Review of machine-vision based methodologies for displacement measurement in civil structures

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional displacement sensors in instrumentation cost, installation efforts and measurement capacity in terms of frequency range and spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like: system development and improvement, the viability on field applications and the potential for structural condition assessment. The main contribution of this paper is to present a literature review of vision-based displacement measurement, from the perspectives of methodologies and applications. Video processing procedures in this paper are summarised as a three-component framework, camera calibration, target tracking and structural displacement calculation. Methods for each component are presented in principle, with discussions about the relative advantages and limitations. Applications in the two most active fields: bridge deformation and cable vibration measurement are examined followed by a summary of field challenges observed in monitoring tests. Important gaps requiring further investigation are presented e.g. robust tracking methods, non-contact sensing and measurement accuracy evaluation in field conditions

Vision-based systems for structural deformation measurement: case studies

This is the author accepted manuscript. The final version is available from Thomas Telford (ICE Publishing) via the DOI in this record.Vision-based systems offer a promising way for displacement measurement and receive increased attention in civil structural monitoring. However, the working performance of vision-based systems, especially the measurement accuracy and the robustness to different field conditions is not fully understood. This study reports three cases studies of vision-based monitoring tests including one in a laboratory, one on a short-span bridge and one on a long-span bridge. The tracking accuracy is quantified in laboratory conditions in the range of 0.02 pixel to 0.20 pixel depending on the target patterns as well as the tracking method selected. The measurement performance under several field challenges are investigated including long-range measurement (e.g. camera-to-target distance at 710 m), low-contrast target patterns, changes of target patterns and changes in lighting conditions. Three representative tracking methods for the video processing, i.e. correlation-based template matching, Lucas Kanade (LK) optical flow estimation and scale-invariant feature transform (SIFT) were used for analysis, indicating their advantages and shortcomings for field measurement. One of the main observations in field application is that changes in lighting conditions might cause some low-frequency measurement error that could be misunderstood without the prior knowledge about structural loading conditions

Strategies for aeroelastic parameter identification from bridge deck free vibration data

Author's manuscript version. The version of record is available from the publisher via: doi:10.1016/S0167-6105(01)00091-5. Copyright © 2001 Elsevier Science Ltd. All rights reserved.Several techniques for identification of aerodynamic derivatives (ADs) from free vibration test data are compared using simulated data and test data obtained from wind tunnel tests. These identification methods include system identification from one degree of freedom or two degree of freedom response to either transient excitation or to turbulent buffeting. The experimental and analytical difficulties involved in each method are highlighted and suggestions made for the best approach to determination of ADs in both model and full-scale studies. Time domain methods using step relaxation provided the best results as long as air-flow turbulence does not cause severe signal to noise ratio problems with the free vibration decay. When, as in full-scale, the turbulence is the primary forcing function, time domain and frequency domain methods can be used to recover the full set of ADs concerning vertical and torsional respons

Numerical modelling of plasticity induced by transcranial magnetic stimulation

We use neural field theory and spike-timing dependent plasticity to make a simple but biophysically reasonable model of long-term plasticity changes in the cortex due to transcranial magnetic stimulation (TMS). We show how common TMS protocols can be captured and studied within existing neural field theory. Specifically, we look at repetitive TMS protocols such as theta burst stimulation and paired-pulse protocols. Continuous repetitive protocols result mostly in depression, but intermittent repetitive protocols in potentiation. A paired pulse protocol results in depression at short (∼ 100 ms) interstimulus intervals, but potentiation for mid-range intervals. The model is sensitive to the choice of neural populations that are driven by the TMS pulses, and to the parameters that describe plasticity, which may aid interpretation of the high variability in existing experimental results. Driving excitatory populations results in greater plasticity changes than driving inhibitory populations. Modelling also shows the merit in optimizing a TMS protocol based on an individual’s electroencephalogram. Moreover, the model can be used to make predictions about protocols that may lead to improvements in repetitive TMS outcomes

Power Spectral-Density Model for Pedestrian Walking Load

This is the author accepted manuscript. The final version is available from American Society of Civil Engineers via the DOI in this recordIntensive vibrations may occur in slender structures like footbridges and long-span floors due to movement of pedestrians. Problems are usually treated in the time domain as Fourier series models of the forcing function, but most methods have disadvantages of neglecting the stochastic character of human walking, being computationally inefficient for random vibration analysis, and overestimating responses in the case of resonance. Meanwhile, frequency-domain models of other types of structural loading are efficient while being a more acceptable approach widely adopted for dealing with stochastic response problems. Hence, an experiment-based power spectral-density (PSD) model normalized to walking frequency and order of harmonic is proposed. To construct this model, 1,528 individual walking-load time histories were collected from an experiment on a rigid floor. These records were then linked to obtain a smaller number of longer samples for a good frequency resolution in spectral analysis. Using the linked samples and for a frequency normalized to mean walking frequency, PSD models in the range 1±0.05 for the harmonic and subharmonic are suggested as a Gaussian mixture with eight model parameters. Via the stationary and nonstationary stochastic vibration theory, the proposed model is used to predict the structural response in terms of root-mean square and peak of acceleration. The framework is finally tested via field measurements demonstrating applicability in practical design work.National Natural Science Foundation of ChinaState Key Laboratory for Disaster Reduction of Civil Engineerin

Parameter identification of pedestrian's spring-mass-damper model by ground reaction force records through a particle filter approach

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The spring-mass-damper (SMD) model with a pair of internal biomechanical forces is the simplest model for a walking pedestrian to represent his/her mechanical properties, and thus can be used in human-structure-interaction analysis in the vertical direction. However, the values of SMD stiffness and damping, though very important, are typically taken as those measured from stationary people due to lack of a parameter identification methods for a walking pedestrian. This study adopts a step-by-step system identification approach known as particle filter to simultaneously identify the stiffness, damping coefficient, and coefficients of the SMD model's biomechanical forces by ground reaction force (GRF) records. After a brief introduction of the SMD model, the proposed identification approach is explained in detail, with a focus on the theory of particle filter and its integration with the SMD model. A numerical example is first provided to verify the feasibility of the proposed approach which is then applied to several experimental GRF records. Identification results demonstrate that natural frequency and the damping ratio of a walking pedestrian are not constant but have a dependence of mean value and distribution on pacing frequency. The mean value first-order coefficient of the biomechanical force, which is expressed by the Fourier series function, also has a linear relationship with pacing frequency. Higher order coefficients do not show a clear relationship with pacing frequency but follow a logarithmic normal distribution.The authors would like to acknowledge the financial support provided by National Natural Science Foundation of China (51478346, 51778465) and State Key Laboratory for Disaster Reduction of Civil Engineering (SLDRCE14-B-16)

A spectral density approach for modelling continuous vertical forces on pedestrian structures due to walking

Peer reviewedPreprin

An Estimation of Pedestrian Action on Footbridges Using Computer Vision Approaches

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData Availability Statement: The datasets generated for this study are available on request to the corresponding author.Vibration serviceability of footbridges is important in terms of fitness for purpose. Human-induced dynamic loading is the primary excitation of footbridges and has been researched with traditional sensors, such as inertial sensors and force plates. Along with the development of computer hardware and algorithms, e.g., machine learning, especially deep learning, computer vision technology improves rapidly and has potential application to the problem. High precision pedestrian detection can be realized with various computer vision methods, corresponding to different situations or demands. In this paper, two widely recognized computer vision approaches are used for detecting body center of mass and ankle movement, to explore the potential of these methods on human-induced vibration research. Consumer-grade cameras are used without artificial markers, to take videos for further processing and wearable inertial sensors were used to validate and evaluate the computer vision measurements

Optimised ambient vibration testing of long span bridges

Eurodyn 2017, 2017-09-10 - 2017-09-13, Rome,This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Vibration testing of long span bridges is becoming a commissioning requirement. Long span bridges represent the extreme end of experimental capability, with challenges for logistics and access (due to length and location), instrumentation (due to frequency range, resolution and physical separation of accelerometers) and system identification (because of the extreme low frequencies). Similar challenges apply to other extreme structures such as tall buildings, masts, offshore lighthouses and extended geotechnical structures stretching technology requirements for both instrumentation and signal interpretation. A solution for instrumentation is autonomous ‘wireless’ recorders. The problem with signal interpretation is the reliability of the modal parameter estimates that is particularly challenged with low frequency modes, which ‘third generation’ operational modal analysis procedures offer using Bayesian approaches. The paper describes a preliminary exercise combining both these technologies in readiness for testing two very large bridges, one in China and one in Scotland.The research was funded by EPSRC grant EP/N017897/1 and EP/N01780

Deformation monitoring of a simply supported railway bridge under varying dynamic loads

This is the author accepted manuscript. The final version is available from IABMAS via the link in this recordStructural health monitoring is a useful tool for evaluating the condition of bridges, with permanent systems installed on bridges which form vital links on the major transport network. The economic cost of the monitoring systems limits their installation on smaller bridges which make up the wider transport network. A short-term monitoring system can be quickly installed and adjusted to suit the requirements of individual bridges. These systems are ideal for rural regions with a high number of single span bridges on isolated road and rail networks. This report will review a single span bridge on a private heritage railway under loading from passing steam engines, including the Flying Scotsman. Acceleration data are used to determine the rotations and deflections of the bridge deck. To verify the data, deflection measurements at mid-span were recorded using a video-based measurement system. The deflection measurements from the accelerometers correlate with the video imagery measurements