the difference between the ideal position and the actual position of a machine tool cutter in a workpiece coordinate system, the quasi-static error sources can slowly change along with time and depend on the topological structure of the machine tool, and about 70% of machine tool error is caused.
Geometric errors of numerically controlled machine tools can be classified into two types by nature, including Position dependent geometric errors (hereinafter abbreviated as "pdgs") and Position independent geometric errors (hereinafter abbreviated as "PIGEs"). Among them, PDGEs is mainly due to shape and position errors of parts caused by low machining accuracy of parts of a manufacturing machine tool itself, and PDGEs of a rotating shaft is also called motion errors (motions). PIGEs are machine tool installation errors caused by manufacturing and assembling defects of parts, load variation and the like, and PIGEs of a rotating shaft are also called structural errors (structures). For five-axis numerically controlled machine tools, according to the regulations in ISO 230-7 and GB/T17421.7, there are 6 items PDGES when the rotating shaft moves, including 3 translation errors (delta)xc,δyc,δzc)，(δxa,δya,δza) And 3 rotation errors ((theta))xc,θyc,θzc)，(θxa,θya,θza) See table below for details):
Figure BDA0003337981000000011
compare in traditional triaxial digit control machine tool, five digit control machine tools have increased two rotation axes, all have great promotion in machining precision, quality and machining efficiency. The calibration method for the geometric errors of the translational shaft of the five-axis numerical control machine tool is mature, the rotary shaft is used as an important component of the five-axis numerical control machine tool, the geometric errors of the rotary shaft are more complicated due to the influence of spatial multi-shaft linkage on the five-axis numerical control machine tool, the machining precision of the machine tool is more seriously influenced, and the calibration is more complicated relative to the translational shaft, so that the calibration and compensation for the geometric errors of the rotary shaft of the five-axis numerical control machine tool have important significance.
The existing R-test measuring instrument and the ball rod instrument have the main defects of relatively high measuring cost, relatively complex structure and long measuring time of the ball rod instrument, and the vision measurement has the advantages of low measuring cost, high measuring precision and high measuring efficiency and can be applied to the error measurement of the rotating shaft of a five-axis machine tool.
Disclosure of Invention
The present disclosure is directed to solving one of the problems set forth above.
Therefore, the method for identifying the geometric error of the machine tool rotating shaft provided by the embodiment of the first aspect of the disclosure can finish detecting the geometric error of the rotating shaft of the five-axis numerical control machine tool by adopting a monocular vision system and combining a high-precision vision target. The method for identifying the geometric error of the rotating shaft of the machine tool provided by the embodiment of the first aspect of the disclosure comprises the following steps:
respectively installing a visual target and a monocular camera provided with a low-distortion microscope lens at the tail end of a cutter handle of the machine tool and on a rotary table; the visual target is provided with a mark A, a mark B and a mark C which are mutually vertical and are respectively vertical to the axis A, the axis B and the axis C;
calibrating the installation errors of the monocular camera and the visual target respectively;
identifying the geometric error of the C axis, including:
according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the A axis to be still at the position of A0 degrees at each machine tool program coordinate, enabling the C axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring the image of the mark C on the visual target by using the monocular camera at each stopping position to form a corresponding mark C sequence image; obtaining three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark C sequence images in each measurement process, and calculating the geometric error of the C axis;
identifying the geometric error of the A axis, comprising:
measuring the cutter length and Y bias of the visual target, wherein the cutter length of the visual target is the distance from the end surface of the machine tool spindle to the center of the mark A or the mark B, and the Y bias of the visual target is the Y-direction component of the deviation between the mark A and the center of the machine tool spindle after the visual target is installed;
according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the C axis to be stationary at a C0-degree position at each machine tool program coordinate, enabling the A axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring images of the mark A on the visual target by using the monocular camera at each stopping position to form corresponding mark A sequence images; and obtaining the three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark A sequence images of each measurement process, so as to calculate the geometric error of the A axis.
The method for identifying the geometric error of the rotating shaft of the machine tool provided by the embodiment of the first aspect of the disclosure has the following characteristics and beneficial effects:
the embodiment of the first aspect of the disclosure provides a scheme for realizing the geometric error of a rotating shaft of a five-axis machining center by using the advantages of accuracy and high efficiency of vision measurement, and can quickly complete the compensation of the geometric error of the rotating shaft of the five-axis machining center. Compared with the existing measurement means such as the R-TEST and the ball rod instrument, the method is simple, low in cost and high in measurement efficiency, and can achieve the same measurement effect close to that of a professional measurement instrument.
In some embodiments, calibrating the installation error of the monocular camera comprises:
and controlling the machine tool to move for a plurality of times at equal intervals along the axis direction of the translational shaft, acquiring sequence images of the visual target by using the monocular camera, calculating the movement displacement of the visual target in a camera coordinate system according to the sequence images, and fitting to obtain an included angle between the camera coordinate system and a machine tool main shaft coordinate system to serve as the installation error of the monocular camera.
In some embodiments, the fitting is a least squares linear fit.
In some embodiments, calibrating the installation error of the visual target comprises:
and controlling each shaft of the machine tool to be immobile, enabling the main shaft of the machine tool to perform circular motion and stop at equal intervals, acquiring images of the visual target at each stopping position by using the monocular camera, acquiring the central point of each image, fitting, and acquiring the installation error of the visual target.
In some embodiments, the fitting is a least squares circle fit.
In some embodiments, the mark on the visual target is a checkerboard, a dot calibration board or a two-dimensional code calibration board, and the measuring of the three-dimensional coordinate deviation of the visual target by the monocular camera includes:
controlling the monocular camera to obtain a full-depth-of-field image sequence, performing definition calculation on the full-depth-of-field image sequence by using a Brenner function, obtaining a definition-image sequence curve, and fitting a definition z-direction displacement function; controlling the monocular camera to image at the optimal definition position, performing sub-pixel identification on the mark characteristic point of the visual target, and calibrating the pixel distance and the real displacement; and acquiring an image sequence in the measuring process, and realizing the three-dimensional coordinate deviation measurement of the visual target.
In some embodiments, the machine program coordinates are selected to be two, and the geometric error of the C-axis is obtained using the following equation:
Figure BDA0003337981000000031
wherein the content of the first and second substances,
Figure BDA0003337981000000032
for the selected two machine tool program coordinates;
Figure BDA0003337981000000033
for machine tool program coordinates xc1,yc1,zc1A three-dimensional coordinate deviation of the visual target at the i-th stop,
Figure BDA0003337981000000034
for machine tool program coordinates xc2,yc2,zc2A three-dimensional coordinate deviation of the visual target at the i-th stop; deltaxci,δyciThe translation error along the x and y axes, theta, respectively, at the i-th stop of the C-axis motionxci,θyci,θzciThe rotation errors along the x, y and z axes at the i-th stop of the C-axis motion are respectively.
In some embodiments, the machine tool program coordinates are chosen to be two, and the geometric error of the a axis is obtained using the following equation:
Figure BDA0003337981000000041
wherein (x)a1,ya1,za1,xa2,ya2,za2) For the selected two machine tool program coordinates;
Figure BDA0003337981000000042
for machine tool program coordinates (x)a1,ya1,za1) A three-dimensional coordinate deviation of the visual target at the i-th stop,
Figure BDA0003337981000000043
for machine tool program coordinates (x)a2,ya2,za2) A three-dimensional coordinate deviation of the visual target at the i-th stop; deltayai,δzaiThe translation error along the y and z axes, theta, at the i-th stop of the A-axis motionxai,θyai,θzaiThe rotation errors along the x, y, z axes at the ith stop of the a axis motion, respectively.
The device for identifying the geometric error of the rotating shaft of the machine tool provided by the embodiment of the second aspect of the disclosure comprises:
the monocular vision measuring module comprises a monocular camera provided with a low-distortion microscope lens, a camera pose fixing part and a vision target; the visual target is provided with a mark A, a mark B and a mark C which are mutually vertical and are respectively vertical to the axis A, the axis B and the axis C, and the visual target is tightly connected with the main shaft of the machine tool through the handle of the machine tool; the monocular camera is fixedly connected with the machine tool rotary table through the camera pose fixing piece;
the installation error calibration module is used for respectively calibrating the installation errors of the monocular camera and the visual target;
the C-axis geometric error measuring module is used for randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range according to the stroke range of the machine tool, controlling the A axis to be still at the position of A0 degrees at each machine tool program coordinate, enabling the C axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring the image of the mark C on the visual target by utilizing the monocular camera at each stopping position to form a corresponding mark C sequence image; obtaining three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark C sequence images in each measurement process, and calculating the geometric error of the C axis; and
the A-axis geometric error measuring module is used for measuring the cutter length and the Y offset of the visual target, the cutter length of the visual target is the distance from the end surface of the machine tool spindle to the center of the mark A or the mark B, and the Y offset of the visual target is the Y-direction component of the center deviation between the mark A and the machine tool spindle after the visual target is installed; according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the C axis to be stationary at a C0-degree position at each machine tool program coordinate, enabling the A axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring images of the mark A on the visual target by using the monocular camera at each stopping position to form corresponding mark A sequence images; and obtaining the three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark A sequence images of each measurement process, so as to calculate the geometric error of the A axis.
The third aspect of the present disclosure provides a computer-readable storage medium, which stores computer instructions for causing the computer to execute the above-mentioned machine tool rotation axis geometric error identification method.
Drawings
Fig. 1 is a flowchart of a method for identifying geometric errors of a machine tool rotation axis according to an embodiment of the first aspect of the disclosure.
Fig. 2 (a) and (b) are schematic diagrams of a monocular vision measuring module and different installation states thereof, respectively, in a method provided by an embodiment of the first aspect of the present disclosure.
FIG. 3 is a schematic diagram of a visual target in a monocular vision measuring module according to an embodiment of the first aspect of the present disclosure
Fig. 4 is a schematic diagram of calibration of installation errors of a monocular camera in the method provided in the embodiment of the first aspect of the present disclosure.
Fig. 5 is a schematic diagram of circle fitting for C-axis geometric errors in a method provided in an embodiment of the first aspect of the present disclosure.
Fig. 6 is a flowchart of three-dimensional coordinate deviation measurement of a visual target by using a monocular vision measuring module when identifying a C-axis geometric error in the method according to the embodiment of the first aspect of the present disclosure.
Fig. 7 is a schematic diagram of measuring an a-axis geometric error in a method provided in an embodiment of the first aspect of the present disclosure.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the third aspect of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
On the contrary, this application is intended to cover any alternatives, modifications, equivalents, and alternatives that may be included within the spirit and scope of the application as defined by the appended claims. Furthermore, in the following detailed description of the present application, certain specific details are set forth in order to provide a better understanding of the present application. It will be apparent to one skilled in the art that the present application may be practiced without these specific details.
Referring to fig. 1, a method for identifying geometric errors of a rotating shaft of a machine tool provided in an embodiment of a first aspect of the present disclosure includes:
respectively installing a visual target and a monocular camera provided with a low-distortion microscope lens at the tail end of a cutter handle of a five-axis numerical control machine tool and on a rotary table, wherein the movement position of a machine tool main shaft relative to the machine tool rotary table is represented by a mark on the visual target, the mark on the visual target comprises three marks A, a mark B and a mark C which are mutually perpendicular, the marks A, the mark B and the mark C are respectively perpendicular to an axis A, an axis B and an axis C of the machine tool, and a sequence image of the visual target is acquired by the monocular camera;
respectively calibrating the installation errors of the monocular camera and the visual target;
identifying the C-axis geometric error, comprising:
randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range according to the stroke range of the machine tool, controlling an A axis to be still at an A0 DEG position (namely the A axis is at a0 DEG position) at each machine tool program coordinate, enabling a C axis to do nose point following (RTCP) motion (controlling the measurement feeding speed to be less than F100mm/min), stopping at equal intervals in the motion process, acquiring an image of a mark C on the visual target by using a monocular cameras at each stopping position to form a corresponding mark C sequence image, and obtaining the three-dimensional coordinate deviation of the visual target at each stopping position of each machine tool program coordinate according to the mark C sequence image in each measurement process so as to calculate the geometric error of the C axis;
identifying the geometric error of the A axis, comprising the following steps:
defining the cutter length of the visual target as the distance from the end surface of the machine tool spindle to the center of the mark A or the mark B, defining the Y bias of the visual target as the Y-directional component of the deviation between the mark A and the center of the machine tool spindle after the visual target is installed, performing off-line measurement on the cutter length and the Y bias of the visual target, and inputting the parameters of a numerical control machine tool cutter system;
according to the stroke range of the machine tool, a plurality of machine tool program coordinates of the machine tool are randomly selected in the machining range, at each machine tool program coordinate, the C axis is controlled to be still at the C0 degrees (namely the C axis is at the 0 degree position), the A axis is controlled to do low-speed RTCP motion (the measurement feed speed is controlled to be less than F100mm/min), stopping is conducted at equal intervals in the motion process, a monocular camera is used for collecting images of a mark A on a visual target at each stopping position to form a corresponding mark A sequence image, and the three-dimensional coordinate deviation of the visual target at each stopping position of each machine tool program coordinate is obtained according to the mark A sequence image in each measurement process, so that the geometric error of the A axis is calculated.
In some embodiments, before the rotation axis geometric error measurement is performed, a monocular vision measuring module as shown in fig. 2 is installed, and fig. 2 (a) and (b) show an assembly view of the monocular vision measuring module at the time of the C-axis geometric error measurement and the a-axis geometric error measurement, respectively. Referring to fig. 2 (a), the monocular vision measuring module comprises a monocular camera 1, a camera pose fixing member 2 and a high-precision vision target 3; referring to fig. 3, the visual target 3 is equipped with high-precision characteristic marks, which include three marks a, B, and C perpendicular to each other, after the visual target 3 is mounted, the corresponding marks are perpendicular to the corresponding rotating shafts, specifically, the mark a is perpendicular to the a axis, the mark B is perpendicular to the B axis, and the mark C is perpendicular to the C axis, the marks on the visual target 3 can be selected from marks such as checkerboard, dot calibration board, two-dimensional code calibration board, and in one example, the marks are selected as checkerboard, the size of a single checkerboard is 0.01mm by 0.01mm, the number of the checkerboard is 10 by 10, and the precision is ± 0.001 mm. The visual target 3 is tightly connected with a main shaft of a five-axis numerical control machine tool through a tool holder 4, a mark on the visual target 3 represents the motion position of the main shaft of the machine tool, and preferably, the visual target 3 is manufactured through CNC machining so as to ensure the machining precision. Camera position appearance mounting 2 is the high accuracy frock of design processing, including magnetic switch base 2.1 and the support 2.2 that is connected, realizes through magnetic switch base 21 with quick assembly disassembly of lathe revolving stage 5, support 22 is fixed in the top of magnetic switch base 21, monocular camera 1 and support 22 fixed connection guarantee through mechanical cooperation structure that monocular camera 1 vertically gathers the sequence image that marks C on visual target 3. The monocular camera 1 is also provided with an annular uniform brightness forward illumination LED light source to ensure high uniformity and high stability of imaging. Referring to fig. 2 (b), when the geometric error measurement of the a axis is performed, the monocular camera 1 is changed from the vertical installation to the horizontal installation, and the mark a on the side of the visual target 3 is recognized, compared with the C axis.
Because the visual target 3 is manufactured by CNC machining and is connected with the machine tool spindle in a high-precision mode through the cutter handle, the pose error of the visual target 3 can be almost ignored, and therefore the pose deviation of the monocular camera installation, namely the included angle between the camera coordinate system and the machine tool spindle coordinate system, is mainly considered in the method.
In some embodiments, taking the C-axis measurement as an example, the pose deviation of the camera installation is as shown in fig. 4, assuming the camera coordinate system (x)v,yv,zv) And machine tool principal axis coordinate system (x)s,ys,zs) The included angle therebetween is theta. The measuring steps are as follows: and controlling the machine tool to move for a plurality of times at equal intervals along a certain axial direction of the translational shaft (such as C-axis measurement, X/Y direction, such as A-axis measurement and Y/Z direction), acquiring a visual target sequence image by using a monocular camera, calculating the movement displacement of the visual target in a camera coordinate system according to the image, and performing least square normal fitting to obtain an included angle theta.
Since the accuracy of the deviation of the installation error of the visual target in the XY direction is less than 0.02mm, but there is a significant influence on the measurement of the geometric error of the C axis, the installation error (Δ x, Δ y) of the visual target is corrected first.
In some embodiments, referring to fig. 5, the axes of the machine tool are controlled to be stationary, so that the main shaft starts to perform circular motion stopped at equal intervals from the 0 position (i.e., at S0 ° in fig. 5), the main shaft is paused for 30 ° and is imaged by shooting with a monocular camera, 12 images in the range of 0-330 ° are acquired, the central points of the 12 images are acquired, and least square circle fitting is performed on the errors to acquire the installation errors Δ x, Δ y of the visual target.
In some embodiments, the geometric error of the C-axis is measured specifically according to the following steps:
and installing a monocular vision measuring module according to the measuring requirements, and carrying out high-precision focusing on the monocular camera. And randomly selecting two machine tool program coordinates of the machine tool in the machining range according to the stroke range of the machine tool. Recording the current machine tool program coordinate (x) of the numerical control systemc1,yc1,zc1) Starting a machine tool RTCP state, controlling an A axis to be fixed, controlling an X axis, a Y axis, a Z axis and a C axis to carry out RTCP motion, controlling a C axis to carry out 0-360-degree equal interval stop motion, pausing once every 30 degrees, controlling a monocular camera to image to form a corresponding mark C sequence image, and calculating the three-dimensional coordinate deviation of the visual target after the ith pause of the first machine tool program coordinate into
Figure BDA0003337981000000071
At a second machine program coordinate (x)c2,yc2,zc2) Repeating the above steps, and recording the program coordinates (x) of the second machine toolc2,yc2,zc2) After each pause the three-dimensional coordinate deviation of the visual target
Figure BDA0003337981000000072
The C-axis geometric error is calculated according to the following formula, wherein the error delta is calculated according to the actual geometric error result of the machine toolzcHas the least influence on the C axis and is deltazcThe remaining 5 PDGES items on the C-axis are solved for 0. Since the PDGES changes along with the position of the angle term, in order to better describe the geometric error component, the working stroke of 0-360 degrees of the C axis is subdivided into 12 parts, each part is 30 degrees, and the PDGES at the position is obtained by solving the equation each time.
Figure BDA0003337981000000073
Wherein, deltaxci,δyciThe translation error along the x and y axes at the i-th stop of the C-axis motion, θxci,θyci,θzciThe rotation errors along the x, y, z axes at the i-th stop of the C-axis motion, respectively.
In some embodiments, referring to fig. 6, three-dimensional coordinate deviation measurement of a visual target is performed by a monocular camera equipped with a low distortion micro lens (where the control stroke is at 0.1mm, the accuracy is at 2um), including:
controlling a monocular camera provided with a low-distortion microscope lens to acquire a full-field-depth image sequence, performing definition calculation on the acquired panoramic depth image sequence by using a Brenner function, acquiring a definition-image sequence curve, and fitting a definition z-direction displacement function; controlling a monocular camera provided with a low-distortion microscope lens to image at the optimal definition position, performing sub-pixel identification on a mark characteristic point (namely a characteristic point of a mark C) of a visual target, and calibrating the pixel distance and the real displacement; and acquiring an image sequence in the measuring process, and realizing the three-dimensional coordinate deviation measurement of the visual target.
In some embodiments, the geometric error of the a-axis is measured as follows:
the A-axis RTCP movement needs to accurately measure the cutter length of the visual target, and the distance from the end surface of the machine tool spindle to the mark center is defined as the cutter length of the visual target, as shown in FIG. 7. Because the center of the visual target is eccentric to the center of the main shaft in the Y direction of the machine tool after being installed, the eccentric result is less than 0.02mm, and the result needs to be measured accurately. Writing a visual target cutter length and the Y-direction offset of the cutter in the cutter length setting of the numerical control system;
the monocular vision measuring module is installed according to the scheme shown in fig. 2 (b), and the monocular camera is focused with high precision. And randomly selecting two machine tool program coordinates of the machine tool in the machining range according to the stroke range of the machine tool. Recording the current machine tool program coordinate (x) of the numerical control systema1,ya1,za1) Starting a machine tool RTCP state, controlling a C axis to be fixed, controlling an X axis, a Y axis, a Z axis and an A axis to carry out RTCP motion, controlling the A axis to carry out stop motion at equal intervals of-60 degrees, pausing once every 10 degrees, controlling a monocular camera to image to form a corresponding mark A sequence image, and calculating the three-dimensional coordinate deviation of the visual target after the ith pause of the first machine tool program coordinate
Figure BDA0003337981000000081
(the three-dimensional coordinate deviation measurement process is referred to as a three-dimensional coordinate deviation measurement process in the C-axis). Repeating the above steps at a second machine program coordinate, recording the second machine program coordinate (x)a2,ya2,za2) And three-dimensional coordinate deviation of corresponding visual target
Figure BDA0003337981000000082
The geometric error of the A axis is calculated according to the following formula, wherein the error delta is calculated according to the actual geometric error result of the machine toolxaHas the least influence on the A axis and is deltaaxThe remaining 5 items PDGES on the a axis are solved for 0:
Figure BDA0003337981000000083
wherein, deltayai,δzaiThe translation error along the y and z axes, theta, at the i-th stop of the A-axis motionxai,θyai,θzaiThe rotation errors along the x, y, z axes at the ith stop of the a axis motion, respectively.
The principle of the machine tool rotation axis geometric error identification method provided by the embodiment of the first aspect of the disclosure is as follows:
when the A axis is kept still and C axis RTCP movement is carried out, the influence of geometric error of the A axis does not need to be considered, the space error of the machine tool is calculated by the following formula, wherein E represents the space error of the RTCP movement of the five-axis machine tool,CEArepresenting the geometric error matrix of the C-axis relative to the A-axis, I4*4Is an identity matrix of order 4, deltax,δy,δzThe components of the spatial error E along the x, y, z axes, PtIs the position of the tool tip point in the workpiece coordinate system, Ptx,Pty,PtzThe components of the position of the tool tip point in the workpiece coordinate system along the x, y, z axes, respectively.
Figure BDA0003337981000000091
When the A-axis RTCP motion is performed while keeping the C-axis stillThen, without considering the influence of the geometric error of the C axis, the spatial error of the machine tool is calculated by the following formula, where E represents the spatial error of the RTCP motion of the five-axis machine tool,AEOrepresenting the geometric error matrix of the A-axis relative to the machine coordinate system, I4*4Is an identity matrix of order 4.
Figure BDA0003337981000000092
For the above equation, there are 6 unknowns, depending on the actual geometric error result of the machine, where the error δzc,δxaHas the minimum influence on the geometric errors of the C axis and the A axis respectively, and is deltazc＝0，δxaThe remaining 5 PDGES items are solved for the C and a axes 0.
And 6 equations can be obtained by measuring two program coordinate points of the machine tool, and the solution of 5 unknowns is completed. The unknown number is compensated to a numerical control system, and the measurement of the geometric error of the rotating shaft can be completed.
The principle of measuring three-dimensional positions with a monocular camera is described below:
1) measurement of displacement in XY directions
And selecting a monocular camera to match with the microspur lens to measure the visual target, and accurately positioning the position of the machine tool. At present, an identification method for a visual target corner is very mature, and by taking a checkerboard as an example, an opencv identification scheme is adopted, so that a precise position of a checkerboard corner at a subpixel level can be quickly found.
By the above method, the pixel coordinates of a single corner point can be theoretically accurate to within ± 0.2 pixel. The uncertainty of the measurement of the points in the checkerboard can be reduced by averaging the 9 x 9 checkerboard corner points.
In a specific example of the present disclosure, the image pixel accuracy is determined according to the camera and lens parameters, for example, the monocular camera selected in this embodiment is a 500-thousand black and white industrial camera, the pixel is 3.45 × 3.45um, the lens selects a 0-distortion macro measurement lens, the magnification is 3 times, the imaging field of view is 2.80 × 2.40(mmxmm), and the lens distortion is less than 0.01 (%). The conversion relationship between the pixel and the real displacement is as follows:
1pixel＝2400um/2048＝1.1719um
and determining the accuracy of the measured data through actual measurement result calibration.
2) Z-direction displacement measurement
The principle of the monocular camera for resolving the Z-axis distance is similar to the principle of automatic focusing, and the small displacement of the checkerboard plane in the Z axis can cause the rapid change of the information quantity in the picture. Therefore, the information content contained in the picture is evaluated through the definition evaluation function, the defocusing amount of the targeted checkerboard is deduced, and the Z-direction change of the checkerboard is further judged. The method is used for accurately judging the key of Z-axis coordinate change, namely selecting a focus evaluation function and accurately calibrating the change of Z-axis defocusing amount according to the focus evaluation function.
Selecting a Brenner focusing evaluation function as a Z-direction identification focusing evaluation function, wherein the function has the advantages of short algorithm time consumption, strong noise interference resistance and strong focusing evaluation capability, and the function expression is as follows: wherein f (x, y) is the gray value corresponding to the x-th row and the y-th column of the camera, and G reflects the definition degree of the current image.
Figure BDA0003337981000000101
And evaluating the acquired image sequence by adopting a Brenner focusing evaluation function, and normalizing the focusing evaluation result to facilitate comparison, wherein the normalization processing formula is as follows. Wherein G ismaxFor maximum sharpness of the current series of images, GkAs a result of the sharpness after the kth measurement, fkIs the result of normalization of the k-th measurement.
Figure BDA0003337981000000102
And fitting the focus evaluation result by adopting a polynomial fitting mode, fitting a focus function and a Z-axis defocusing amount change parameter by taking a quadratic function as a model according to the shape of a Z-axis focus fitting function, wherein the formula is as follows. Wherein a, b, c are fitsCoefficients of a quadratic function model, zfIs GmaxThe corresponding Z-axis coordinate, namely the Z-axis coordinate where the clearest image is located. z is a radical ofkThe corresponding Z-axis coordinate is measured for the kth time.
fk＝a(zk-zf)2+b|zk-zf|+c
I.e. according to fkAnd evaluating the defocusing amount in the Z direction according to the measurement result to acquire accurate Z-direction variation.
The device for identifying the geometric error of the rotating shaft of the machine tool provided by the embodiment of the second aspect of the disclosure comprises:
the monocular vision measuring module comprises a monocular camera provided with a low-distortion microscope lens, a camera pose fixing part and a vision target; the surface of the visual target is provided with a calibration plate, the visual target is tightly connected with a machine tool spindle through a machine tool handle, and the characteristics on the visual target represent the motion position of the machine tool spindle; the camera pose fixing piece comprises a magnetic switch base and a support which are connected, the magnetic switch base is fixedly connected with a machine tool rotary table, and the monocular camera is connected with the magnetic switch base through the support;
the installation error calibration module is used for respectively calibrating the installation errors of the monocular camera and the visual target;
the C-axis geometric error measuring module is used for randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range according to the stroke range of the machine tool, controlling the A axis to be still at the position of A0 degrees at each machine tool program coordinate, performing RTCP motion on the C axis, stopping at equal intervals in the motion process, and acquiring the image of the mark C on the visual target by using the monocular camera at each stopping position to form a corresponding mark C sequence image; obtaining three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark C sequence images in each measurement process, and calculating the geometric error of the C axis; and
the A-axis geometric error measuring module is used for measuring the cutter length and the Y offset of the visual target, the cutter length of the visual target is the distance from the end surface of the machine tool spindle to the center of the mark A or the mark B, and the Y offset of the visual target is the Y-direction component of the center deviation between the mark A and the machine tool spindle after the visual target is installed; according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the C axis to be still at a C0-degree position at each machine tool program coordinate, performing RTCP (real-time transport control protocol) motion on the A axis, stopping at equal intervals in the motion process, and acquiring the image of the mark A on the visual target by using the monocular camera at each stopping position to form a corresponding mark A sequence image; and obtaining the three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark A sequence images of each measurement process, so as to calculate the geometric error of the A axis.
In order to implement the above embodiments, the present disclosure further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor, and is used to execute the machine tool rotation axis geometric error identification method of the above embodiments.
Referring now to FIG. 8, a block diagram of an electronic device 100 suitable for use in implementing embodiments of the present disclosure is shown. It should be noted that the electronic device 100 in the embodiment of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet), a PMP (portable multimedia player), a vehicle-mounted terminal (e.g., a car navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, a server, and the like. The electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 8, the electronic device 100 may include a processing means (e.g., a central processing unit, a graphic processor, etc.) 101 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)102 or a program loaded from a storage means 108 into a Random Access Memory (RAM) 103. In the RAM103, various programs and data necessary for the operation of the electronic apparatus 100 are also stored. The processing device 101, the ROM102, and the RAM103 are connected to each other via a bus 104. An input/output (I/O) interface 105 is also connected to bus 104.
Generally, the following devices may be connected to the I/O interface 105: input devices 106 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, etc.; an output device 107 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 108 including, for example, magnetic tape, hard disk, etc.; and a communication device 109. The communication means 109 may allow the electronic device 100 to communicate wirelessly or by wire with other devices to exchange data. While fig. 8 illustrates an electronic device 100 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, the present embodiments include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 109, or installed from the storage means 108, or installed from the ROM 102. The computer program, when executed by the processing device 101, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: respectively calibrating installation errors of a monocular camera which is arranged at the tail end of a cutter handle of the machine tool and is provided with a low-distortion microscope lens and a visual target which is arranged on a rotary table of the machine tool; identifying the geometric error of the C axis, comprising: randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range according to the stroke range of the machine tool, controlling an A axis to be still at an A0-degree position at each machine tool program coordinate, controlling a C axis to do RTCP motion, stopping at equal intervals in the motion process, and acquiring images of a mark C on a visual target by utilizing a monocular camera at each stopping position to form a corresponding mark C sequence image; obtaining three-dimensional coordinate deviation of the visual target of each machine tool program coordinate at each stop according to the mark C sequence image of each measurement process, and calculating the geometric error of the C axis; identifying the geometric error of the A axis, comprising: measuring the cutter length and Y offset of a visual target, wherein the cutter length of the visual target is the distance from the end surface of a machine tool spindle to the center of a mark A or a mark B, the Y offset of the visual target is the Y-direction component of the center deviation of the mark A and the machine tool spindle after the visual target is installed, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range according to the stroke range of the machine tool, controlling a C axis to be still at a C0-degree position at each machine tool program coordinate, controlling an A axis to do RTCP motion, stopping at equal intervals in the motion process, and collecting images of the mark A on the visual target by utilizing a monocular camera at each stopping position to form corresponding mark A sequence images; and obtaining the three-dimensional coordinate deviation of the visual target of the program coordinates of each machine tool at each stop according to the mark A sequence images of each measurement process, thereby calculating the geometric error of the A axis.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, python, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by a program instructing associated hardware to complete, and the developed program may be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (10)

1. A geometric error identification method for a machine tool rotating shaft is characterized by comprising the following steps:
respectively installing a visual target and a monocular camera provided with a low-distortion microscope lens at the tail end of a cutter handle of the machine tool and on a rotary table; the visual target is provided with a mark A, a mark B and a mark C which are mutually vertical and are respectively vertical to the axis A, the axis B and the axis C;
calibrating the installation errors of the monocular camera and the visual target respectively;
identifying the geometric error of the C axis, including:
according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the A axis to be still at the position of A0 degrees at each machine tool program coordinate, enabling the C axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring the image of the mark C on the visual target by using the monocular camera at each stopping position to form a corresponding mark C sequence image; obtaining three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark C sequence images in each measurement process, and calculating the geometric error of the C axis;
identifying the geometric error of the A axis, comprising:
measuring the cutter length and Y bias of the visual target, wherein the cutter length of the visual target is the distance from the end surface of the machine tool spindle to the center of the mark A or the mark B, and the Y bias of the visual target is the Y-direction component of the deviation between the mark A and the center of the machine tool spindle after the visual target is installed;
according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the C axis to be stationary at a C0-degree position at each machine tool program coordinate, enabling the A axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring images of the mark A on the visual target by using the monocular camera at each stopping position to form corresponding mark A sequence images; and obtaining the three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark A sequence images of each measurement process, so as to calculate the geometric error of the A axis.
2. The machine tool rotating shaft geometric error recognition method according to claim 1, wherein calibrating the installation error of the monocular camera comprises:
and controlling the machine tool to move for a plurality of times at equal intervals along the axis direction of the translational shaft, acquiring sequence images of the visual target by using the monocular camera, calculating the movement displacement of the visual target in a camera coordinate system according to the sequence images, and fitting to obtain an included angle between the camera coordinate system and a machine tool main shaft coordinate system to serve as the installation error of the monocular camera.
3. The machine tool rotating shaft geometric error identification method according to claim 2, wherein the fitting manner is least squares linear fitting.
4. The machine tool rotating shaft geometric error identification method according to claim 1, wherein calibrating the installation error of the visual target comprises:
and controlling each shaft of the machine tool to be immobile, enabling the main shaft of the machine tool to perform circular motion and stop at equal intervals, acquiring images of the visual target at each stopping position by using the monocular camera, acquiring the central point of each image, fitting, and acquiring the installation error of the visual target.
5. The machine tool rotating shaft geometric error identification method according to claim 4, wherein the fitting manner is least square circle fitting.
6. The machine tool rotating shaft geometric error recognition method according to claim 1, wherein the marks on the visual target are checkerboard, dot calibration board or two-dimensional code calibration board, and the monocular camera is used to perform three-dimensional coordinate deviation measurement on the visual target, and the method comprises:
controlling the monocular camera to obtain a full-depth-of-field image sequence, performing definition calculation on the full-depth-of-field image sequence by using a Brenner function, obtaining a definition-image sequence curve, and fitting a definition z-direction displacement function; controlling the monocular camera to image at the optimal definition position, performing sub-pixel identification on the mark characteristic point of the visual target, and calibrating the pixel distance and the real displacement; and acquiring an image sequence in the measuring process, and realizing the three-dimensional coordinate deviation measurement of the visual target.
7. The machine tool rotation axis geometric error recognition method according to claim 1,
selecting two machine tool program coordinates, and obtaining the geometric error of the C axis by using the following formula:
Figure FDA0003337980990000021
wherein (x)c1，yc1，zc1)，(xc2，yc2，zc2) For the selected two machine tool program coordinates;
Figure FDA0003337980990000022
for machine tool program coordinates (x)c1，yc1，zc1) Three-dimensional coordinates of the visual target at the i-th stopThe deviation is a function of the time of day,
Figure FDA0003337980990000023
for machine tool program coordinates (x)c2，yc2，zc2) A three-dimensional coordinate deviation of the visual target at the i-th stop; deltaxci，δyciThe translation error along the x and y axes, theta, respectively, at the i-th stop of the C-axis motionxci，θyci，θzciThe rotation errors along the x, y and z axes at the i-th stop of the C-axis motion are respectively.
8. The method according to claim 1, wherein two machine tool program coordinates are selected, and the geometric error of the a axis is obtained by using the following formula:
Figure FDA0003337980990000024
wherein (x)a1，ya1，za1)，(xa2，ya2，za2) For the selected two machine tool program coordinates;
Figure FDA0003337980990000031
for machine tool program coordinates (x)a1，ya1，za1) A three-dimensional coordinate deviation of the visual target at the i-th stop,
Figure FDA0003337980990000032
for machine tool program coordinates (x)a2，ya2，za2) A three-dimensional coordinate deviation of the visual target at the i-th stop; deltayai，δzaiThe translation error along the y and z axes, theta, at the i-th stop of the A-axis motionxai，θyai，θzaiThe rotation errors along the x, y, z axes at the ith stop of the a axis motion, respectively.
9. A machine tool rotation axis geometric error recognition apparatus, comprising:
the monocular vision measuring module comprises a monocular camera provided with a low-distortion microscope lens, a camera pose fixing part and a vision target; the visual target is provided with a mark A, a mark B and a mark C which are mutually vertical and are respectively vertical to the axis A, the axis B and the axis C, and the visual target is tightly connected with the main shaft of the machine tool through the handle of the machine tool; the monocular camera is fixedly connected with the machine tool rotary table through the camera pose fixing piece;
the installation error calibration module is used for respectively calibrating the installation errors of the monocular camera and the visual target;
the C-axis geometric error measuring module is used for randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range according to the stroke range of the machine tool, controlling the A axis to be still at the position of A0 degrees at each machine tool program coordinate, enabling the C axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring the image of the mark C on the visual target by utilizing the monocular camera at each stopping position to form a corresponding mark C sequence image; obtaining three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark C sequence images in each measurement process, and calculating the geometric error of the C axis; and
the A-axis geometric error measuring module is used for measuring the cutter length and the Y offset of the visual target, the cutter length of the visual target is the distance from the end surface of the machine tool spindle to the center of the mark A or the mark B, and the Y offset of the visual target is the Y-direction component of the center deviation between the mark A and the machine tool spindle after the visual target is installed; according to the stroke range of the machine tool, randomly selecting a plurality of machine tool program coordinates of the machine tool in a machining range, controlling the C axis to be stationary at a C0-degree position at each machine tool program coordinate, enabling the A axis to do nose point following movement, stopping at equal intervals in the movement process, and acquiring images of the mark A on the visual target by using the monocular camera at each stopping position to form corresponding mark A sequence images; and obtaining the three-dimensional coordinate deviation of the visual target at each stop of the machine tool program coordinates according to the mark A sequence images of each measurement process, so as to calculate the geometric error of the A axis.
10. A computer-readable storage medium storing computer instructions for causing a computer to execute the machine tool rotational axis geometric error identification method according to any one of claims 1 to 8.
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114770219A (en) * 2022-06-21 2022-07-22 歌尔股份有限公司 Method, device, equipment, storage medium and program product for automatically aligning workpiece
CN116661374A (en) * 2023-07-27 2023-08-29 泉州华中科技大学智能制造研究院 Shoe mold processing method and device based on three-axis linkage control and readable medium
CN116673792A (en) * 2023-08-04 2023-09-01 成都飞机工业（集团）有限责任公司 Machining center rotating shaft error source stripping feature and machining evaluation method
CN116728158A (en) * 2023-08-09 2023-09-12 成都飞机工业（集团）有限责任公司 Error detection result visualization method for five-axis machine tool R-test detection

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120212623A1 (en) * 2010-08-05 2012-08-23 Dong-Il Cho System and method of controlling vision device for tracking target based on motion commands
CN102699733A (en) * 2012-06-12 2012-10-03 大连理工大学 Method and device for measuring movement locus of automatic tool changing mechanical arm
JP2015182144A (en) * 2014-03-20 2015-10-22 キヤノン株式会社 Robot system and calibration method of robot system
CN105382631A (en) * 2015-12-15 2016-03-09 福建工程学院 Equipment and method for detecting error of rotating shaft of five-axis numerical control machine tool
CN205342667U (en) * 2015-12-15 2016-06-29 福建工程学院 Check out test set of five digit control machine tool rotation axis errors
US20170045877A1 (en) * 2015-02-12 2017-02-16 Glowforge, Inc. Visual preview for laser fabrication
CN106863014A (en) * 2017-02-24 2017-06-20 大连理工大学 A kind of five-axle number control machine tool linear axis geometric error detection method
CN107186548A (en) * 2017-06-08 2017-09-22 大连理工大学 A kind of five-axle number control machine tool gyroaxis geometric error detection method
CN107971831A (en) * 2017-11-07 2018-05-01 大连理工大学 Numerically-controlled machine tool high dynamic any profile errors monocular 6 DOF measuring method on a large scale
CN108620955A (en) * 2018-04-18 2018-10-09 大连理工大学 Machine tool rotary axis error based on monocular vision measures and discrimination method
US20200061769A1 (en) * 2017-11-07 2020-02-27 Dalian University Of Technology Monocular vision six-dimensional measurement method for high-dynamic large-range arbitrary contouring error of cnc machine tool
CN112276674A (en) * 2020-10-13 2021-01-29 上海交通大学 Precision measurement method and system for geometric motion error of rotating shaft of multi-axis numerical control machine tool

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120212623A1 (en) * 2010-08-05 2012-08-23 Dong-Il Cho System and method of controlling vision device for tracking target based on motion commands
CN102699733A (en) * 2012-06-12 2012-10-03 大连理工大学 Method and device for measuring movement locus of automatic tool changing mechanical arm
JP2015182144A (en) * 2014-03-20 2015-10-22 キヤノン株式会社 Robot system and calibration method of robot system
US20170045877A1 (en) * 2015-02-12 2017-02-16 Glowforge, Inc. Visual preview for laser fabrication
CN105382631A (en) * 2015-12-15 2016-03-09 福建工程学院 Equipment and method for detecting error of rotating shaft of five-axis numerical control machine tool
CN205342667U (en) * 2015-12-15 2016-06-29 福建工程学院 Check out test set of five digit control machine tool rotation axis errors
CN106863014A (en) * 2017-02-24 2017-06-20 大连理工大学 A kind of five-axle number control machine tool linear axis geometric error detection method
CN107186548A (en) * 2017-06-08 2017-09-22 大连理工大学 A kind of five-axle number control machine tool gyroaxis geometric error detection method
CN107971831A (en) * 2017-11-07 2018-05-01 大连理工大学 Numerically-controlled machine tool high dynamic any profile errors monocular 6 DOF measuring method on a large scale
US20200061769A1 (en) * 2017-11-07 2020-02-27 Dalian University Of Technology Monocular vision six-dimensional measurement method for high-dynamic large-range arbitrary contouring error of cnc machine tool
CN108620955A (en) * 2018-04-18 2018-10-09 大连理工大学 Machine tool rotary axis error based on monocular vision measures and discrimination method
CN112276674A (en) * 2020-10-13 2021-01-29 上海交通大学 Precision measurement method and system for geometric motion error of rotating shaft of multi-axis numerical control machine tool

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
孙惠娟等: "基于机器视觉的五坐标机床旋转轴误差检测方法", 《农业机械学报》 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114770219A (en) * 2022-06-21 2022-07-22 歌尔股份有限公司 Method, device, equipment, storage medium and program product for automatically aligning workpiece
CN116661374A (en) * 2023-07-27 2023-08-29 泉州华中科技大学智能制造研究院 Shoe mold processing method and device based on three-axis linkage control and readable medium
CN116661374B (en) * 2023-07-27 2023-10-27 泉州华中科技大学智能制造研究院 Shoe mold processing method and device based on three-axis linkage control and readable medium
CN116673792A (en) * 2023-08-04 2023-09-01 成都飞机工业（集团）有限责任公司 Machining center rotating shaft error source stripping feature and machining evaluation method
CN116673792B (en) * 2023-08-04 2023-11-10 成都飞机工业（集团）有限责任公司 Machining center rotating shaft error source stripping feature and machining evaluation method
CN116728158A (en) * 2023-08-09 2023-09-12 成都飞机工业（集团）有限责任公司 Error detection result visualization method for five-axis machine tool R-test detection
CN116728158B (en) * 2023-08-09 2023-12-08 成都飞机工业（集团）有限责任公司 Error detection result visualization method for five-axis machine tool R-test detection

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