3D Camera Strain Measurement via Multi-Position Image Splicing

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Solution Overview

Problem

Current strain measurement methods for large-scale movements or areas face challenges in achieving high resolution due to limitations in camera resolution, making it difficult to accurately measure strain in larger observation ranges or areas.

Innovation Solution

The use of a 3D camera module and image processor to acquire and splice 3D images from multiple positions, allowing for the generation of initial and deformed 3D images, which are then compared to output deformation information, effectively increasing the measurement range without reducing recognition quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Area of stationary object

If the measurement range is increased to cover larger areas or distances, then the observation range is improved, but the recognition degree decreases due to fixed camera resolution

Engineering Contradiction:
Improvemeasurement rangeVSAvoidrecognition degree
Core Design Contradiction:
Area of stationary objectVSMeasurement precision

Solution Approach 1:

The patent divides the large measurement area into multiple smaller sub-areas, each captured by the camera at different positions. Multiple images are taken from different locations and then spliced together to form a complete large-area image, allowing high-resolution capture across the entire measurement range

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent transitions from a single static image capture to multi-position sequential capture, adding the dimension of spatial movement. By moving the camera to multiple positions and combining images from different spatial locations, the system achieves both large measurement range and high recognition degree

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

2Measurement precision

If the camera resolution is maintained at current technology levels, then device complexity is kept simple, but strain measurement accuracy for large scale movement is insufficient

Engineering Contradiction:
Improvestrain measurement accuracyVSAvoidmeasurement system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces dynamic movement of the camera module to different measurement positions. Instead of using a single high-resolution camera, the system dynamically captures multiple images from different positions and combines them, achieving high measurement accuracy without requiring a single complex high-resolution device

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent creates multiple copies of the measurement process by capturing images from different positions. Each position provides a local high-resolution view, and the combination of these copies produces the complete accurate measurement result for the entire large area

Inventive Principle:
Principle #26Copying

Data Source

PatentUS11204240B2Strain measurement method and strain measurement apparatus
Publication Date: 2021.12.21 IND TECH RES INST
  • US11204240B2 patent drawing
  • US11204240B2 patent drawing
  • US11204240B2 patent drawing

AI summary

A strain measurement method includes disposing a 3D camera module at a first measurement position; using the 3D camera module to acquire a first 3D image of a to-be-measured object at a first to-be-measured position; acquiring a second 3D image of the to-be-measured object at the first to-be-measured position; and splicing the first and second 3D images to obtain an initial 3D image. The method still includes: moving the 3D camera module from the first measurement position to a second measurement position; using the 3D camera module to acquire a third 3D image of the to-be-measured object at a second to-be-measured position; acquiring a fourth 3D image of the to-be-measured object at the second to-be-measured position; and splicing the third and fourth 3D images to obtain a deformed 3D image. The method further includes comparing the initial 3D image and the deformed 3D image to output 3D deformation information.