Method and apparatus for surface analysis of a workpiece

Abstract

Method for surface analysis of a workpiece, which during machining is moved along a trajectory with a tool and in the course of which at least one operating parameter is detected in the form of discrete values, wherein the trajectory is subdivided into a first sub-section and at least one second sub-section, which have a course parallel to one another, and the discrete values of the at least one operating parameter are explicitly assigned to predetermined groups along the first sub-section and the at least one second sub-section, then it is checked whether the first sub-section is at least partially contiguous with the at least one second sub-section, but does not belong to the groups of the at least one second sub-section, and the first sub-section is classified as a surface anomaly of the workpiece.

Description

TECHNICAL FIELD

[0001] The invention relates to a method and a device for surface analysis of a workpiece, which is moved along a trajectory during machining with a tool and at least one operating parameter is detected in the form of discrete values in the process. BACKGROUND

[0002] In computer-controlled machining machines with tools, for example CNC milling machines, it is often necessary to analyze the surface quality achieved by the manufactured workpiece.

[0003] This is traditionally carried out optically after the manufacture of the workpiece, but this can be complex and expensive, for example due to time-consuming processing.

[0004] A method is shown in the publication EP 3 623 888 A1, which detects the temporal course of the measured actual tool position during the CNC manufacture of a workpiece, analyzes the deviation from the ideal tool position and from this infers the surface quality. SUMMARY

[0005] The task of the invention is to carry out an accurate surface analysis of a workpiece and to automatically, reliably and quickly identify surface abnormalities caused by the manufacturing process in the process without the need for visual inspection of the workpiece.

[0006] The task of the invention is solved by a method of the type mentioned at the outset, wherein the trajectory is subdivided into a first sub-section and at least one second sub-section, which have a course that is preferably partially parallel to one another,

[0007] and the discrete values of the at least one operating parameter along the first sub-section and the at least one second sub-section are explicitly assigned to predetermined groups,

[0008] it is then checked whether the first sub-section is at least partially contiguous with the at least one second sub-section, but does not belong to the groups of the at least one second sub-section, and the first sub-section is classified as a surface abnormality of the workpiece.

[0009] What is achieved by the invention is that an automatic, fast and accurate surface analysis is carried out by identifying surface abnormalities.

[0010] Alternatively, the manufacture of the workpiece can be simulated, i.e. a virtual workpiece can be created and a surface analysis can be carried out virtually before the physical manufacture is carried out. Problems can thus be identified in time and the manufacture can be corrected accordingly.

[0011] The method provides that the machining process is recorded, for example electronically, by the computer-controlled machine and the abnormality recognition is then carried out on the basis of the movement curve of the tool and the associated detected operating parameters.

[0012] The first sub-portion and the at least one second sub-portion are subsets of the trajectory.

[0013] The data points existing in the form of the values of the operating parameter reflect, for example, the movement of the tool along the trajectory, wherein the trajectory describes a spatial or temporal sequence of the detected data points.

[0014] In other words, the sub-portion is determined by the course of the trajectory, i.e. by the temporal sequence of the individual data points in the form of the values of the operating parameter which jointly form the trajectory. The sub-portion is a subset of the trajectory.

[0015] The sub-portion contains a sequence of data points which are temporally or spatially consecutive to one another, irrespective of their respective values of the operating parameter. The data points are thus located within the sub-portion.

[0016] On the other hand, the group is determined by the values of the individual data points which form the trajectory and can be set, for example, by means of a threshold value which is assigned to the respective group.

[0017] The group comprises data points having values of the operating parameter which lie within the same value range which is assigned to the respective group, but independently of the assignment to the sub-portion. A predetermined value range is thus assigned to each group, to which the data points are in turn assigned.

[0018] The invention assigns data points of the trajectory to groups and sub- portions, then determines the relationship between the respective group and the respective sub-portion and derives therefrom that an anomaly exists if the respective data points belong to different groups, i.e. deviate from one another by more than a predefined limit value.

[0019] In other words, for two data points of the trajectory, it is determined:

[0020] • whether the sequence of data points is not consecutive to one another, i.e. is assigned to separate sub- portions, but nevertheless has at least a partially parallel course of the respective sub-portion, and

[0021] • whether the absolute values of the data points differ by at least the value of the value range of one group.

[0022] In an extension of the invention, it is provided to check whether the first sub-portion is at least partially contiguous to at least two second sub- portions of the same group, but does not belong to the group of the at least two second sub- portions, and to classify the first sub-portion as a surface anomaly of the workpiece.

[0023] The reliability of the anomaly recognition, i.e. for example the probability of correct detection, can thereby be further improved.

[0024] This is achieved by an additional check as to whether the sub- portions are directly contiguous to one another in space, i.e. adjacent.

[0025] In one expansion of the application it is provided that the tool has a machining width and that the at least one operating parameter is detected at support points along the trajectory, which have a distance of at most half the machining width from one another.

[0026] Thereby a high accuracy of the method is achieved.

[0027] In one expansion of the application it is provided that a minimum value and a maximum value are determined from the at least one operating parameter along the trajectory, and that a speed range is determined from the difference between the minimum value and the maximum value, in which speed range the value ranges of the groups, preferably adjoining one another, lie.

[0028] Thereby a simple group definition is achieved.

[0029] In one expansion of the application it is provided that an average value is determined from the at least one operating parameter, from which average value a speed range is determined, in which speed range the value ranges of the groups, preferably adjoining one another, lie.

[0030] Thereby a reliable anomaly recognition is achieved.

[0031] In one expansion of the application it is provided that the at least one operating parameter is assigned to the predetermined groups repeatedly and that the groups are reset in the process.

[0032] Thereby the recognition rate, i.e. the probability of correct classification, for example, of the method can be improved.

[0033] The anomaly should occur independently of the grouping, i.e. independently of the selection of the predetermined value range.

[0034] In one expansion of the application it is provided that a linear distribution is used as a basis for the initial setting of the groups, and that a non-linear distribution is applied to the resetting of the groups, preferably in the directly following setting.

[0035] Thereby the recognition rate of the method can be further improved.

[0036] In one expansion of the application it is provided that at least two operating parameters are detected and that different operating parameters from the at least two operating parameters are applied to the resetting of the groups.

[0037] Thereby the recognition rate of the method can be further improved.

[0038] In one expansion of the application it is provided that the operating parameter is the machining speed, the machining temperature at the tool or the current consumption of the machine.

[0039] Thereby a criterion is provided in a simple manner, which can be used as a basis for further analysis.

[0040] In one expansion of the application it is provided that the method is executed after the physical manufacture of the workpiece.

[0041] Thereby the surface quality can be analyzed without a physical inspection of the workpiece.

[0042] In one expansion of the application it is provided that the method is executed by a computing device after the workpiece has been manufactured in simulation. Thereby it is possible to avoid time-consuming handling of the workpiece during the inspection.

[0043] Thereby the surface quality can be analyzed before the workpiece is physically manufactured. Thereby it is also possible to advantageously and simply perform an adaptation of the manufacturing process.

[0044] The object of the application is also achieved by a computing device for surface analysis of a workpiece, the computing device having a memory, the computing device being set up to move the workpiece along a trajectory during the machining of the workpiece with a tool and to detect at least one operating parameter during this process by means of at least one sensor device, characterized in that the computing device is set up to execute the method according to the application. BRIEF DESCRIPTION OF DRAWINGS

[0045] The application is explained in more detail below on the basis of the embodiments shown in the drawings. In the drawings:

[0046] Figure 1 An embodiment of a machined workpiece and a tool trajectory is shown,

[0047] Figures 2-3 An enlarged section of Figure 1 is shown,

[0048] Figures 4-9 A diagram showing the trajectory of Figure 2 with grouping is shown,

[0049] Figure 10 An enlarged section of Figure 1 is shown, with support points of operating parameters,

[0050] Figure 11 An embodiment of the method according to the application is shown in the form of a flowchart. DETAILED DESCRIPTION

[0051] Figure 1 An embodiment of a machined workpiece 1 is shown in a top view, the workpiece being machined by a computer-controlled machine, such as a CNC milling machine, with a tool 10 in the form of a milling cutter.

[0052] The workpiece 1 has a circular surface which is machined with a milling cutter having a three-axis kinematics.

[0053] In this example, the machining is carried out by means of a meandering milling using a milling tool 10 having a diameter 11 of 0.2 mm and an advance speed 12 of up to 4700 mm / min.

[0054] In the course of this manufacturing plan, a trajectory 20 for the machining by means of the milling tool 10 is defined for the workpiece 1.

[0055] Although a constant speed can be set during planning, deviations can occur, for example due to unfavorable runtime behavior of the controller.

[0056] Here, the movement of the workpiece 1 in the machine and its coordinates as well as the machining speed are pre-defined.

[0057] The milling machine is thus now set to move the workpiece 1 along the trajectory 20 during machining by the milling tool.

[0058] During the manufacturing process, one or more runtime parameters 12, such as the machining speed, the machining temperature at the tool 10 or the current consumption of the machine, are detected by corresponding sensor devices, respectively.

[0059] A computing device having a memory is now used in order to carry out a surface analysis of the workpiece 1 after machining by the computer-controlled machine having the tool.

[0060] Figure 2 and Figure 3 An enlarged section of Figure 1 is shown.

[0061] The trajectory 20 is subdivided into sub-sections 21-24 having a course parallel to one another.

[0062] The course can be, for example, straight or curved, as in a turning curve of the tool 10 for removing material on the workpiece 1 surface by surface.

[0063] The values of the detected runtime parameter 12, here the advance speed, are then assigned to the predefined groups A-D along the sub-sections 21-24.

[0064] Figures 4 to 9 A trajectory 20 with sub-sections 21-24 from Figure 2 is shown, which has the groups A-D for the pre-defined value ranges of the runtime parameter 12.

[0065] For the groups, groups are defined to which the respective runtime parameter 12 can be assigned based on its value.

[0066] The determination of these groups can be carried out, for example, in such a way that a minimum value and a maximum value are determined from the runtime parameter 12 along the trajectory 20.

[0067] The speed range can then be determined from the difference between the maximum and minimum values, the value ranges of the groups A-D lying within this speed range.

[0068] In the simplest case, the groups A-D can abut one another, but can also provide a gap for known values that should not be included, for example in the case of a change in position during the operation of the CNC machine or in the case of a change in configuration, for example when the milling tool is idling.

[0069] Alternatively, the average value can also be determined from the operating parameters 12.

[0070] From this average value, the speed range can be set for the value ranges of the groups A-D of the adjacent groups, for example on the basis of a statistical distribution function, said value ranges not necessarily having the same size.

[0071] Combinations of the mentioned group definitions can also be applied.

[0072] In Figure 4 and Figure 5 subsections in the groups A-D can be seen.

[0073] The trajectory 20 is subdivided into a first subsection 22 and a second subsection 21 having a course parallel to one another.

[0074] The first subsection 22 and the second subsection 21 are a subset of the subsections 21-24.

[0075] The discrete values 31-33 (see Figure 10 ) of the operating parameters 12 along the first subsection and at least one second subsection 21-24 are explicitly assigned to the predetermined groups A-D.

[0076] It is then checked whether the first subsection 22 at least partially abuts the second subsection 21 but does not belong to the group B of the second subsection 21.

[0077] If so, the second subsection 21 is identified or classified as a surface anomaly of the workpiece 10.

[0078] Optionally, as a further refinement of the method, it can additionally be checked whether the first subsection 22 at least partially abuts two second subsections 21 and 23 of the same group B but does not belong to the group B of these two second subsections.

[0079] If so, the second subsection 21 is identified or classified as a surface anomaly of the workpiece 10.

[0080] In Figure 6 only those subsections are shown that are parallel to other regions of the trajectory 20 and in the same group A of the advance speed.

[0081] In Figure 7Only those sub-sections are shown which are parallel to further areas of the track 20 and in the same group B of advancement speeds.

[0082] In Figure 8 Only those sub-sections are shown which are parallel to further areas of the track 20 and in the group C of advancement speeds.

[0083] In Figure 9 Only those sub-sections are shown which are parallel to further areas of the track 20 and in the group D of advancement speeds.

[0084] Adjoining sub-sections 21-24 which do not belong to the same groups A-D are determined as surface anomalies of the workpiece 10.

[0085] Adjoining sub-sections 21-24 can exist, for example, when the respective sub-sections with the machining width 11 touch or at least partially overlap one another along the track 20, the sub-sections 21-24 thus directly abutting one another.

[0086] Such a track is provided, for example, when material is milled from a workpiece blank to manufacture a flat surface of the workpiece.

[0087] Alternatively, such a track can also be provided, for example, when material is milled from a workpiece blank to manufacture parallel- extending grooves in the workpiece. Here, the parallel- extending grooves can also form adjoining sub-sections 21-24, even if further shaping of the workpiece takes place between the grooves.

[0088] Figure 10 An enlarged section of the Figure 1 is shown, with the support points of the detection positions of the operating parameters 12.

[0089] The sub-sections of the track 20 extend parallel to one another at a distance 25.

[0090] In this example, the distance 25 is chosen such that the milling paths with the machining width 11 overlap, thereby ensuring complete removal of material.

[0091] The choice of the support points is mostly determined by the sampling rate of the detection system of the operating parameters 12.

[0092] It is apparent that, for example, the possible feed speed of the milling tool 10 must be taken into account here.

[0093] The support points for detecting the operating parameters 12 result in corresponding values 31-33.

[0094] The choice of the support points can be made, for example, in such a way that the operating parameters 12 are detected at the support points along the track 20, and the support points along the track 20 have a support point distance 26 of at most half the machining width 11 from one another.

[0095] The tool 10 mostly determines the machining width 11 by the diameter of the milling cutter.

[0096] Figure 11 An embodiment of the method according to the application is shown in the form of a flow chart.

[0097] After the start 100, the workpiece 1 is manufactured according to a manufacturing plan or also only simulated.

[0098] Here, the respective position of the milling cutter 10 and the milling cutter speed 12 are detected along the trajectory 20.

[0099] The manufacturing data of the workpiece 1 can be stored, for example, in a log file.

[0100] The manufacturing data are then analyzed.

[0101] Here, the trajectory 20 is subdivided in step 120 into sub-portions 21-24, which have a slightly curved course parallel to one another.

[0102] Groups are then defined in step 130, and the values of the operating parameters 12 detected along the sub-portions 21-24 are assigned to the predefined groups A-D in step 140.

[0103] It is then checked 150 whether an anomaly exists.

[0104] The anomaly check 150 checks whether the first sub-portion 22 at least partially adjoins at least one second sub-portion 21 but does not belong to the group B of the at least one second sub-portion 21.

[0105] Optionally, it can be checked whether the first sub-portion 22 at least partially adjoins two or more second sub-portions 21 and 23 of the same group B but does not belong to the group B of these second sub-portions.

[0106] If this is the case, the first sub-portion 22 is identified or classified as a surface anomaly of the workpiece 10.

[0107] If the check 150 indicates that no anomaly is identified, the analysis can now optionally be repeated in step 151 or ended by step 160.

[0108] The assignment of the operating parameters 12 to the predefined groups A-D can be performed repeatedly, wherein the groups are reset.

[0109] Here, as a criterion for the repetition, it can be determined that at least a predetermined number of the identified surface anomalies of the workpiece 10 are recognized, or until a predetermined number of the reset of the groups A-D is reached.

[0110] Linear distributions can be used as a basis for the initial setting of the groups A-D, while non-linear distributions can be applied to the re-setting of the groups A-D, for example in the directly following setting.

[0111] Two or more operating parameters 11 can also be detected, and different operating parameters can be applied to the re-setting of the groups A-D, respectively.

[0112] List of reference signs:

[0113] 1 workpiece

[0114] 10 milling tool of the CNC machine

[0115] 11 machining width, diameter of the milling tool

[0116] 12 machining direction of the milling tool, movement direction, operating parameter

[0117] 20 trajectory, milling trajectory

[0118] 21-24 sub-sections

[0119] 25 track spacing

[0120] 26 support point spacing

[0121] 31-33 discrete values of operating parameters

[0122] 100 method start

[0123] 110 manufacturing a workpiece or carrying out a simulation and detecting the speed as an operating parameter in the process

[0124] 120 setting sub-sections

[0125] 130 defining groups

[0126] 140 assigning operating parameters or speeds to the groups

[0127] 150 checking for anomalies

[0128] 151 no anomalies identified

[0129] 152 anomalies identified

[0130] 160 method end

Claims

1. Method for surface analysis of a workpiece (1) which is moved along a trajectory (20) during machining with a tool (10) in the form of a milling cutter of a CNC milling machine and in the process of which at least one operating parameter (12) is detected in the form of discrete values (31-33), characterized in that subdividing the trajectory (20) into a first sub-portion and at least one second sub-portion (21-24) which have a course parallel to one another, and assigning the discrete values (31-33) of the at least one operating parameter (12) along the first sub-portion and the at least one second sub-portion (21-24) explicitly to predetermined groups (A-D), wherein a minimum value and a maximum value are determined from the at least one operating parameter (12) along the trajectory (20) and a speed range is determined from the difference between the minimum value and the maximum value, the value range of the groups (A-D) lying within the speed range, wherein the operating parameter (12) is a machining speed, a machining temperature at the tool (10) or a current consumption of the CNC milling machine, then checking whether the first sub-portion (22) is at least partially contiguous with the at least one second sub-portion (21) but does not belong to the group (B) of the at least one second sub-portion, and classifying the first sub-portion (22) as a surface anomaly of the workpiece (10).

2. Method according to claim 1, wherein it is checked whether the first sub-portion (22) is at least partially contiguous with at least two second sub-portions (21, 23) of the same group (B) but does not belong to the group (B) of the at least two second sub-portions, and the first sub-portion (22) is classified as a surface anomaly of the workpiece (10).

3. Method according to any of the preceding claims, wherein the tool (10) has a machining width (11) and the at least one operating parameter (12) is detected at support points along the trajectory (20) which have a distance of at most half the machining width (11) from one another.

4. Method according to any of claims 1 to 2, wherein the groups (A-D) are contiguous with one another.

5. Method according to any of claims 1 to 2, wherein an average value is determined from the at least one operating parameter (12), from which an average value range is determined, in which the value range of the groups (A-D) lies.

6. Method according to claim 5, wherein the groups (A-D) are contiguous with one another.

7. Method according to any of claims 1 to 2, wherein the assignment of the at least one operating parameter (12) to predetermined groups (A-D) is carried out repeatedly and in the process the groups are reset.

8. Method according to claim 7, wherein a linear distribution is used as a basis for the initial setting of the groups (A-D) and a non-linear distribution is applied to the resetting of the groups (A-D).

9. Method according to claim 8, wherein the resetting of the groups (A-D) is in the directly following setting.

10. The method according to claim 5, wherein at least two operating parameters (12) are detected and different operating parameters of the at least two operating parameters (12) are applied to the re-setting of the group (A-D).

11. The method according to any one of claims 1 to 2, wherein the method is performed after a physical manufacturing of the workpiece (10).

12. The method according to any one of claims 1 to 2, wherein the method is performed by a computing device after a simulated manufacturing of the workpiece (10).

13. A computing device for surface analysis of a workpiece (1) having a memory, the computing device being arranged to move the workpiece (1) along a trajectory (20) during machining of the workpiece (1) with a tool (10) in the form of a milling tool of a CNC milling machine, and to detect at least one operating parameter (12) by means of at least one sensor device in the process, characterized in that, The computing device is arranged to perform the method according to any one of the preceding claims.

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