Optical Texture and Shape Detection via Dual-Beam Segmentation
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Solution Overview
Problem
Current optical detection methods for product quality control, particularly in the non-contact mode, are prone to environmental interference and complex calculations, leading to reduced accuracy and increased costs due to the need for stable conditions and coherence in light beams.
Innovation Solution
A method involving two light sources and photodetectors to detect the topography and surface shape of an object, with the first light source emitting a collimated beam for topography detection and the second light source emitting a coherent beam for surface shape tracking, allowing for reconstruction of the three-dimensional geometric contour by superimposing the collected data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-contact detection method using interferometers is used, then detection accuracy is improved, but environmental interference (vibration, temperature) increases and requires stable detecting environment
Solution Approach 1:
The detection system is divided into two independent subsystems: a topography detection subsystem using a first light source and photodetector, and a shape track detection subsystem using a second light source and photodetector. Each subsystem independently measures specific characteristics without interfering with the other, reducing sensitivity to environmental disturbances while maintaining high measurement precision
Solution Approach 2:
A beam splitter is introduced as an intermediary component to separate the detection paths of the two light sources. This allows the system to process topography and shape track information through different optical paths, isolating the measurement processes from each other and from environmental interference
2Measurement precision
If interference fringes analysis is used, then surface contour reconstruction is achieved, but calculation complexity increases and image analysis accuracy is affected
Solution Approach 1:
The complex task of surface reconstruction is segmented into two simpler sub-tasks: topography measurement through wavefront interference and shape track measurement through light reflection. Each sub-task uses simplified calculation methods appropriate to its specific measurement goal, avoiding the need for complex comprehensive analysis
Solution Approach 2:
The patent extracts and separates the different measurement information (topography and shape track) from the complex interference fringe pattern. By using two distinct light sources and detection paths, the system extracts specific measurement data without being overwhelmed by the full complexity of interference analysis
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 minimizes external interference, simplifies the detection mechanism, and reduces calculation complexity, enhancing detection accuracy and precision while reducing costs.
Implementation Method 1
a first light source to emit a first light beam toward an object to be tested along a first optical axis, the first light beam emitted is first expanded and collimated and then transmits the object to form a topography detection light beam
Implementation Method 2
a second light source to emit a second light beam toward the object along a second optical axis, the second light beam emitted is first reflected from a surface of the object to form a track detection light beam
Implementation Method 3
the topography detection light beam is detected by a first photodetector, which can collect imaging signals of the object in the direction of the first optical axis
Data Source
AI summary
The present invention relates to a method for detecting the texture, geometric shape and geometric center of a geometric element, which comprises the following steps: providing a first light beam projected on the object under test to obtain a gradual gradient image, and its texture and topography are reconstructed; providing a second light beam directed toward the object, and then the object is rotated, to obtain a continuous surface shape track, and reconstructs the surface shape of the object; calculating the geometric center from the surface shape track, and superimposes the surface shape track with the topography to rebuild a three-dimensional geometric contour of the object.