METHOD, COMPUTER PROGRAM AND LASER CUTTING SYSTEM FOR SMART CORNER CUTTING

Abstract

In one aspect, the present invention relates to a computing unit (RE) for executing a conversion algorithm, having an interface (UI) for acquiring a first cutting parameter data set (1SP); and having a processor (P) which is designed to extract a movement profile object (bpo) and which is also designed to execute a conversion algorithm that is stored in a memory of the electronic computing unit (RE) so that it can be loaded and/or executed to calculate and provide the second cutting parameter data set (2SP) to the acquired first cutting parameter data set (1SP), wherein the second cutting parameter data set (2SP) is calculated as a function of the extracted movement profile object (bpo).

Claims

1-15. (canceled)

16. A computer-implemented method for calculating a second cutting parameter data set for controlling and/or regulating a laser cutting process for cutting metal sheets of a laser cutting machine during the laser cutting of components, having the following method steps, which are carried out on an electronic computing unit: acquisition of a first cutting parameter data set; extraction of a movement profile object with data relating to the movement to be performed by a laser cutting head and/or data relating to the geometry to be cut, in particular data on the curvature and/or radii of the contour to be cut; execution of a conversion algorithm during cutting to dynamically adjust the cutting parameters, said conversion algorithm is stored loadable and/or executable in a memory of the electronic computing unit, to calculate and provide the second cutting parameter data set from the acquired first cutting parameter data set by using transformation rules that are based on a function catalogue which can be stored in an external or internal memory, wherein the second cutting parameter data set is calculated as a function of the extracted movement profile object wherein the first cutting parameter data set and/or second cutting parameter data set comprises dynamic cutting parameters, namely in particular cutting speed, focus position, pulse pattern, nozzle distance, gas pressure, laser power, beam parameter product/BPP and/or focus diameter; wherein said conversion algorithm calculates a dedicated function for each of the dynamic cutting parameters from a set of functions stored in the memory.

17. The method according to claim 16, wherein the method further comprises: acquisition of a material property of the component to be cut, in particular a sheet metal thickness and/or a material type; wherein the conversion algorithm for calculating the second cutting parameter data set takes into account the acquired material property, in particular the sheet metal thickness and/or the material type.

18. The method according to claim 16, in which the movement profile object indicates a value for a speed, an acceleration and/or a jerk and/or a curvature for a point on a cutting geometry or a course of the aforementioned variables over time.

19. The method according to claim 18, in which the set of functions can be parametrised.

20. The method according to claim 16, in which the provided second cutting parameter data set is transmitted directly to a controller on the laser cutting machine for controlling and/or regulating the laser cutting process.

21. The method according to claim 16, in which the conversion algorithm is only executed when preconfigurable change conditions are met, in particular when the movement profile object exceeds or falls below predetermined limit values.

22. The method according to claim 16, in which the conversion algorithm is implemented as a linear or trigonometric function.

23. The method according to claim 16, in which the conversion algorithm calculates the second cutting parameter data set dynamically for each point or for sections of a trajectory.

24. The method according to claim 16, in which an acceleration and/or jerk profile is calculated that serves as an input variable in the conversion algorithm.

25. A computer program having computer program code for performing all method steps of claim 16 method when the computer program is executed on a computer, an electronic entity and/or a computing unit.

26. An electronic computing unit for calculating a second cutting parameter data set for controlling and/or regulating a laser cutting process for cutting metal sheets of a laser cutting machine during the laser cutting of components, having: an interface for acquiring a first cutting parameter data set; a processor that is designed to extract a movement profile object with data relating to the movement to be performed by a laser cutting head and/or data relating to the geometry to be cut, in particular data on the curvature and/or radii of the contour to be cut; to execute a conversion algorithm during cutting to adjust the cutting parameters, said conversion algorithm is stored loadable and/or executable in a memory of the electronic computing unit to calculate and provide the second cutting parameter data set from the acquired first cutting parameter data set by using transformation rules that are based on a function catalogue which can be stored in an external or internal memory, wherein the second cutting parameter data set is calculated as a function of the extracted motion profile object and to execute a conversion algorithm which calculates a dedicated function for each of the dynamic cutting parameters from a set of functions stored in the memory; wherein the first cutting parameter data set and/or second cutting parameter data set comprises dynamic cutting parameters, namely in particular cutting speed, focus position, pulse pattern, nozzle distance, gas pressure, laser power, beam parameter product/BPP and/or focus diameter.

27. A laser cutting system, having: an electronic computing unit according to the claim 26 and a laser cutting machine that is controlled and/or regulated by a controller.

28. The laser cutting system according to system claim 26, wherein the electronic computing unit is implemented on the controller.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0095] FIG. 1 shows a schematic overview of a laser cutting machine that is controlled by a computing unit;

[0096] FIG. 2 is a flow chart of a method for calculating the second cutting parameter set in different embodiments;

[0097] FIG. 3 is a schematic representation of an architecture according to a first preferred embodiment of the invention and

[0098] FIG. 4 is a schematic representation of an alternative architecture according to a second preferred embodiment of the invention;

[0099] FIG. 5 shows an example of a correction of the focus position that is linearly dependent on the acceleration as a cutting parameter;

[0100] FIG. 6 shows, in another example, an acceleration-dependent correction of the focus position as a cutting parameter with a sine function as the base and exponent and

[0101] FIG. 7 shows a further example of a speed-based correction of the gas pressure as a cutting parameter;

[0102] FIG. 8a shows a cutting result without correction of the cutting parameters according to the prior art and

[0103] FIG. 8b shows a cutting result with a correction of the cutting parameters according to the invention by using the calculation method and

[0104] FIG. 9 shows an example of a graphic representation of the speed-dependent change in the focus position.

DESCRIPTION OF ADVANTAGEOUS EMBODIMENTS IN CONNECTION WITH THE FIGURES

[0105] The invention relates to a computer-implemented method for correcting cutting parameters for a laser machine L, which is typically operated with a power of over 2 kW. It can be used in particular for cutting metal sheets and pipes.

[0106] The method according to the invention implements an intelligent conversion algorithm for correcting or adapting cutting parameters to increase quality, especially when cutting small radii and corners, in which the setpoint speed of the laser cutting head must be reduced so that sufficient cutting quality can be guaranteed.

[0107] The advantageous technical effect of the method according to the invention was tested in test series by the applicant. A workpiece WS is shown in FIG. 8A that has been cut with non-adapted or corrected cutting parameters, in particular a first cutting parameter data set 1SP. As can be seen in FIG. 8A, the cut has melting regions in the corners and radii as well as in the incision. In contrast thereto, the method according to the invention was used in FIG. 8B and the cutting parameters were corrected; the workpiece WS was cut with the second cutting parameter data set 2SP calculated by means of a conversion algorithm. As can be seen, the quality is also good in the corners and radii as well as in the first and last cut. According to the invention, this quality can be ensured with constant or even improved performance (time for cutting the parts).

[0108] FIG. 1 shows a laser cutting machine L with a nozzle D that is designed to cut, for example, a plate-shaped sheet metal or a metal tube, also called a workpiece WS. The specific structure of the laser machine L is not significant for the implementation of the present invention. Usually, a plurality of sensors, for example in the form of photodiodes 4, can be integrated into the laser head, for example to take pictures of the cutting gap to be able to assess the quality of the cutting result based thereon. The laser machine L can comprise a controller C (not shown in FIG. 1) that is designed to implement external instructions andpossibly parametrisedinstructions and to control or regulate the laser cutting process. In the present case, a computing unit RE can be designed to calculate and provide at least some of the external instructions and to transmit them to the controller C for execution. The computing unit RE is an electronic entity that is provided as a node in a network. It can be part of a cloud-based server, for example. The electronic computing unit RE (hereinafter also referred to as computing unit RE for short) comprises a processor P. As shown in more detail in FIG. 1, the computing unit RE comprises a processor P for executing procedures, functions and in particular a conversion algorithm. The computing unit RE is in data exchange with other entities. In particular, an external memory MEM can be provided, which the computing unit RE accesses to call up parameters for the parameterisation of functions for adapting the cutting parameters as well as the respective functions. The respectivepreferably parametrisedfunctions are then loaded onto the computing unit RE and are available there for execution. Furthermore, the computing unit RE is designed to receive additional data sets. The computing unit RE can thus comprise a user interface UI on which the user can make inputs. For example, a first cutting parameter data set 1SP can be acquired on the user interface UI. Alternatively, the first cutting parameter data set 1DS can also be read out from a memory (for example, a table-like data structure) as a standard parameter data set, for example. The computing unit RE can also be in data exchange with a further control unit CNC to receive, in particular, a cutting plan sp and/or cutting plan-related data. Cutting plan-related data are data that are either contained in the cutting plan sp or can be deduced therefrom. The cutting plan-related data include, for example, the feed rate, the acceleration, the curvature ratios of the geometry to be cut, etc.

[0109] In a first variant of the invention, the computing unit RE can be designed to extract or calculate a movement profile object bpo from the received data, in particular from the cutting plan sp and possibly standardised, preset cutting parameters. A value for the speed, acceleration and/or jerk (derivation over time) of the drive axes of the laser head for a specific position on the geometry (circumference of the part to be cut) can be stored in the motion profile object bpo. In the movement profile object bpo, a value for a curvature for a point on the cutting geometry can also be stored cumulatively or alternatively. In a variant, a course of the named variables (speed, acceleration, jerk, curvature) over time can also be stored in the movement profile object bpo.

[0110] In a second variant of the invention, the movement profile object bpo can already have been extracted on an entity external to the computing unit, for example on the CNC control. In this case, the movement profile object bpo need not be calculated on the computing unit RE, but can already be read in in processed form via an interface and processed directly.

[0111] After acquiring the first cutting parameter data set 1SP and the extracted movement profile object bpo, the computing unit RE can convert the first cutting parameter data set 1SP into the second cutting parameter data set 2SP using a conversion algorithm using the functions of the parametrised function catalogue. The second cutting parameter data set 2SP functions as a modified CNC code, so to speak, and is transmitted directly to the internal controller C of the laser cutting machine L for controlling the laser cutting machine L (or the axes/axis drives thereof). Thus, the laser cutting machine L is notas beforeoperated with the specifications of the CNC control, but with a modified code that comprises corrected setting values that are encoded in the second cutting parameter data set 2SP.

[0112] FIG. 2 shows a sequence of the calculation method according to the invention in different embodiments (represented in the figure by dotted circles).

[0113] After the start of the method, the first cutting parameter data set 1SP is acquired in step S1. In step S2, the movement profile object bpo is extracted. In a first variant of the invention, the conversion algorithm can then be carried out in step S4. The method can then be ended. In a second variant of the invention, a material property of the material to be cut can optionally be acquired in step S3. In this method step it can be specified, for example, how thick the material to be cut (for example sheet metal) is and what type of material it is (for example, aluminium or steel, etc.). These aforementioned variables for the material property can then be taken into account by the conversion algorithm for calculating the second cutting parameter data set 2SP. The corrected or adapted cutting parameter data set, namely the second cutting parameter data set 2SP, can thus be matched even better to the respective application.

[0114] In principle, the sequence of the method steps acquisition of the first cutting parameter data set S1, extraction S2 and acquisition of the material property S3 is not fixed and can also be varied so that the method steps can be carried out in a different sequence (for example S2, S3, S1) or even in parallel.

[0115] In a preferred embodiment, it is provided that the calculated second cutting parameter data set 2SP is transmitted directly and automatically in step S5 to the controller C of the laser cutting machine L for control and/or regulation. However, this step is optional and is therefore shown in dotted lines in FIG. 2. In a variant of the invention, however, it can be provided that the calculated second cutting parameter data set 2SP is fed to a validation process in that it is output on a user interface UI and, during validation, a validation signal is acquired on the user interface UI, which indicates the validation of the corrected cutting parameter data set. In this case, the second cutting parameter data set 2SP is only transmitted to the controller C after the validation signal has been acquired, so that the security of the correction method can be increased.

[0116] A possible structural design of the laser cutting system is shown in FIG. 3. In this variant, the electronic computing unit RE is connected to the laser cutting machine L as an external entity via a data connection. The computing unit RE can be deployed, for example, on a cloud-based server (cloud in FIG. 3) which is connected to the laser cutting machine L via an internet connection. In this respect, the embodiment shown in FIG. 3 agrees with that described in more detail in FIG. 1. The electronic computing unit RE serves, as described, to calculate the second cutting parameter data set 2SP, which is transmitted directly to the controller C of the laser cutting machine L via the data connection. In this case, the computing unit RE can be implemented, so to speak, between the CNC control CNC and the controller C internal to the laser machine. Alternatively, it is also possible to implement the computing unit RE on the control CNC.

[0117] In comparison to FIG. 3, FIG. 4 shows an alternative embodiment. In this case, the computing unit RE is installed directly on the controller C of the laser cutting machine L. The computing unit RE and/or the controller C can optionally be in data exchange with an external control CNC, in particular to receive control data.

[0118] As already mentioned above, the conversion algorithm is based on functions of the function catalogue. The functions can be linear or trigonometric. In other embodiments of the invention, other types of functions can be selected. For example, the conversion algorithm can determine the speed-dependent focus position using a sine function as the base and exponent .sub.z.sub.0=2 as follows:

[00008]$f^{z0}\left(x\right)={}_{z_0}^{v_c}{\sin \left(\frac{F-v_c}{F}2\right)}^2\left(v_{c}F\right).fwdarw.z_0^{*}=z_0+f^{z0}\left(x\right).$

[0119] For focus positions that are linearly dependent on the acceleration, the conversion algorithm can access the following function of the function catalogue:

.sup.z0(x)=.sub.z.sub.0.sup.A((A.sub.maxA.sub.min)A)(0A)(AA.sub.max)(A.sub.minA)+.sub.z.sub.0.sup.A(A.sub.maxA)(A.sub.minA).fwdarw.z.sub.0*=z.sub.0+.sup.z0(x), [0120] where A.sub.max the acceleration is up to that at which the changes should be applied. Higher accelerations do not lead to any additional change. A.sub.min indicates the acceleration from which the changes are to be applied, as shown in FIG. 5. Lower accelerations do not lead to any additional change. Example with

[00009]$A_{\max }=4\frac{m}{s^2}\mathrm{and}{A}_{\min }=0.4\frac{m}{s^2}.$

[0121] The linear relationship is shown graphically as an example in FIG. 5, where the acceleration on the abscissa and the adapted focus position on the ordinate .sup.z0(x) is shown.

[0122] For the acceleration-dependent correction of the focus position, the conversion algorithm can calculate, for example, using a sine function as the base and exponent .sub.z.sub.0=4 as follows:

[00010]$f^{z0}\left(x\right)={}_{z_0}^A\left(1-\frac{{\sin \left(A_{\max }-.Math.A.Math.\right)}^4}{\left(A_{\max }-A_{\min }\right)}\frac{}{2}\right)\left(0.Math.A.Math.\right)\left(.Math.A.Math.A_{\max }\right)\left(A_{\min }.Math.A.Math.\right)+{}_{z_0}^A\left(A_{\max }.Math.A.Math.\right)\left(A_{\min }.Math.A.Math.\right).fwdarw.z_0^{*}=z_0+f^{z0}\left(x\right).$

[0123] FIG. 6 shows an example of the speed-based adaptation of the focus position .sup.z0(x) with

[00011]$A_{\max }=4\frac{m}{s^2}\mathrm{and}{A}_{\min }=0.4\frac{m}{s^2}.$

In this example, 4 was selected as the exponent of the sine function; alternatively, a quadratic sine function can be used.

[0124] For the speed-dependent change in gas pressure, the conversion algorithm can calculate, for example, using a sine function as the base and exponent .sub.p.sub.H=3 as follows:

[00012]$f^{p_H}\left(x\right)={{}_{p_H}^{v_c}\left(\frac{F-v_c}{F}2\right)}^3\left(v_{c}F\right).fwdarw.p_H^{*}=p_H+f^{p_H}\left(x\right).$

[0125] An example is shown graphically in FIG. 7, wherein the cutting speed on the abscissa v.sub.c and the optimised or adapted focus position plotted on the ordinate as a function of the cutting speed.

[0126] Corresponding graphs result when the gas pressure is adjusted as a function of the acceleration or the speed by means of the conversion algorithm.

[0127] In further embodiments of the invention, more complex functions and combinations of speed, acceleration and curvature-dependent adjustments can be used:

[00013]$f^{z0}\left(x\right)={}_{z_0}^{v_c}{\sin \left(\frac{F-v_c}{F}2\right)}^2\left(v_{c}F\right)+{}_{z_0}^{}{\sin \left(\frac{F-v_c}{F}2\right)}^{12}\left({}_{\min }\right),$

[0128] where the radius of curvature can be read from the cutting plan sp. The exponent is given here as an example with 2 and 12. In principle, the exponents of the functions can be set differently depending on the material and depending on the parameter dependency. The exponent can therefore preferably be parametrised.

[0129] FIG. 9 shows again in which situations an adaptation or correction of the cutting parameters is to be carried out using the example of the focus position (also representing the other dynamic cutting parameters). The conversion algorithm can preferably scale depending on the material and sheet metal thickness. FIG. 9 shows that the focus position is corrected to the maximum when the ratio of the current feed rate to the maximum feed rate is zero or very low, that is, when a trajectory section can be moved much slower than the maximum possible due to the feed rate. If the cutting speed v.sub.c corresponds to the maximum feed rate v.sub.c=F.sub.max, then the focus position is not adapted, i.e., z 0/z 0 max is zero.

[0130] Finally, it should be noted that the description of the invention and the exemplary embodiments are not to be understood as limiting in terms of a particular physical realisation of the invention. All of the features explained and shown in connection with individual embodiments of the invention can be provided in different combinations in the object according to the invention to simultaneously realise the advantageous effects thereof.

[0131] The scope of protection of the present invention is given by the following claims and is not limited by the features illustrated in the description or shown in the figures.

[0132] It is particularly obvious to a person skilled in the art that the invention can be used not only for settings of certain process parameters, such as the focus position, but also for other process parameters, for example, such as for adjusting or correcting the gas pressure. Furthermore, the components of the device or computing unit can be produced so as to be distributed over a plurality of physical products.