Video Extensometer Error Correction for Perspective and Vibration
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Solution Overview
Problem
Conventional camera-based video extensometer systems suffer from imaging errors due to perspective variations, noise, and component placement issues, leading to inaccurate measurements of specimen strain, especially when the distance between the specimen and the camera changes during testing.
Innovation Solution
The system employs multiple cameras with telecentric lenses, active vibration control, fluid delivery systems, and real-time image processing to correct for errors by adjusting the imaging device's position and orientation based on sensor data, using actuators to mitigate noise and perspective variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional cameras are used to capture images for strain measurement, then the system structure is simple, but measurement accuracy deteriorates due to perspective variations and imaging errors
Solution Approach 1:
A calibration target with known geometric features is introduced as an intermediary between the camera and the specimen. The calibration target captures perspective distortion and imaging errors, allowing the system to compute correction factors that compensate for these errors in subsequent strain measurements, thereby improving accuracy without requiring complex hardware changes
Solution Approach 2:
The system dynamically adjusts imaging parameters such as exposure time, gain, and focus based on real-time feedback from the calibration target and specimen position. This allows the camera to maintain optimal measurement conditions across varying test scenarios, improving precision while using standard camera hardware
2Measurement precision
If the camera position is adjusted to maintain focus on the specimen during testing, then measurement accuracy improves, but system complexity increases due to additional actuators and control mechanisms
Solution Approach 1:
The system continuously monitors the position of the specimen and the calibration target using image processing algorithms. Based on this feedback, actuators automatically adjust the camera position or focal length to maintain optimal imaging conditions throughout the test, ensuring consistent measurement accuracy without manual intervention
Solution Approach 2:
The imaging system transitions from a static configuration to a dynamic one where camera parameters (position, focus, exposure) are continuously adapted during the test based on specimen deformation and position changes. This dynamic adjustment maintains image quality and measurement precision throughout the entire testing process
3Reliability
If multiple cameras are used to reduce perspective errors, then measurement reliability improves, but device complexity and cost increase
Solution Approach 1:
The system uses a single camera to capture images from multiple angles by rotating the camera or the specimen between captures. This multi-angle imaging approach reconstructs three-dimensional specimen deformation, providing reliable strain measurements equivalent to multiple simultaneous cameras but with reduced hardware complexity
Data Source
AI summary
Systems and methods for materials testing include mage devices employing camera based image capture (e.g., vision or video) for measurement of strain on the test specimen. Such systems and methods collect multiple images of the specimen under test (i.e. during a testing process), with the images being synchronized with other signals of interest for the test (such as specimen load, machine actuator and/or crosshead displacement, etc.). The images of the specimen are analyzed (e.g., in real-time and/or post-test) by algorithms to locate and track specific specimen characteristics as the test progresses.