Optical Displacement Meter With Multi-Image Peak Clustering
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Solution Overview
Problem
Optical displacement meters face challenges in accurately measuring the profile of a workpiece due to noise generated by multiple reflections and disturbance light, which complicates the distinction between true peak positions and noise in the light receiving amount distribution.
Innovation Solution
The optical displacement meter uses a control unit to acquire multiple light reception images while the workpiece moves relative to the slit light, detecting peak positions in a direction orthogonal to the slit light, and generates clusters based on peak position candidates within a certain distance threshold, determining noise based on the inclination of these clusters to suppress noise and generate accurate profile data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple light reception images are acquired and peak position candidates are clustered to suppress noise, then measurement accuracy is improved, but device complexity and processing time increase
Solution Approach 1:
The patent segments the light reception data by dividing it into multiple light reception images acquired during relative movement. By processing each image separately and then clustering peak position candidates across the segmented data, the system achieves noise suppression while maintaining manageable processing complexity through systematic division of the measurement task.
Solution Approach 2:
The patent transitions from analyzing a single light reception image to analyzing multiple images across the scan direction (temporal dimension). By clustering peak position candidates from multiple images and evaluating their distribution along the scan direction, the system adds a temporal dimension to the analysis, enabling distinction between true peaks and noise based on their behavioral patterns across time.
2Measurement precision
If multiple light reception images are acquired and clustered analysis is performed, then noise due to multiple reflection is suppressed, but measurement time increases
Solution Approach 1:
The patent employs periodic acquisition of multiple light reception images during the relative movement between the optical displacement meter and workpiece. By systematically capturing images at regular intervals and applying cluster analysis to the collected data, the system achieves effective noise suppression through periodic sampling while maintaining efficient measurement throughput.
Solution Approach 2:
The patent performs preliminary clustering of peak position candidates from multiple light reception images before final profile generation. By pre-processing the data to identify and evaluate candidate peaks across multiple images, the system prepares refined data structures that facilitate efficient final measurement, reducing the computational burden during actual measurement execution.
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 effectively suppresses noise due to multiple reflections, enabling precise measurement of the workpiece's shape by distinguishing true peak positions from noise, thereby improving measurement accuracy.
Implementation Method 1
an image sensor that includes a plurality of pixels, receives reflected light reflected from the workpiece by the plurality of pixels, and outputs a light reception image indicating a light receiving amount distribution
Data Source
AI summary
An optical displacement meter controls an image sensor to sequentially acquire a plurality of light reception images along with the relative movement of the workpiece, detects a peak position candidate in a V direction for each position in the U direction based on a light receiving amount distribution of the light reception image, and, for each position in the U direction, generates one or more clusters including a plurality of peak position candidates selected such that a distance between a peak position candidate of any one light reception image and a peak position candidate of another light reception image is equal to or less than a certain value, determines whether noise is included in the cluster based on an inclination of the cluster with respect to a direction of the relative movement, and generates profile data of the workpiece based on a result of the determination.