|About this Abstract
||2022 TMS Annual Meeting & Exhibition
||Seeing Beneath the Surface: Estimating Interior Material Properties with Visual Vibration Tomography
||Berthy T. Feng, Alexander C. Ogren, Chiara Daraio, Katherine L. Bouman
|On-Site Speaker (Planned)
||Berthy T. Feng
An object’s interior material properties, while invisible to the human eye, determine motion observed on its surface. We propose an approach that estimates spatially-varying material properties of an object directly from a monocular video of its surface vibrations. Specifically, we estimate Young’s modulus and density throughout a 3D object with known geometry. Vibration analysis tools such as laser vibrometers, ultrasound detectors, and other contact sensors generally do not recover full-field measurements. Our work shows how to overcome such limitations, imaging full-field material properties from 2D surface displacements captured in a monocular video. Our approach is to (1) measure sub-pixel motion and decompose this motion into image-space modes, and (2) directly infer Young’s modulus and density values by solving a constrained optimization problem. We demonstrate our approach on both simulated and real videos. In particular, our method allows us to characterize unseen defects on a drum head from real, high-speed video.
||Characterization, Computational Materials Science & Engineering, Modeling and Simulation