Laser Machining Head Monitoring via HDR Fingerprint Classification
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Solution Overview
Problem
Current laser machining process monitoring systems lack the ability to adaptively classify and improve machining quality in real-time, relying on manual adjustments and limited automatic control, which is inefficient and not suitable for varying workpiece conditions.
Innovation Solution
A method and device that utilize a camera unit with high dynamic range imaging and machine learning algorithms to create a 'fingerprint' of the machining process, allowing for real-time classification and adaptive control of process parameters through a sensor system that includes photodiodes, sound sensors, and cameras, enabling automatic adjustment of laser power, speed, and focus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard radiation sensors and cameras are used for process monitoring, then the current status of the machining process can be classified, but the system cannot adaptively improve machining quality in real-time
Solution Approach 1:
The patent implements a closed-loop feedback system where sensor data from the machining zone is continuously analyzed and used to automatically adjust process parameters. The evaluation unit compares measured values against reference data to determine quality characteristics, and the control unit responds by adjusting laser power, feed rate, or other parameters in real-time, creating an adaptive feedback mechanism that resolves the contradiction between monitoring capability and adaptive control
Solution Approach 2:
The system performs self-adjustment by automatically analyzing its own process data and correcting deviations without external intervention. The evaluation unit autonomously assesses machining quality based on sensor inputs, and the control unit self-corrects process parameters to maintain optimal conditions, enabling the system to serve itself in maintaining and improving machining quality
2Device complexity
If manual adjustments and limited automatic control are used, then system complexity is reduced, but machining quality improvement efficiency is insufficient
Solution Approach 1:
The patent replaces manual mechanical adjustment operations with automated electronic control systems. Sensors, evaluation units, and control algorithms automatically monitor and adjust process parameters, substituting human operators and manual controls with an integrated automated system that increases productivity while managing complexity through software-based solutions
3Manufacturing precision
If regulation of process parameters is based only on respective measurement data of corresponding sensors, then measurement-specific control is achieved, but comprehensive process optimization is limited
Solution Approach 1:
The patent creates a universal control system where a single evaluation unit processes data from multiple different sensor types (radiation sensors, cameras, temperature sensors) and coordinates adjustment of various process parameters (laser power, feed rate, focus position). This multi-functional evaluation unit transcends sensor-specific control by integrating information from diverse sources to achieve comprehensive process optimization across all machining parameters
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables improved and adaptive monitoring and control of laser machining processes, allowing for rapid learning and error correction, enhancing machining quality and efficiency by automatically adjusting to changes in workpiece conditions.
Implementation Method 1
The at least one sensor comprises at least one camera unit, which takes camera images with different exposure times and offsets them using a high dynamic range (HDR) method to form current measured values
Implementation Method 2
In addition to the use of photodiodes, which are each sensitive to a specific wavelength range, the laser processing process is also monitored by cameras
Implementation Method 3
workpieces are cut or joined using focused laser radiation
Implementation Method 4
focused laser radiation
Implementation Method 5
the observation beam path of the photodiodes and the CCTV camera being coupled coaxially via beam splitters into the beam path of a processing laser beam
Data Source
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AI summary
The invention relates to a method for monitoring a laser machining operation to be performed on a workpiece, comprising the following steps: detecting at least two current measured values by at least one sensor, which monitors the laser machining operation, determining at least two current characteristic values from the at least two current measured values, wherein the at least two current characteristic values jointly represent a current fingerprint in a characteristic value space, providing a predetermined point set in the characteristic value space, and classifying the laser machining operation by detecting the position of the current fingerprint relative to the predetermined point set in the characteristic value space, wherein the at least one sensor comprises at least one camera unit, which records camera images with different exposure times and processes them together by using a high dynamic range (HDR) method, in order to provide images having a high contrast ratio as the current measured values.