Lateral Displacement Estimation Research Articles

A new p-y model for soil-pile interaction analyses in cohesionless soils under monotonic loading

The most widely used analysis method for the laterally loaded pile problem is the Winkler spring approach. Although researchers have proposed nonlinear formulations for the p-y curves, the contribution of the soil nonlinearity has not been thoroughly studied. The main drawback of the current approach is the use of a single stiffness in the p-y formulation. This study investigates the laterally loaded pile problem by employing the pressure-dependent hardening soil model with small-strain stiffness (HS-Small Model), where the degree of soil nonlinearity is better integrated. The parametric analyses are performed on the verified model for various pile and soil properties. A new p-y model is proposed for pile behaviour under monotonic loading based on the numerical analysis results. The model includes the initial stiffness, ultimate soil resistance, and degree of nonlinearity parameters. The validity of the proposed model is demonstrated by simulating a centrifuge and two field tests from the literature. The proposed model accurately accounts for soil nonlinearity and significantly improves the estimation of lateral displacements.

A lane-level localization method via the lateral displacement estimation model on expressway

The gradual proliferation of high-definition (HD) maps has played a pivotal role in the advancement of intelligent vehicles. However, a considerable number of vehicles still face limitations in harnessing HD maps for high-precision navigation due to the absence of lane-level localization information. To address this challenge, this paper presents a lightweight lane-level localization method based on ubiquitous low-cost on-board vehicle cameras and Global Navigation Satellite System (GNSS) receivers. Initially, the line anchor-based feature refinement network is combined with the DeepSort-based lane tracking algorithm to detect and track the lanes in the image sequences. Subsequently, a lateral displacement estimation (LDE) model is proposed to establish the relationship between the vehicle's lateral displacement value in the ego lane and the slope of the lanes on both sides. Moreover, a lateral motion estimation (LME) method is employed to track the motion of the vehicle across multiple lanes. Finally, a lane-level map matching method is proposed based on the GNSS data and lateral displacement information. In the experimental section, three distinct types of dashcams have been installed in a vehicle, and high-precision positioning equipment is utilized as the ground truth for algorithm validation. The experimental results indicate that the proposed method can be effectively deployed in vehicles, enabling lane-level vehicle positioning on expressway. The code has been open-sourced and can be accessed at https://codeocean.com/capsule/6640813/.

Exploiting Mechanics-Based Priors for Lateral Displacement Estimation in Ultrasound Elastography.

Tracking the displacement between the pre- and post-deformed radio-frequency (RF) frames is a pivotal step of ultrasound elastography, which depicts tissue mechanical properties to identify pathologies. Due to ultrasound's poor ability to capture information pertaining to the lateral direction, the existing displacement estimation techniques fail to generate an accurate lateral displacement or strain map. The attempts made in the literature to mitigate this well-known issue suffer from one of the following limitations: 1) Sampling size is substantially increased, rendering the method computationally and memory expensive. 2) The lateral displacement estimation entirely depends on the axial one, ignoring data fidelity and creating large errors. This paper proposes exploiting the effective Poisson's ratio (EPR)-based mechanical correspondence between the axial and lateral strains along with the RF data fidelity and displacement continuity to improve the lateral displacement and strain estimation accuracies. We call our techniques MechSOUL (Mechanically-constrained Second-Order Ultrasound eLastography) and L1 -MechSOUL ( L1 -norm-based MechSOUL), which optimize L2 - and L1 -norm-based penalty functions, respectively. Extensive validation experiments with simulated, phantom, and in vivo datasets demonstrate that MechSOUL and L1 -MechSOUL's lateral strain and EPR estimation abilities are substantially superior to those of the recently-published elastography techniques. We have published the MATLAB codes of MechSOUL and L1 -MechSOUL at https://code.sonography.ai.

Deep estimation of viscoelastic and backscatter quantitative ultrasound

Deep learning is an ideal tool to solve inverse problems, which are often ill-posed and require incorporation of a priori information. We focus on solving two well-known inverse problems that entail the estimation of (1) viscoelastic (VE) and (2) backscatter quantitative ultrasound (QUS). These properties are of critical clinical value but are not currently available from B-mode images. On the first front, we propose a novel technique called PICTURE (Physically Inspired ConsTraint for Unsupervised Regularized Elastography) [Tehrani, Rivaz, MICCAI, (2022)], where we impose additional physics-based constraints on the deformation vector field within our loss function and show that it substantially improves the quality of lateral displacement estimation. We develop semi- and unsupervised methods to tackle the problem of lack of ground truth training datasets in real experiments. On the second front, we propose a novel method for segmenting regions of ultrasound images without any patching based on scatterer number densities [Tehrani et al. TUFFC (2022)]. Our segmentation maps can divide the image into irregular regions of fully developed speckle (FDS) or underdeveloped speckle. When moving from simulation to real datasets, we exploit domain adaptation methods using concepts similar to the popular reference phantom method in QUS.

Theoretical analysis and application research on local toggle energy dissipation device

The toggle-brace-damper system (TBDS) can obviously improve the energy dissipation efficiency of a damper by amplifying its deformation. The small deformation solution is widely used to characterize the amplification capacity of the TBDS. However, the parameters of the small deformation solution are not mutually independent. Furthermore, as the small deformation solution is a constant, it cannot comprehensively characterize the mechanism of the TBDS. These drawbacks hinder a more in-depth study of the TBDS mechanism. In addition, the existing TBDS requires a large building space, which adversely affects the layouts of doors and windows. In view of the problems above, a space-saving local toggle-brace-damper system (LTBDS), as an extended form of the TBDS, is proposed. The displacement amplification factor considering the large deformation effect is derived. The variation law of this amplification factor with the lateral displacement is clarified. The local toggle energy dissipation device (LTEDD), which consists of two identical and symmetrically arranged LTBDSs, is recommended to overcome the LTBDS’ amplification capacity asymmetry. The effects of the geometric parameters on the amplification capacity of the LTEDD are clarified. A geometric optimization method to improve the amplification capacity of the LTEDD is proposed based on the estimation of the maximum lateral displacement of the LTEDD under earthquakes. To estimate the maximum lateral displacement of the LTEDD and calculate the additional damping ratio contributed by the LTEDD damping system, the storey drift utilization ratio is proposed, and the calculation method is derived and verified. Finally, the case analysis verifies the feasibility of the LTEDD and the effectiveness of the optimization method.

Virtual Source Synthetic Aperture for Accurate Lateral Displacement Estimation in Ultrasound Elastography.

Ultrasound elastography (USE) is an emerging noninvasive imaging technique in which pathological alterations can be visualized by revealing the mechanical properties of the tissue. Estimating tissue displacement in all directions is required to accurately estimate the mechanical properties. Despite capabilities of elastography techniques in estimating displacement in both axial and lateral directions, estimation of axial displacement is more accurate than lateral direction due to higher sampling frequency, higher resolution, and having a carrier signal propagating in the axial direction. Among different ultrasound imaging techniques, synthetic aperture (SA) has better lateral resolution than others, but it is not commonly used for USE due to its limitation in imaging depth of field. Virtual source synthetic aperture (VSSA) imaging is a technique to implement SA beamforming on the focused transmitted data to overcome the limitation of SA in depth of field while maintaining the same lateral resolution as SA. Besides lateral resolution, VSSA has the capability of increasing sampling frequency in the lateral direction without interpolation. In this article, we utilize VSSA to perform beamforming to enable higher resolution and sampling frequency in the lateral direction. The beamformed data are then processed using our recently published elastography technique, OVERWIND. Simulation and experimental results show substantial improvement in the estimation of lateral displacements.

Evaluation of liquefaction-induced lateral displacement using Bayesian belief networks

Liquefaction-induced lateral displacement is responsible for considerable damage to engineered structures during major earthquakes. Therefore, an accurate estimation of lateral displacement in liquefaction-prone regions is an essential task for geotechnical experts for sustainable development. This paper presents a novel probabilistic framework for evaluating liquefaction-induced lateral displacement using the Bayesian belief network (BBN) approach based on an interpretive structural modeling technique. The BBN models are trained and tested using a wide-range case-history records database. The two BBN models are proposed to predict lateral displacements for free-face and sloping ground conditions. The predictive performance results of the proposed BBN models are compared with those of frequently used multiple linear regression and genetic programming models. The results reveal that the BBN models are able to learn complex relationships between lateral displacement and its influencing factors as cause-effect relationships, with reasonable precision. This study also presents a sensitivity analysis to evaluate the impacts of input factors on the lateral displacement.

Deformation and Stability Analyses of Hybrid Earth Retaining Structures

Hybrid earth retaining structure (HERS) is an efficient solution for earth retention problems that face spatial constraints. Deformation and stability analyses of the HERS have not been studied rigorously. The present study focuses on the development of predictive equations for the estimation of maximum lateral facing displacement and global factor of safety of the mechanically stabilized earth (MSE) over the soil nail (SN) hybrid retaining (MSE/SN) wall, a category of the HERS. Multiple linear regression is performed using the method of least squares to develop the predictive equations. The regression models for the MSE/SN wall are proposed using the data generated from the finite element model of the MSE wall of heights 6, 8 and 10 m. The adequacy of the predictive equations is verified by evaluating the summary of fit statistics. The failure surface of the MSE/SN wall consists of two parts: (i) a linear surface which propagates internally through the bottom nail of the SN wall starting at the toe of the MSE/SN wall and propagates externally through the remaining height of the SN wall, and (ii) continuation of the linear surface externally behind the reinforcement through the MSE wall. It is concluded that the predominant deformation modes are base sliding, rotation about the base and local bulging of the MSE wall. The failure surface always passes through the soil nails and therefore, it is recommended that the ultimate pullout capacity of the nails should be assessed during the design of the MSE/SN walls.

Synthetic aperture with high lateral sampling frequency for ultrasound elastography.

Ultrasound elastography is a non-invasive technique for detecting pathological alterations in tissue. It is known that pathological alteration of tissue often has a direct impact on its elastic modulus, which can be revealed using elastography. For estimating elastic modulus, we need to estimate both axial and lateral displacement accurately. Current state of the art elastography techniques provide a substantially less accurate lateral displacement field as compared to the axial displacement field. One of the most important factors in poor lateral estimation is a low sampling frequency in the lateral direction. In this paper, we use synthetic aperture beamforming to benefit from its capability of high sampling frequency in the lateral direction. We compare highly sampled data and focused line per line beam formed data by feeding them to our recently published elastography method, OVERWIND [1]. According to simulation and phantom experiments, not only the lateral displacement estimation is substantially improved, but also the axial displacement estimation is improved.

Efficacy Of Kriging Interpolation In Ultrasound Imaging; Subsample Displacement Estimation.

Ultrasound images have an inherently low lateral resolution due to the size of transducers that are used in standard clinical scanners. This makes for low resolution images, as well as imprecise lateral displacement estimation. In speckle tracking, the well known discipline of estimating displacement by tracking pixel movement, lateral interpolation is often used to get subsample accurate displacement estimation. Standard methods for interpolation are known as inverse distance weighting methods, of which the well known cubic interpolation method is a part. Kriging interpolation, however, is a stochastic approach that uses statistical data to calculate interpolated data points as opposed to the purely mathematical methods of more traditional interpolators. This analysis tests the efficacy of one variety of Kriging interpolation, called Simple Kriging, on ultrasound data. Simple Kriging is tested on its accuracy to interpolate a sparse ultrasound image frame, as well as its usefulness in interpolating the correlation map to estimate subsample displacement. The applied bias of the estimation using Simple Kriging is also tested by interpolating the autocorrelation map where displacement is zero. Simple Kriging is an alternative interpolation scheme that could be used with image data and its accuracy is comparable to the accuracy of using the cubic interpolation.

An Iterative Axial and Lateral Ultrasound Strain Estimator Using Subband Division

Conventional ultrasound strain imaging usually only calculates the axial strain. Although axial strain is the main component of two dimensional strain field, lateral displacement and strain estimation can provide additional information of human mechanical properties. Shear strain and Poisson’s ratio can be estimated by using lateral strain estimation technique. Low lateral sampling rate and decorrelation noise of lateral radio frequency (RF) signal caused by axial displacement motion increase the difficulty of lateral strain estimation. Subband division technique is to divide a broadband signal into several narrowband signals. In this paper, the application of subband division technique in axial and lateral strain estimation is studied, and an iterative method for estimating axial and lateral strains is proposed based on subband technique. The subband division of this method is carried out along the axial direction, so that the bandwidth of the lateral subband signal is maintained and the quality of the lateral sub strain image is not reduced. In this paper, the number of subbands is three; the compounded lateral strain image is obtained by superimposing these sub strain images on the average. In each iteration, the temporal stretching technique is used to align the axial and lateral RF signals by using the axial and lateral displacement estimation information, which reduces the decorrelation noise of the RF signals. The length of temporal stretching window decreases with the number of iterations, so as to gradually improve the accuracy of temporal stretching. The phase zero algorithm is used to estimate the axial and lateral displacements. The effectiveness of this method is tested by simulations. The simulation results show that the elastographic signal-to-noise ratio (SNRe) of lateral strain image is increased by about 50%, the elastographic contrast noise ratio (CNRe) of lateral strain image is increased by about 120%, the SNRe of axial strain image is increased by about 4%, the CNRe of axial strain image is increased by 8%, and the signal-to-noise ratio of Poisson’s ratio image is increased by about 40%.

Optimization of transmission and reconstruction parameters in angular displacement compounding using plane wave ultrasound

In ultrasound elastography, plane-wave acquisitions and angular displacement compounding (ADC) are often used and combined to allow high frame rates and to improve accuracy of lateral displacement estimates, respectively. This study investigates the performance of displacement and strain estimation for ADC as a function of; the main-to-grating-lobe-amplitude ratio which decreases as a function of steering angle; plane-wave acquisition and Delay-and-Sum (DaS)-related parameters; and grating-lobe filter cut-off frequency. Three experiments were conducted with a block phantom to test ADC performance for displacement fields of varying complexity: a lateral transducer shift, phantom rotation and phantom deformation. Experiments were repeated for four linear array transducers (pitch-to-lambda ratios between 0.6 and 1.4). Best ADC performance was found for steering angles that resulted in a theoretically derived main-to-grating-lobe-amplitude ratio of 1.7 dB for pure lateral translation and 6 dB for predominately lateral strain or rotation. Temporal filtering to reduce grating lobe signal or shifting of the receive aperture to receive angles below or above the optimal angle, as dictated by the main-to-grating-lobe-amplitude ratio, did not improve results. The accuracy of lateral displacement and strain estimates was improved by apodization in transmission and a dedicated F-number in DaS (0.75) allowing incidence angles within ± 33° in the active aperture. ADC with the optimized settings as found in this study improves the accuracy of displacements and strain estimates up to 80.7% compared to non-ADC. Compared to ADC settings described in current literature, our optimization improved the accuracy by 11.9% to 75.3% for lateral displacement and strain, and by 89.3% to 96.2% for rotation. The accuracy of ADC in rotation seemed to depend highly on plane-wave and DaS-related parameters which may explain the major improvement compared to settings in current literature. The overall improvement by optimized ADC was statistically significant compared to non-ADC (p = 0.003) and literature (p = 0.002).

Accurate and Precise Time-Delay Estimation for Ultrasound Elastography With Prebeamformed Channel Data.

Free-hand palpation ultrasound elastography is a noninvasive approach for detecting pathological alteration in tissue. In this method, the tissue is compressed by a handheld probe and displacement of each sample is estimated, a process which is also known as time-delay estimation (TDE). Even with the simplifying assumption that ignores out of plane motion, TDE is an ill-posed problem requiring estimation of axial and lateral displacements for each sample from its intensity. A well-known class of methods for making elastography a well-posed problem is regularized optimization-based methods, which imposes smoothness regularization in the associated cost function. In this article, we propose to utilize channel data that have been compensated for time gain and time delay (introduced by transmission) instead of postbeamformed radio frequency (RF) data in the optimization problem. We name our proposed method Channel data for GLobal Ultrasound Elastography (CGLUE). We analytically derive bias and variances of TDE as functions of data noise for CGLUE and Global Ultrasound Elastography (GLUE) and use the Cauchy-Schwarz inequality to prove that CGLUE provides a TDE with lower bias and variance error. To further illustrate the improved performance of CGLUE, the results of simulation, experimental phantom, and ex-vivo experiments are presented.

Locally optimized correlation-guided Bayesian adaptive regularization for ultrasound strain imaging

Ultrasound strain imaging utilizes radio-frequency (RF) ultrasound echo signals to estimate the relative elasticity of tissue under deformation. Due to the diagnostic value inherent in tissue elasticity, ultrasound strain imaging has found widespread clinical and preclinical applications. Accurate displacement estimation using pre and post-deformation RF signals is a crucial first step to derive high quality strain tensor images. Incorporating regularization into the displacement estimation framework is a commonly employed strategy to improve estimation accuracy and precision. In this work, we propose an adaptive variation of the iterative Bayesian regularization scheme utilizing RF similarity metric signal-to-noise ratio previously proposed by our group. The regularization scheme is incorporated into a 2D multi-level block matching (BM) algorithm for motion estimation. Adaptive nature of our algorithm is attributed to the dynamic variation of iteration number based on the normalized cross-correlation (NCC) function quality and a similarity measure between pre-deformation and motion compensated post-deformation RF signals. The proposed method is validated for either quasi-static and cardiac elastography or strain imaging applications using uniform and inclusion phantoms and canine cardiac deformation simulation models. Performance of adaptive Bayesian regularization was compared to conventional NCC and Bayesian regularization with fixed number of iterations. Results from uniform phantom simulation study show significant improvement in lateral displacement and strain estimation accuracy. For instance, at 1.5% lateral strain in a uniform phantom, Bayesian regularization with five iterations incurred a lateral strain error of 104.49%, which was significantly reduced using our adaptive approach to 27.51% (p < 0.001). Contrast-to-noise (CNRe) ratios obtained from inclusion phantom indicate improved lesion detectability for both axial and lateral strain images. For instance, at 1.5% lateral strain, Bayesian regularization with five iterations had lateral CNRe of −0.31 dB which was significantly increased using the adaptive approach to 7.42 dB (p < 0.001). Similar results are seen with cardiac deformation modelling with improvement in myocardial strain images. In vivo feasibility was also demonstrated using data from a healthy murine heart. Overall, the proposed method makes Bayesian regularization robust for clinical and preclinical applications.

Actuator-assisted Subpitch Translation-capable Transducer for Elastography: Preliminary Performance Assessment.

In conventional linear array (CLA)-based elastography tissue compression in one direction (e.g., axial) leads to an expansion in all other directions (lateral, elevation). Therefore, the estimation of the lateral displacements and strains may provide additional information on the tissue mechanical properties. However, these are not exploited fully due to the inherent limitation in lateral sampling. Recently, a method named actuator-assisted beam translation (ABT) was demonstrated to address this issue, wherein the focused beam was translated at subpitch locations using an external bench-top setup. However, because such bench-top setup may be impractical for routine clinical use, an ultrasound transducer was customized to have an internal actuator. The performance of the customized transducer was studied through experiments on phantoms for rotation elastography application, which requires precise lateral displacement estimation. Furthermore, the results obtained from ABT was compared against the currently practiced spatial displacement compounding (SDC) method, which is known to yield better quality lateral displacement estimates than conventional approaches. The results show that the ABT method yields a full-width half-maximum (FWHM) value, taken from the lateral profile across a point scatterer, which is 65% and 24% smaller than that obtained using CLA and SDC methods, respectively. Furthermore, the contrast-to-noise ratio (CNR) estimated from rotation elastogram obtained using ABT method is better by 300% and 35% compared with that obtained by using CLA and SDC methods, respectively. Furthermore, the results demonstrate an additional advantage of having larger field of view (FoV) for the ABT method compared with spatial compounding approach.

Computational estimation of lateral pile displacement in layered sand using experimental data

In this research, 150 experimental tests were conducted on a series of derived single piles embedded in sand layer. The sand samples were reconstructed with the pluviation method in the two relative densities of 30% (loose state) and 75% (dense state). The pile lateral displacement values were recorded subjected to the combination of the lateral and vertical static loads until failure occurred. In addition, for the estimation of lateral displacement of piles, different Multi-Layer Perceptron Artificial Neural Network models (MLP-ANN) were created and tested. The experimental results showed that when the driving energy increased from 2 J to 4 J, the piles lateral displacement values increased by about 20%. Besides, the measured lateral displacement values of shorter piles were significantly lower compared to the longer piles at the same loading conditions. In addition, the results of computational efforts indicated that the optimum MLP-ANN model presented satisfactory results in the terms of mean square error and regression indices. Moreover, sensitivity analysis showed that pile length and driving energy were the most influential factors on the estimation of lateral displacement recordings.

Diverging beam with synthetic aperture technique for rotation elastography: preliminary experimental results

Rotation Elastogram (RE) is a 2D spatial distribution map of the estimated local rigid-body rotation undergone by a target when subjected to an external compression, which is one of the recent variants in elastographic imaging. A recent study has shown that inclusion-contrast in RE is independent of inclusion-background modulus contrast and thus may be helpful in distinguishing between barely-stiff benign and malignant lesions. However, estimation of quality RE requires not only precise axial displacement estimates but also lateral displacement estimates. The widely used conventional focused beamforming technique using linear array (CFB-LA) provides better lateral resolution only over the depth of focus, which still results in poorer quality lateral displacement estimates compared to the axial displacement estimates. As an alternative to overcome this depth-dependent lateral resolution and obtain an improved lateral resolution, synthetic aperture-based approaches have been proposed in literature. Recently, we developed a synthetic aperture-based method, diverging beam with synthetic aperture technique (DB-SAT) that was aimed to not only reduce the ultrasound system complexity, but also provide improved lateral resolution throughout the depth of imaging and at higher frame-rate than that is possible in CFB-LA. In this paper, we report the preliminary experimental findings on the use of DB-SAT on RE and compare the resultant image quality against that obtained using often-employed CFB-LA and the synthetic transmit aperture (STA) technique. The investigation was done on tissue-mimicking phantoms and using contrast-to-noise ratio (CNR) as the metric for performance evaluation. The estimated CNR values from the REs obtained using CFB-LA, STA, and DB-SAT were 2.69 ± 0.81, 1.35 ± 0.22, and 14.71 ± 9.83, respectively, for inclusion present at 55 mm depth. The obtained results clearly demonstrated that the quality of RE can be improved significantly, especially at larger depth, using DB-SAT compared to that obtained using CFB-LA and STA technique.

Effects of the use of the surface spectrum of a specific region on seismic performances of R/C structures

The present study pertains to the estimation of the significance of the use of the local acceleration spectrum of a region rather than the design spectra based on the linear time-history analyses of real structures in the region. The study was realized in three stages: (1) development of the target spectrum of the bedrock level accounting for the possible devastative earthquake, the distance of the region to the main fault and the earthquake magnitude; (2) establishment of the surface (local) spectrum of the region based on the bedrock spectrum and soil profile; and (3) the linear time-history analyses of the existing R/C building structures from the studied region using earthquake records that were produced by spectral matching according to the site-depended local spectrum and the design spectra of the seismic code. For this objective, the city of Kirikkale, located in mid-Anatolia, was adopted as the study region owing to the high seismic risk of the region and the presence of abundant poorly designed and poorly or non-engineered structures. The analyses indicated that the use of the local spectrum instead of the code design spectra is rather crucial in R/C structures with irregular story plans. In addition, structures with high eccentricity were obtained to be rather affected from earthquake motions compared to those with regular story plan. The use of the code design spectra provides closer and more conservative base shear, base overturning moment and lateral displacement estimates in R/C structures with regular story plans.

Strategies to Obtain Subpitch Precision in Lateral Motion Estimation in Ultrasound Elastography.

In elastography, conventional linear array (CLA)-based RF data acquisition provides more accurate displacement measurements in the direction of beam propagation (axial direction) when compared to the perpendicular direction (lateral). Obtaining good quality lateral displacement estimates in ultrasound (US) elastography will lead to several benefits such as obtaining accurate inverse solutions, improving shear strain elastogram quality, getting good quality poroelastograms, and obtaining reliable rotation elastograms. For accomplishing high-precision lateral displacement estimation (LDE), one of the popular methods is by interpolating additional A-lines in between neighboring RF A-lines. We describe a method wherein true RF A-lines (not interpolated) are acquired and augmented at subpitch locations using CLA transducer, instead of interpolating the data, and using this new frame data for further image formation and/or processing to yield better lateral resolution and LDE. We demonstrate the proposed method by translating the US beam of CLA transducer in subpitch range by the following two approaches: 1) actuator-assisted beam translation and 2) electronic translation of subaperture of a CLA by activating odd and even number of consecutive elements sequentially, referred to as electronic beam translation. The performances of the different methods were studied through simulations and experiments on phantoms. The results demonstrate that these methods yield better quality LDE compared to those obtained from interpolation of RF A-lines. These methods may provide affordable ways to obtain subpitch precision LDE using CLA.

Multi-type sensor placement and response reconstruction for building structures: Experimental investigations

Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes: the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.