Laser Focal Offset Learning for Heat-Drift Correction
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Solution Overview
Problem
Laser processing apparatuses face challenges in accurately correcting focal position offsets due to disturbances like heat, leading to deviations in the effective light-focusing position, which affect the quality of processing and the lifespan of optical system components.
Innovation Solution
A machine learning device and method that learn the positional relationship between a workpiece and the effective light-focusing position by generating a learning model from data on focal position commands and light detection data, enabling precise correction of focal position offsets during processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional focal position correction methods are used, then the focal position can be adjusted, but the precision of correction is insufficient due to disturbances like heat
Solution Approach 1:
The system performs preliminary learning to establish the relationship between light detector output values and focal position offsets before actual processing. By pre-acquiring correction data under various conditions (including heat disturbances), the system can apply accurate corrections without real-time measurement delays, improving both precision and reliability
Solution Approach 2:
The system uses light detectors to continuously monitor the actual focal position and feeds this information back to the correction mechanism. The light detector output values are compared against the learned relationship model, and real-time feedback enables dynamic adjustment of the focal position to compensate for heat-induced drift and other disturbances
2Productivity
If the light-focusing optical system is used for processing, then workpiece processing can be performed, but the effective light-focusing position deviates from the designed focal position due to heat and other disturbances
Solution Approach 1:
The patent introduces light detectors as intermediary elements that indirectly measure the focal position by detecting the position of the focused laser beam. This intermediary measurement approach allows for precise focal position monitoring without interfering with the actual workpiece processing, enabling continuous correction while maintaining productivity
Solution Approach 2:
The system performs preliminary learning to establish the relationship between light detector output values and focal position offsets before actual processing. By pre-acquiring correction data under various conditions (including heat disturbances), the system can apply accurate corrections without real-time measurement delays, improving both precision and reliability
3Duration of action of moving object
If the focal position is not corrected, then processing can continue, but the quality of laser processing deteriorates
Solution Approach 1:
The system implements continuous focal position monitoring and correction during the entire processing operation. Light detectors continuously track focal position drift, and the correction mechanism continuously adjusts the focal position to maintain optimal processing quality throughout extended production runs, enabling both continuous operation and consistent quality
Solution Approach 2:
The system uses light detectors to continuously monitor the actual focal position and feeds this information back to the correction mechanism. The light detector output values are compared against the learned relationship model, and real-time feedback enables dynamic adjustment of the focal position to compensate for heat-induced drift and other disturbances
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
Improves the precision of focal position offset correction, maintains processing quality, and extends the lifespan of light-focusing optical system components by adapting to variations in processing conditions and workpiece characteristics.
Implementation Method 1
a light-focusing optical system including a lens, a mirror, a protective window, etc.
Implementation Method 2
detection data of a physical quantity of light detected when a laser beam is emitted
Data Source
AI summary
A machine learning device for learning a focal position offset of a laser processing apparatus. A data acquisition section acquires a learning dataset which includes data of a focal position command for a light-focusing optical system given to the laser processing apparatus and detection data of a physical quantity of light detected when a laser beam is emitted from a laser oscillator in accordance with a processing command including the focal position command. A learning section generates a learning model by using the learning dataset, which represents correlativity between the physical quantity of the detected light and the positional relationship of an effective light-focusing position of the light-focusing optical system relative to a workpiece. When performing processing, the physical quantity of light is detected so that a positional relationship between the workpiece and the effective light-focusing position during processing can be estimated from the detected quantity and the learning model.