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Influence of Noise in Computer-Vision-Based Measurements on Parameter Identification in Structural Dynamics
Mariusz Ostrowski1, Bartlomiej Blachowski1, Grzegorz Mikułowski1
1Institute of Fundamental Technological Research, Polish Academy of Sciences, 02-106 Warsaw, Poland.
Sensors (Basel, Switzerland)
|January 8, 2023
Summary
Consumer-grade smartphone cameras can measure dynamic displacements for structural analysis. While introducing frequency-dependent errors, they offer a low-cost solution for identifying lower-order vibration modes and stiffness parameters.
Area of Science:
- Structural Dynamics and Vibration Analysis
- Computer Vision and Signal Processing
- Consumer Electronics Applications
Background:
- Consumer electronics, particularly smartphone cameras, offer potential for computer-vision-based (CV) measurements of dynamic displacements.
- Existing CV measurement techniques face trade-offs between sampling frequency, resolution, and cost.
- Hardware limitations of consumer-grade devices can impact measurement accuracy for dynamic analysis.
Purpose of the Study:
- To investigate the influence of smartphone camera hardware limitations on dynamic displacement estimation.
- To evaluate the accuracy of modal and stiffness parameter identification using smartphone cameras.
- To compare CV measurements with traditional sensors like accelerometers and laser distance sensors.
Main Methods:
- Utilized a consumer-grade smartphone camera (CMOS technology) for dynamic displacement measurements.
- Employed a zero-normalized cross-correlation algorithm for displacement extraction.
- Applied stochastic subspace identification for modal parameter estimation.
- Used model-updating based on modal sensitivities for stiffness parameter identification.
Main Results:
- CV measurements identified lower-order vibration modes with a systematic bias error proportional to frequency (2% at 9.4 Hz to 10% at 71.4 Hz).
- Smartphone camera measurement errors had less influence on stiffness parameters compared to the number of modes/parameters considered, due to bias-variance trade-off.
- Results were validated against data from accelerometers and a laser distance sensor.
Conclusions:
- Consumer-grade smartphone cameras are viable low-cost tools for measuring dynamic displacements and identifying lower-order vibration modes in structures.
- The accuracy is sufficient for applications requiring identification of fundamental structural behaviors.
- Careful consideration of the bias-variance trade-off is necessary when interpreting results for parameter identification.
