Method, control unit and laser cutting system for combined path and laser process planning for highly dynamic real-time systems
In one aspect, the present invention relates to a control unit (RE) for calculating a spatially and time-resolved, combined setpoint data set (SW-DS) for open- and/or closed-loop control of a laser cutting process during laser cutting with a laser cutting machine (L), wherein a processor (P) is intended to access a process model (PM) in a first memory (SI) via a process interface (P-SS) and a machine model (MM) in a second memory (S2) via a machine interface (M-SS) in order, on the basis of an estimated status data of the laser cutting process and the movement process, to calculate the spatially and time-resolved, combined setpoint data set (SW-DS) with coordinated setpoints for the laser cutting process and setpoints for the movement process, taking into account the read-in sensor data.
1. A laser cutting system that improves a quality of a laser cutting process while ensuring process stability and productivity with a combination of a process model and a machine model for a combined calculation of a setpoint data set by recognizing and avoiding quality deviations in advance and, in an event of deviations between a model estimation and a measurement, a model update is carried out automatically to reduce the deviations, the laser cutting system, the laser cutting system comprising:
a control unit for calculating a spatially and time-resolved, combined setpoint data set for open- and/or closed-loop control of the laser cutting process; and
a laser cutting machine with a movable laser cutting head, which is moved and operated with drives along a geometry according to the setpoint data set calculated by the control unit,
wherein the control unit is configured with:
a measurement data interface to at least one sensor for measuring sensor data during the cutting operation, wherein the sensor data encode a cutting result of the laser cutting process;
the at least one sensor;
a process interface to a first memory in which a process model is stored which represents the laser cutting process and estimates status data of the laser cutting process and a cutting result resulting therefrom, wherein the status data of the laser cutting process include physical laser parameters during laser cutting, wherein the physical laser parameters at least include a feed rate value for the laser cutting head and/or a nozzle spacing value;
a machine interface to a second memory in which a machine model is stored which represents a kinematic behavior of the laser cutting head during movement thereof and estimates status data of a movement process and the cutting result resulting therefrom, wherein the status data of the movement process at least include the feed rate value for the laser cutting head and/or the nozzle spacing value;
a processor which is intended to execute an algorithm which couples the process model and the machine model via the feed rate value for the laser cutting head and/or via the nozzle spacing value;
wherein the processor is furthermore intended to access the process model in the first memory via the process interface and the machine model in the second memory via the machine interface in order, on a basis of the estimated status data of the laser cutting process and the movement process, to calculate the spatially and time-resolved, combined setpoint data set with coordinated setpoints for the laser cutting process and setpoints for the movement process, taking into account the sensor data, wherein the model-estimated cutting results are compared with the measured cutting result, and wherein the process model and/or the machine model is updated in the event of deviations; and
in response to the process model and/or the machine model being updated, recalculating and correcting the spatially and time-resolved, combined setpoint data set with coordinated setpoints for the laser cutting process and setpoints for the movement process of the laser cutting machine, and controlling the laser cutting machine with the corrected setpoint data set to reduce the deviations.