Calibration of a laser processing machine with respect to different excitation frequencies
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Solution Overview
Problem
Existing laser processing machines exhibit unique oscillation behaviors due to varying mechanical properties, necessitating machine-specific compensation to improve processing accuracy and quality, as a one-size-fits-all compensation scheme is ineffective.
Innovation Solution
A frequency-dependent machine model is generated by exciting the laser processing machine with defined frequencies, detecting the response using sensors, and calculating oscillation data to create a machine-specific model that compensates for oscillations across various cutting plans and operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a one-size-fits-all compensation scheme is applied to different laser processing machines, then the device complexity is reduced, but the manufacturing precision deteriorates because each machine has different oscillation behaviors
Solution Approach 1:
The patent applies parameter changes by creating machine-specific oscillation models that capture the unique dynamic characteristics of each laser processing machine. Instead of using a universal compensation scheme, the system determines frequency-dependent oscillation parameters (masses, damping coefficients, stiffness) for each individual machine through identification procedures, allowing the compensation algorithm to adapt to each machine's specific behavior and thereby maintain high processing accuracy across different machines.
2Manufacturing precision
If machine-specific oscillation models are determined for every laser processing machine, then the manufacturing precision is improved, but the device complexity and calibration time increase
Solution Approach 1:
The patent applies preliminary action by performing oscillation model identification and calibration before actual production processing. The system executes identification procedures that determine the machine-specific oscillation parameters in advance, creating a pre-calibrated model that can then be used for compensation during normal operation. This preliminary calibration step separates the complex model determination process from production operations, reducing the impact on productivity while maintaining high precision.
Solution Approach 2:
The system applies self-service by implementing automated oscillation identification procedures that use the machine's own operational data and built-in sensors to determine its characteristic parameters. The calibration process utilizes the machine's existing control system, drive axes, and measurement capabilities to generate its own oscillation model without requiring external specialized equipment or extensive manual intervention, thereby reducing the complexity of the calibration system.
3Manufacturing precision
If frequency-dependent oscillation data is collected and stored for compensation, then the manufacturing precision is improved, but the loss of time during calibration and data collection increases
Solution Approach 1:
The patent applies periodic action by implementing efficient frequency sweep procedures that excite the machine at multiple discrete frequencies in a structured sequence. The identification process uses periodic excitation signals at different frequencies to systematically determine the frequency-dependent oscillation characteristics. This periodic approach allows for comprehensive data collection across the relevant frequency range while maintaining a systematic and time-efficient measurement protocol.
Solution Approach 2:
The system applies partial action by focusing the frequency-dependent measurement on the most relevant frequency range for the specific application. Instead of measuring across all possible frequencies, the identification procedure targets the frequency band where oscillation effects are most significant for the given machine and processing tasks. This selective approach reduces the total measurement time while still capturing the essential oscillation characteristics needed for effective compensation.
Data Source
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AI summary
The present invention relates to generating a frequency-dependent machine model, in which oscillation data are stored which may be used to compensate a frequency-based oscillation behaviour of a laser processing machine (LPM) with a processing head (H) which is to be moved with at least two drive axes, having the following method steps: - Reading in or generating (S1) a setpoint function, wherein the setpoint function is configured to excite the laser processing machine (LPM) with at least two defined different frequencies for triggering a frequency-based oscillation behaviour as response of the laser processing machine (LPM) to the excitation; - Generating (S2) control commands for the at least two drive axes for instructing the processing head (H) of the laser processing machine (LPM) to move along a target trajectory, whereby the control commands implement the generated or read-in setpoint function (SPF1, SPF2); - Transmitting (S3) the generated control commands to the laser processing machine (LPM) for execution for machining (S4) a workpiece, during which the laser is at least temporarily switched on; - Detecting (S5) the frequency dependent response of the laser processing machine (LPM) by means of at least one optical sensor (S) for detecting an actual trajectory of the machined workpiece; - Determining (S6) a result, comprising the actual trajectory in relation to the instructed target trajectory, wherein the result serves to calculate and store frequency-dependent oscillation data for generating the frequency-dependent machine model.