Camera Perturbation Signal Analysis for Accurate Vibration Measurement
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Solution Overview
Problem
Vision-based vibration measurement technology is affected by camera perturbations due to external vibration noise, leading to inaccuracies in structural vibration time history signals.
Innovation Solution
A method involving signal decomposition, frequency domain analysis, and mirror index calculation to identify and eliminate perturbation signals by generating multiple signal sets, determining frequency domain mirror indexes, and removing the perturbation signal based on the maximum index.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vision-based vibration measurement is used to achieve non-contact measurement with long monitoring distance, then measurement accessibility and safety are improved, but camera perturbation from external vibration noise degrades measurement precision
Solution Approach 1:
The patent extracts and eliminates the camera perturbation component from the measured signal by identifying it as a separate signal source. Through signal decomposition and feature extraction, the camera's vibration-induced noise is separated from the actual structural vibration signal, allowing the true vibration characteristics to be recovered without the contaminating camera perturbations.
Solution Approach 2:
The patent introduces an intermediary processing system consisting of signal decomposition modules, frequency domain analysis units, and perturbation elimination algorithms. This intermediary processing chain transforms the contaminated signal into a cleaned signal by inserting multiple processing stages between the camera capture and final measurement output.
2Measurement precision
If signal decomposition and frequency domain analysis are performed to eliminate camera perturbation, then measurement precision is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent segments the signal processing into distinct functional modules: signal decomposition, frequency domain analysis, perturbation identification, and signal reconstruction. Each module handles a specific aspect of the processing task, allowing for optimized computation and potential parallel execution. The segmentation enables systematic processing while managing computational complexity through modular design.
Solution Approach 2:
The patent transforms the signal from the time domain to the frequency domain, changing the representation parameters to facilitate easier identification and elimination of perturbation components. By converting to frequency domain representations, the processing algorithms can more efficiently identify and remove camera perturbations compared to direct time-domain processing.
Data Source
AI summary
Disclosed are a camera perturbation effect evaluation and elimination method, device and storage medium. The method includes: decomposing a signal to be processed and eliminating them one by one to generate a plurality of second signal sets, obtaining a plurality of frequency domain mirror indexes according to curve information obtained after frequency domain analysis of the plurality of second signal sets and a mirror index formula, determining a perturbation signal based on a maximum frequency domain mirror index, and eliminating the perturbation signal to obtain a perturbation elimination signal.