OCT Height Signal Correction for Background Dispersion Compensation
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Solution Overview
Problem
Optical coherence tomography (OCT) measurements in high-energy machining processes face challenges in accurately filtering out background signals, leading to inaccurate height signals due to background components being subject to different dispersion than the object signal, causing broadening and difficulty in distinguishing from noise.
Innovation Solution
A method involving a measuring device and control unit that performs transformations to isolate and compensate background components in OCT measurement data, using dispersion compensation and threshold-based clipping to obtain a corrected height signal, ensuring accurate removal of background noise and refinement of the object signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If software-based dispersion compensation algorithms are used, then dispersion compensation is achieved, but background signals become strongly broadened and difficult to distinguish from noise
Solution Approach 1:
The patent segments the signal processing into distinct stages: first performing dispersion compensation to correct the object signal, then separately handling background signal removal through subtraction or thresholding. This segmentation allows each processing stage to be optimized independently, preventing the broadening and loss of background signals that occurs when dispersion compensation is applied to the entire composite signal.
Solution Approach 2:
The patent performs preliminary dispersion compensation on the measurement data before background signal removal. By applying dispersion compensation first, the object signal is properly focused and corrected, while the background signal remains in its original state for easier identification and removal in subsequent steps, avoiding the broadening effect that would make background signals indistinguishable.
2Reliability
If static background subtraction is performed, then background removal is achieved, but accuracy is reduced due to background signal changes from environmental influences
Solution Approach 1:
The patent implements dynamic background compensation by performing dispersion compensation on the measurement data first, which transforms the background signal characteristics. This dynamic approach allows the background signal to be continuously updated and adapted to current measurement conditions, rather than relying on static pre-recorded backgrounds that may have changed due to environmental factors.
Solution Approach 2:
The patent changes the parameters of the background signal through dispersion compensation transformation. By applying dispersion compensation algorithms, the background signal undergoes parameter changes that make it more distinguishable from noise and more accurately removable, while preserving the integrity of the object signal for subsequent analysis.
3Measurement precision
If dispersion compensation is applied to the entire measurement data, then object signal is corrected, but background components are broadened and lost
Solution Approach 1:
The patent segments the signal processing workflow to apply dispersion compensation only to the object signal component, not to the entire composite measurement data including background signals. This is achieved by first removing or identifying background components, then applying dispersion compensation selectively to the remaining object signal, thereby preserving background signal integrity while still achieving accurate object signal correction.
Solution Approach 2:
The patent extracts and separates the background signal components from the measurement data before applying dispersion compensation. By taking out the background signals through various methods (subtraction, thresholding, or identification based on their distinct characteristics), the dispersion compensation algorithm can be applied solely to the object signal without causing broadening or loss of the background signal information.
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
The method effectively filters out background signals, providing a high-quality, accurate object signal by prioritizing background correction before dispersion compensation, thus improving the reliability of height signal determination in OCT measurements.
Implementation Method 1
obtaining measurement data based on interference of sample light guided in a sample arm and reference light guided in a reference arm
Implementation Method 2
When passing through the first transmission grating, an incident light beam is split as a function of the wavelength
Data Source
AI summary
A method, measuring device, machining system and computer program product are provided for determining a corrected height signal from measurement data obtained with optical coherence tomography. The measurement data comprises an object signal and a background signal superimposed on the object signal, the object signal and the background signal being subject to different dispersion. A first transformation is performed comprising transforming the measurement data, the first transformation being targeted at the background signal to obtain a height signal, background components in the height signal are determined, the background components in the height signal are compensated to obtain a background-compensated height signal, an inverse transformation is performed comprising back-transforming the background-compensated height signal to obtain background-compensated measurement data, dispersion compensation for the object signal is performed to obtain dispersion-compensated and background-compensated measurement data, and a second transformation is performed comprising transforming the dispersion-compensated and background-compensated measurement data to obtain a dispersion-compensated and background-compensated height signal.