Article
Engineering, Multidisciplinary
Jian Zhou, Bence Kato, Ying Wang
Summary: Compressive Sensing (CS) provides a solution for modal analysis with fewer/compressed measurements. However, operational modal analysis using compressed measurements has not been studied. This work proposes a new approach that uses CS to identify modal parameters from compressed measurements with prior information. Numerical and experimental studies demonstrate its effectiveness in accurately analyzing damped structures under different vibration conditions. The proposed approach can be a practical tool for efficient and accurate online structural health monitoring.
Article
Engineering, Mechanical
Yinan Miao, Yeseul Kong, Hyeonwoo Nam, Seunghwan Lee, Gyuhae Park
Summary: Inspired by thermal imaging, we have developed a phase-based vibration imaging technique that utilizes marker-free full-field displacement measurements to determine vibrational energy distribution and possibly vibration parameters. Accurate sub-pixel level measurements are achieved by performing a full-field phase-based optical flow with three new advancements. This technique has been demonstrated through numerical experiments and experimental validation, proving its effectiveness in imaging vibrations.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Civil
Michael Styrk Andersen
Summary: This paper discusses observations of vortex shedding on the wedge-shaped Gjemnessund Bridge Box girder during the period from August 2019 to February 2020. Operational fluid modal analysis identifies oscillations in wake flow, even though vortex shedding is not prominently visible in lift and response spectra. Characteristic vortex shedding fluid mode shapes are recognized for records at Reynolds numbers ranging from 500,000 to 2,000,000, with simultaneous identification of Strouhal numbers. Comparison with wind tunnel tests of a 1:30 scaled section model shows a Reynolds number dependency of the Strouhal number.
ENGINEERING STRUCTURES
(2021)
Article
Acoustics
Olivier Robin, Patrick O'Donoughue, Alain Berry, Vincent Farley, Kishan Prithipaul
Summary: This study conducted full-field vibration measurements on a cantilever beam using deflectometry technique in visible and infrared spectra, showing promising performances and potential applications in various fields.
Article
Engineering, Civil
Qingfang Lv, Yujie Lu, Ye Liu
Summary: This study designed and constructed a composite floor lifted by carbon fiber-reinforced polymer cables for small-scale exhibitions, and conducted field measurements to study its dynamic characteristics and human-induced vibration serviceability. The results showed that the floor's vibration responses were influenced by factors such as pedestrian number, walking frequency, and vibration constraints at different positions.
Article
Engineering, Civil
Y. M. Zhu, Q. Sun, C. Zhao, S. T. Wei, Y. Yin, Y. H. Su
Summary: The operational modal analysis (OMA) of two types of ultra-high-voltage (UHV) transmission towers was conducted using a fast Bayesian FFT method. The dynamic properties of the towers were obtained and compared, and the stiffness of the tension tower was found to be relatively higher. The results can provide a reference for wind resistance design of UHV transmission towers.
ENGINEERING STRUCTURES
(2023)
Article
Engineering, Multidisciplinary
Jian Zhou, Sheng Yu, Hongwei Li, Ying Wang, Jinping Ou
Summary: This study proposes an automated CS-based operational modal analysis (OMA) method, called Automated Sparse Decomposition (ASD), which gradually eliminates noise and false modes to achieve automated modal identification based on compressed measurements. A search strategy with both extensive and intensive search stages is proposed to improve the search resolution with low computational costs. Experimental data on an offshore wind turbine model and real-world monitoring data from a cable-stayed bridge are analyzed to demonstrate the effectiveness of the proposed method. The results show that the proposed ASD method has comparable identification accuracy to state-of-art CS-based methods.
Article
Computer Science, Artificial Intelligence
Pei Zhang, Chutian Wang, Edmund Y. Lam
Summary: This paper proposes a new graph representation for event data and couples it with a Graph Transformer for accurate neuromorphic classification. Results show that this approach performs well in challenging realistic situations with limited computational resources and a small number of events.
Article
Construction & Building Technology
Siti Shahirah Saidin, Sakhiah Abdul Kudus, Adiza Jamadin, Muhamad Azhan Anuar, Norliyati Mohd Amin, Zainah Ibrahim, Atikah Bt Zakaria, Kunitomo Sugiura
Summary: The advancement of technology has made accurate and dependable monitoring of bridge infrastructure conditions increasingly important. This study focuses on using operational modal analysis and structural health monitoring to determine the dynamic characteristics of bridge structures and improve their accuracy through numerical finite element model updating.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Yuankun Lin, Pinbo Huang, Zihao Ni, Shengli Xie, Yulei Bai, Bo Dong
Summary: This study developed a method using a single monochrome high-speed camera to measure both in-plane and out-of-plane full-field vibrations without sacrificing spatial resolution. The method extracts the out-of-plane displacement field from the measured virtual in-plane strains using a high-speed camera and a 2D digital image correlation (2D-DIC) algorithm. The in-plane displacement field is then retrieved after eliminating the motion-induced virtual component. Validation tests and experiments showed good agreement with reference values, indicating the effectiveness of the proposed high-speed 2D-DIC method.
APPLIED SCIENCES-BASEL
(2023)
Article
Construction & Building Technology
Mengmeng Sun, Qiusheng Li, Xuliang Han
Summary: This paper presents a combined operational modal analysis scheme to estimate the long-term modal properties of civil structures. The effectiveness and accuracy of the scheme are validated through numerical simulation and field measurement. The study also investigates the effects of environmental and operational variations on the modal properties of a supertall building.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Engineering, Civil
K. Luis Garcia, K. Maes, V. Elena Parnas, G. Lombaert
Summary: This paper presents the results of an operational modal analysis on a self-supporting antenna mast, highlighting two particular challenges in the analysis. By solving these issues, five bending modes are identified, which are very close to the results predicted by a detailed finite element model. This confirms the validity of such detailed finite element models for the assessment of lattice towers' dynamic response under wind loading.
JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
(2021)
Article
Engineering, Civil
Qiang-Ming Zhong, Shi-Zhi Chen, Zhen Sun, Lu-Chao Tian
Summary: This study proposes an applicable fully automatic OMA method by comparing clustering algorithms, and investigates its performance through numerical analysis and measured data from an actual bridge. The results demonstrate that this method functions well in the tested scenarios and has potential for wide application in actual engineering.
ENGINEERING STRUCTURES
(2023)
Article
Construction & Building Technology
Zachariah Wynne, James R. Hopgood, Tim Stratford, Thomas P. S. Reynolds
Summary: Filtering in modal analysis introduces artefacts that corrupt the accuracy of frequency and damping estimates. This paper presents a technique of trimming noise from unfiltered correlation functions to improve estimation accuracy. Experimental results show significant reduction in errors for frequency and damping estimates.
STRUCTURAL CONTROL & HEALTH MONITORING
(2022)
Article
Engineering, Mechanical
Runyu Lu, Md Rifat Shahriar, Pietro Borghesani, Robert B. Randall, Zhongxiao Peng
Summary: Transmission error (TE) is an important measurement for gear monitoring and quality control, especially at low speeds. Geometric transmission error (GTE) is closely related to geometric tooth-profile anomalies, while the difference between GTE and static transmission error (STE) provides information on meshing stiffness. A cepstrum-based operational modal analysis method can be used to reconstruct equivalent STE or GTE from a single dynamic transmission error (DTE) measurement at moderate/high speeds.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Multidisciplinary
Homin Song, Yongchao Yang
Summary: This article introduces a noncontact super-resolution guided wave array imaging approach based on deep learning, which can visualize subwavelength defects in plate-like structures. By utilizing two fully convolutional networks to globally detect defects and locally resolve fine structural details, the proposed method achieves the localization and visualization of subwavelength defects.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Article
Engineering, Multidisciplinary
David D. L. Mascarenas, JoAnn P. Ballor, Oscar L. McClain, Miranda A. Mellor, Chih-Yu Shen, Brian Bleck, John Morales, Li-Ming R. Yeong, Benjamin Narushof, Philo Shelton, Eric Martinez, Yongchao Yang, Alessandro Cattaneo, Troy A. Harden, Fernando Moreu
Summary: This article introduces the use of emerging augmented reality technology to enhance structural infrastructure inspection and awareness, enabling data to be collected at higher resolutions for comprehensive and high-resolution 3D measurements. Augmented reality can be applied to high-risk infrastructure and improve structural awareness.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Article
Engineering, Multidisciplinary
HweeKwon Jung, Andre Green, John Morales, Moises Silva, Bridget Martinez, Alessandro Cattaneo, Yongchao Yang, Gyuhae Park, Jarrod McClean, David Mascarenas
Summary: Modern infrastructure systems have both cyber and physical aspects, making them vulnerable to cyber-attacks. A protocol has been developed to authenticate the origin of imagery data, and a computer vision approach based on mutual information has been presented for damage detection in images.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Article
Acoustics
Shanwu Li, Yongchao Yang
Summary: This study presents a recurrent neural network (RNN) framework with an adaptive training strategy for long-time prediction of future states in nonlinear dynamical systems. By explicitly incorporating multi-step prediction and error accumulation into model training, the model robustness is improved. Experiments on Duffing oscillators demonstrate the advantages and limitations of this approach.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Acoustics
Lele Luan, Jingwei Zheng, Ming L. Wang, Yongchao Yang, Piervincenzo Rizzo, Hao Sun
Summary: This study developed a deep learning framework based on convolutional neural networks for real-time extraction of full-field subpixel structural displacements from videos, overcoming the limitations of traditional displacement sensing techniques. Results showed that the trained networks have generalizability to accurately extract full-field subpixel displacements for pixels with sufficient texture contrast.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Engineering, Mechanical
Shanwu Li, Yongchao Yang
Summary: This study presents a hierarchical deep learning approach to identify reduced-order models of nonlinear dynamical systems from measurement data only, including nonlinear normal modal subspace and associated dynamics. The approach is validated on unforced and forced nonlinear systems, demonstrating efficient dimensional truncation for optimal low-dimensional ROM. Performance and applicability of this approach are discussed in detail.
NONLINEAR DYNAMICS
(2021)
Article
Engineering, Civil
Debasish Jana, Satish Nagarajaiah, Yongchao Yang, Shunlong Li
Summary: Stay-cables in cable-stayed bridges are vital components that require continuous real-time performance monitoring. Wireless sensors provide accurate measurement without wiring cost, but data loss during transmission may interrupt real-time monitoring, which can be addressed through data processing. Monitoring cable health using multiple sensors reduces estimation errors and a proposed framework utilizes compressive sensing algorithm and Blind Source Separation Technique to estimate real-time tension effectively.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2022)
Article
Physics, Applied
Wentao Wang, Yongchao Yang
Summary: This study presents an approach to generate a selective single-mode guided wave in plate-like structures by utilizing the directionality of a d(36) type piezoelectric wafer and the symmetry of fundamental guided wave modes. The proposed method provides selective, directional single-mode guided waves for actuation and sensing, with the use of in-phase or out-of-phase applied electrical fields to produce SH0 or A(0) modes, respectively. Numerical simulations and laboratory experiments were conducted to validate the theoretical development of the approach.
APPLIED PHYSICS LETTERS
(2022)
Article
Engineering, Mechanical
Moises Felipe Silva, Andre Green, John Morales, Peter Meyerhofer, Yongchao Yang, Eloi Figueiredo, Joao C. W. A. Costa, David Mascarenas
Summary: Video-based measurement is increasingly important in modal analysis and structural sensing technologies. Recent research has explored the use of laser point cloud data for 3D mapping of scenes and structures. This paper proposes an efficient and high-resolution 3D structural dynamic identification/modal analysis approach using point cloud data.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Construction & Building Technology
Debasish Jana, Satish Nagarajaiah, Yongchao Yang
Summary: This paper presents a framework that uses video-based measurement as multiple sensors to reduce the estimation error in determining the real-time cable tension. The proposed algorithm is validated on an actual cable-stayed bridge and compared with conventional methods, showing smaller estimation error and significant potential in the field of structural health monitoring.
STRUCTURAL CONTROL & HEALTH MONITORING
(2022)
Article
Acoustics
Homin Song, Yongchao Yang
Summary: An accelerated noncontact guided wave array imaging method is proposed in this study, which reconstructs dense guided wave array data from sparse scanning measurements and successfully detects and locates defects within a composite plate.
Article
Environmental Sciences
Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Summary: This study explores the application of deep learning in predicting lake surface temperature in the Laurentian Great Lakes. The results show that the LSTM neural network, trained with limited data, provides consistent and reliable performance in capturing the spatiotemporal variabilities of lake temperature. The analysis using explainable artificial intelligence techniques reveals that air temperature is the most influential feature in the LSTM prediction. Furthermore, integrating the hydrodynamic modeling and deep learning results enhances prediction accuracy.
Article
Optics
Shanwu LI, Yongchao Yang
Summary: The sensitivity of incoherent optical methods for displacement measurements is limited by the bit depth of the digital camera. However, the use of random noise in the imaging system can overcome the sensitivity limit.
Article
Materials Science, Characterization & Testing
Homin Song, Yongchao Yang
Summary: A Bayesian deep learning approach is proposed to quantify and interpret uncertainties in super-resolution guided wave array imaging. The approach successfully quantifies two types of uncertainties: aleatoric uncertainty inherent in the data and epistemic uncertainty associated with the Bayesian deep learning model.
NDT & E INTERNATIONAL
(2023)
Article
Engineering, Mechanical
Charle Dorn, Yongchao Yang
Summary: Identifying modal parameters is crucial for modal analysis and structural dynamics modeling based on vibration measurements. This study presents an approach that quantifies spatial features of high-resolution response measurements to enable automated identification of modal parameters. It is found that the local variances of the physical and spurious mode shapes are significantly different, especially with high spatial resolution measurements, allowing for effective identification of physical modes from spurious modes.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)