Publications

In this paper, we present an accelerated noncontact guided wave array imaging method with sparse scanning measurements at only a small number of points with comparable performance using dense measurements.

H. Song, Y. Yang

Ultrasonics 121, 106672 (2021)

we present a hierarchical deep learning approach for identifying optimal low-order models of nonlinear dynamical systems. It simultaneously identifies the nonlinear normal modal (NNM) subspace with a hierarchical order and the associated nonlinear modal dynamics.

S. Li, Y. Yang

Nonlinear Dynamics 105, 3409–3422 (2021)

we present a new data-driven framework based on physics-integrated deep learning for nonlinear modal identification of unknown nonlinear dynamical systems.

S. Li, Y. Yang

Nonlinear Dynamics 106, 3231–3246 (2021)

we present a non-contact super-resolution guided wave array imaging approach with deep learning to visualize sub-wavelength defects in plate-like structures.

H. Song, Y. Yang

Structural Health Monitoring 20(4), 1904-1923 (2020)

we enable super-resolution ultrasonic beamforming that computationally exceeds the diffraction limit and visualizes subwavelength defects.

H. Song, Y. Yang

NDT & E International 116, 102344 (2020)

We identify 3-Dimensional full-field modes of dynamic structures from point cloud data acquired using a commercial, low-cost, time-of-flight imager.

M. Silva, A. Green, J. Morales, P. Meyerhofer, Y. Yang, E. Figueiredoe, J. Costa, D. Mascarenas

Mechanical Systems and Signal Processing 166, 108352 (2021)

see Best Paper award, IMAC 2021 of Society of Experimental Mechanics (SEM)

we explicitly incorporate the multi-step prediction with error accumulation and an adaptive training strategy into model training to improve long-time prediction of future states of nonlinear dynamics.

S. Li, Y. Yang

Journal of Sound and Vibration 506, 116167 (2021)

We exploit and visualize the spatial, full-field mode shape associated with each candidate mode to distinguish the physical and spurious modes.

Y. Yang, C. Dorn

Journal of Sound and Vibration 483, 115473 (2020)

Our method performs simultaneous processing of all pixel time-series to extract full-field high-resolution mode shapes and other modal parameters.

M. Silva, B. Martinez, E. Figueiredo, J. Costa, Y. Yang, D. Mascarenas

Journal of Sound and Vibration 487, 115586 (2020)

we introduce CNN-LSTM deep learning based approach that can serve as a backbone for computer vision-based vibration measurement techniques.

R. Yang, S. Singh, M. Tavakkoli, N. Amiri, Y. Yang, M. Karami, R. Rai

Mechanical Systems and Signal Processing 144, 106885 (2020)

We simultaneously identify (separate) both the subtle, full-field deformation modes and the dominant rigid-body motion from only the video of the vibrating while moving structure.

Y. Yang, C. Dorn, C. Farrar, D. Mascarenas

Engineering Structures 207, 110183 (2020)

This study develops a physics-guided, unsupervised machine learning-based video processing approach that can blindly and efficiently extract the full-field (as many points as the pixel number of the video frame) modal parameters of cable vibration using only the video of an operating (output-only) cable.

Y. Yang, L. Sanchez, H. Zhang, A. Roeder, J. Bowlan, J. Crochet, C. Farrar, D. Mascarenas

Structural Control and Health Monitoring 26(6), e2358 (2019)

We estimate the full-field (as many measurement points as the pixel number of the video frame on the structure) dynamic strains at high-spatial (pixel)-resolution/density location points from the digital video measurement of output-only vibrating structures.

Structural Control and Health Monitoring 26(10), e2408 (2019)

We explore light field imagers - a new camera system that captures the direction light entered the camera - to make depth measurements of scenes and extend modal analysis to three dimensions.

B. Chesebrough, S. Dasari, A. Green, Y. Yang, C. Farrar, D. Mascarenas

Structural Health Monitoring, Photogrammetry & DIC 6, 101-108 (2019)

This work explores the use of event-based neuromorphic imagers, specifically silicon retinas, an efficient alternative to traditional frame-based video cameras, to perform full-field vibration measurements and operational modal analysis.

C. Dorn, S. Dasari, Y. Yang, C. Farrar, G. Kenyon, P. Welch, D. Mascarenas

Journal of Engineering Mechanics 144(7), 04018054 (2018)

We perform spatiotemporal video-domain high-fidelity simulation and realistic visualization of full-field structural dynamics by an innovative combination of the fundamentals of structural dynamic modeling and the advanced video motion manipulation techniques.

Y. Yang, C. Dorn, T. Mancini, Z. Talken, G. Kenyon, C. Farrar, D. Mascarenas

Structural Control and Health Monitoring 25(8), e2193 (2018)

Using the full-field, very high-resolution mode shape enables detection of minute, non-visible, damage in a global, completely passive sensing manner, which was previously not possible to achieve.

Y. Yang, C. Dorn, T. Mancini, Z. Talken, J. Theiler, G. Kenyon, C. Farrar, D. Mascarenas

Structural Health Monitoring 17(3), 514-531 (2018)

This work leverages the spatio-temporal separable modal superposition model to perform vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis.

Y. Yang, C. Dorn, T. Mancini, Z. Talken, S. Nagarajaiah, G. Kenyon, C. Farrar, D. Mascarenas

Journal of Sound and Vibration 390, 232-256 (2017)

See video extras

This study explores the feasibility of an alternative approach to this problem - a computational solution in which a limited set of randomly positioned, low-resolution global strain measurements are used to reconstruct the full-field, high-spatial-resolution, two-dimensional (2D) strain field and rapidly detect local damage.

Y. Yang, P. Sun, S. Nagarajaiah, S. Bachilo, RB Weisman

Journal of Sound and Vibration 399, 75-85 (2017)

We develop a novel full-field imaging method for structural dynamic measurement and modal analysis that alleviate the need of structural surface preparation associated with existing vision-based methods and can be implemented in a relatively efficient and autonomous manner with little user supervision and calibration.

Y. Yang, C. Dorn, T. Mancini, Z. Talken, G. Kenyon, C. Farrar, D. Mascarenas

Mechanical Systems and Signal Processing 85, 567-590 (2017)

see Researchgate Project, scope - R&D 100 - Video-Based Dynamic Measurement & Analysis, R&D 100 Award 2018, The Best Paper Award of 2015 United Nations International Conference on Sustainable Development, New York, Mary & Richard Mah Publication Award in Engineering Sciences 2018, 2nd place of 2019 Fedtech, 2nd place of Student Competition in IEEE Resilience Week 2016.

See video extras