Accurate Displacement Research Articles

Accurate droplet depth displacement measurement with time-resolved astigmatic interferometric particle imaging.

The astigmatic interferometric particle imaging (AIPI) model reveals that the fringe orientation shifts with droplet depth displacement, and their relationships are quantitatively formulated. The depth displacement is directly evaluated from the relative angular shift of the fringes with angular cross power spectral density, and this algorithm isolates the uncertainty of droplet depth position from depth displacement. Proof-of-concept experiments on micrometer-sized transparent droplets with a 5 kHz AIPI system demonstrates that droplet three-dimensional (3D) trajectories are accurately obtained with the accuracy of depth displacement up to tens of micrometers, improving an order of magnitude from hundreds of microns in a traditional Lagrangian framework by comparing droplet depth positions.

Accuracy of phase-based optical flow for vibration extraction

In this paper, phase-based optical flow done using the complex steerable pyramid is evaluated to quantify upper and lower bounds of accurate pixel displacement extraction. The objective is to understand how typical image parameters affect these bounds and to determine if phase-based optical flow alone is effective and sufficient to extract vibrations. Across the current literature, phase-based optical flow is largely treated as a pre-processing step for more traditional optical methods, and its ability to extract motions rather than magnify them seems to have been largely overlooked. Rather than compound methodologies, phase-based optical flow is evaluated as a motion extraction tool in its own right in both a synthetic and experimental context. The evaluation provides expected bounds given ideal image parameters as well as a metric to adjust these bounds for a general scenario. Beyond these results, previous evaluations specific to phase-based optical flow are addressed and resulting bounds are compared. Due to dramatic effects caused by the image parameters, rules of thumb specific to this type of processing are also discussed.

Multi-probe linear fitting and time of arrival linear correction method to analyze blade vibration based on blade tip timing without once-per-revolution

Blade vibration monitoring can ensure the safe operation of aero-engine rotor blades. Among the methods of blade vibration monitoring, Blade Tip Timing (BTT) method has attracted more and more attention because of its advantages of non-contact measurement. However, it is difficult to install the Once-Per-Revolution (OPR) probe in the confined space of aero-engine, and the failure and instability of the OPR signal will reduce the reliability of the blade vibration analysis results, which directly affects the accuracy of the blade vibration parameters identification. The Multi-Probe linear fitting and Time of Arrival (ToA) Linear Correction method based on the BTT (MP-LC-BTT) without OPR is proposed to reduce the errors of single probe linear fitting method for blade vibration displacement analysis. The proposed method can also correct the calculation error of blade vibration displacement due to the nonlinear change of rotation speed, which can improve the analysis accuracy of the blade vibration displacement. A new blade vibration model conforming to the actual vibration characteristics is established, and the effectiveness of the proposed method is verified by numerical simulation. Finally, the reliability and accuracy of the MP-LC-BTT method have been verified by the experiments which include two high-speed blade test-benches and an industrial axial fan. This method can be used in the actual aero-engine monitoring instead of the BTT method with OPR.

Finite - Element Analysis of Shear - Connection Shear - Out Fracture Performance

Abstract This paper presents the finite-element analysis of the shear-connection shear-out fracture (SOF) performance, covering the prediction of the SOF displacement at fracture and surface and through-thickness fracture failure analyses. The appearance of fracture on the connected plate surface, taken, as the SOF initiation in published literature is not the accurate SOF initiation. This work proposes using SOF displacement or fracture strain as a displacement or strain-based fracture limit state for shear connections that exhibit the SOF. The displacement or strain at fracture initiation at the middle-thickness of the connected plate represents the accurate SOF displacement or strain at fracture.

A modal displacement-based design method for irregular building frames equipped with elastomeric bearings

In this study, a Modal Displacement-Based Design (MDBD) method for seismic design of base isolated building frames with vertical irregularity has been proposed using principles of the Direct Displacement Based Design method and evaluated through the Nonlinear Time History Analysis (NTHA). The structural models used here are regular and irregular building frames equipped with elastomeric bearings. By comparing the results of the proposed MDBD method with those of the NTHA, it can be concluded that the proposed procedure is able to predict seismic demands of this kind of structures with acceptable accuracy. The advantage of this method is not only that it can predict the design values in a way that the maximum seismic responses of structure reach to the pre-selected values, but also can predict the true displacement profile of frame and find where maximum drifts happen.

The Inversion Analysis and Material Parameter Optimization of a High Earth-Rockfill Dam during Construction Periods

Inversion analysis is usually an efficient solution to process the monitoring data of earth-rockfill dams. However, it is still difficult to obtain calculation results that are consistent with monitoring data due to different construction statuses. To deal with this situation and to introduce a new solution to improve calculation accuracy, the general method of inversion analysis based on back-propagation neural networks and the original step-by-step inversion method assuming that the parameters of the constitutive model vary with construction periods are introduced and verified in this work. Then, both methods are applied in the inversion analysis of a high gravelly soil core rock-fill dam during construction periods. Moreover, the relationship between the inversed material parameters and the stress values of the core wall is discussed. The material parameters are further optimized to obtain more accurate displacement values. The results show that the step-by-step inversion method has a higher accuracy in vertical compression values compared with the conventional inversion method, the trend of material parameter K is more significant than other parameters, and the proposed variable parameter constitutive model has an accuracy between the step-by-step and conventional inversion methods. Conclusions can be drawn that the original step-by-step inversion method has more advantages than the conventional method and the variable parameter constitutive model proposed in this paper might be more suitable for the analysis of a high earth-rockfill dam during construction periods.

Kinetics Analysis and ADRC-Based Controller for a String-Driven Vascular Intervention Surgical Robotic System.

Vascular interventional surgery is a typical method for diagnosing and treating cardio-cerebrovascular diseases. However, a surgeon is exposed to significant X-radiation exposure when the operation is conducted for a long period of time. A vascular intervention surgical robotic system for assisting the surgeon is a promising approach to address the aforementioned issue. When developing the robotic system, a high displacement accuracy is crucial, and this can aid in enhancing operating efficiency and safety. In this study, a novel kinetics analysis and active disturbance rejection control (ADRC)-based controller is proposed to provide high accuracy for a string-driven robotic system. In this controller, kinetics analysis is initially used to improve the accuracy affected by the inner factors of the slave manipulator. Then, the ADRC controller is used to further improve the operating accuracy of the robotic system. Finally, the proposed controller is evaluated by conducting experiments on a vascular model. The results indicate maximum steady errors of 0.45 mm and 6.67°. The experimental results demonstrate that the proposed controller can satisfy the safety requirements of the string-driven robotic system.

Accurate structural displacement monitoring by data fusion of a consumer-grade camera and accelerometers

The displacement responses of bridge structures are critical both for structural health monitoring and structural safety evaluation. Using vision-based sensors to measure structural displacement responses is an effective method and has attracted considerable attention owing to its advantages of achieving non-contact, time-saving, and full-field measurements. However, there are several obstacles, including the limited frame rate, insufficient accuracy in large-scale measurements, and camera instability, which prevent the application of vision-based sensors. To overcome the shortcomings and improve the accuracies of the vision-based sensors, a displacement monitoring system combined with a consumer-grade camera and accelerometers was developed. Accelerometers attached to the target structures were used to reconstruct the dynamic displacement for data fusion with the vision-based displacement, while an accelerometer attached to the camera was used for camera vibration cancellation. Dynamic loading tests on a self–anchored suspension model bridge were conducted and results of the proposed system, the linear variable differential transformers, and a conventional vision-based system were compared. Field tests on a steel–concrete composite continuous beam bridge and a cable-stayed railway bridge were conducted, and the potential of the proposed system for use in real structures was validated.

Multi-scale and full-field vibration measurement via millimetre-wave sensing

Vibration measurement is of great significance for structural health monitoring (SHM). The emerging microwave vibration measurement technology has distinct advantages over the laser and vision-based approaches, such as long-range, low-power consumption and environmental adaptability. However, it has critical limitations on multi-scale and full-field vibration measurement, especially for SHM of large structures. To overcome these drawbacks, in this paper, we propose mmSHM, a mmWave radar-based vibration measurement approach for SHM. An adaptive segmented phase demodulation (ASPD) method is developed to effectively quantify the displacement variation, allowing accurate displacement measurement spanning from µm to dm scales. What’s more, to eliminate the coupling and aliasing interferences from adjacent targets in full field of view, an improved interferometric phase evolution tracking method is presented to extract the vibration displacement from the range-angle joint dimensions. To be specific, the basic principle of vibration measurement using linear frequency-modulated continuous wave (LFMCW) radar is firstly depicted. Then, the detailed procedures of multi-scale and full-field vibration measurement method are illustrated. Finally, with the built prototype of mmSHM, experimental results under different scenarios show that our method can achieve multi-scale and full-field synchronous vibration measurement with µm-level accuracy. The proposed method can be expected to provide a promising approach for contactless vibration measurement in SHM.

Characterisation of soil deformation over wide strain ranges in triaxial test with high-precision stereophotogrammetry

Stereophotogrammetry was adopted as a means to measure three-dimensional displacements of a soil specimen surface in triaxial tests. New developments include an efficient algorithm that resolves the relative displacements with high precision to the order of 10−3 mm, and strains in common-sized soil specimens to the order of 10−3%, while correcting for ray refraction effects caused by the pressure cell wall and water. The system, requiring only sets of compact-type digital cameras as hardware, allows a stiffness–strain curve to be determined over wide strain ranges spanning from 10−3% to virtually any large strain with a fixed configuration. This paper explains the proposed image analysis processes, which combine a ray tracing formulation by Zhang and co-workers, particle tracking velocimetry and sub-pixel digital image correlation in efficiently deriving accurate and precise relative displacements. Rigorous assessment of the accuracy and precision was conducted. As a demonstration, two undrained triaxial compression tests on reconstituted clay were performed with and without end lubrication. Both for small-strain (<0·05%) axial loading–unloading cycles and for monotonic loading to large axial strain (15%), the strain development was tracked and the specimen behaviour was characterised. These tests demonstrate that the new technique can be a useful option in a soil laboratory both for research and practice.

Non-Measuring Camera Monitoring of Comprehensive Displacement of Simulated Slope Mass Based on Edge Extraction of Subpixel Ring Mark

Slope hazards threaten the safety of buildings and people’s lives and property. Real-time and dynamic monitoring of slope deformation by digital image monitoring technology is an effective method to prevent slope hazards. In this study, the Zhang Zhengyou calibration method is used to calibrate a non-metric digital camera, which is used to monitor the simulated slope with ring marks. The sub-pixel algorithm is used to identify the center coordinates of the landmarks. The proportional coefficient is obtained from the relationship between the landmarks and the actual distance. The change in displacement of the position of the digital camera is calculated in combination with the specific displacement value of the slope, yielding the rapid and accurate displacement trend of the slope. The outdoor experimental results show that the monitoring accuracy of this method can reach millimeter level, which can meet the demand of slope monitoring.

Real-time dynamic simulation for highly accurate spatiotemporal brain deformation from impact

Real-time dynamic simulation remains a significant challenge for spatiotemporal data of high dimension and resolution. In this study, we establish a transformer neural network (TNN) originally developed for natural language processing and a separate convolutional neural network (CNN) to estimate five-dimensional (5D) spatiotemporal brain–skull relative displacement resulting from impact (isotropic spatial resolution of 4 mm with temporal resolution of 1 ms). Sequential training is applied to train (N = 5184 samples) the two neural networks for estimating the complete 5D displacement across a temporal duration of 60 ms. We find that TNN slightly but consistently outperforms CNN in accuracy for both displacement and the resulting voxel-wise four-dimensional (4D) maximum principal strain (e.g., root mean squared error (RMSE) of ∼1.0% vs. ∼1.6%, with coefficient of determination, R2 >0.99 vs. >0.98, respectively, and normalized RMSE (NRMSE) at peak displacement of 2%–3%, based on an independent testing dataset; N = 314). Their accuracies are similar for a range of real-world impacts drawn from various published sources (dummy, helmet, football, soccer, and car crash; average RMSE/NRMSE of ∼0.3 mm/∼4%–5% and average R2 of ∼0.98 at peak displacement). Accuracy in strain rate is also illustrated in one case (NRMSE of 7.8% and of 0.91). Sequential training is effective for allowing instantaneous estimation of 5D displacement with high accuracy, although TNN poses a heavier computational burden in training. This work enables efficient characterization of the intrinsically dynamic brain strain in impact critical for downstream multiscale axonal injury model simulation. This is also the first application of TNN in biomechanics and biomedical engineering, which offers important insight into how real-time dynamic simulations can be achieved across diverse engineering fields.

An edge center-based strain-smoothing triangular and tetrahedral element for analysis of elasticity

A novel edge center-based strain-smoothing method is put forward and applied to triangular and tetrahedral finite elements for linear and geometric nonlinear analysis of elastic mechanics. In the proposed edge center-based strain-smoothing element (EC-SSE), the linear strain field is constructed accordingly to the smoothed strain at element edge centers or face centers. The smoothed strain at both triangular and tetrahedral element edge centers is obtained directly utilizing elements adjacent to the edge, without requiring smooth domain. Besides, the smoothed strain at edge centers is averaged and assigned to the face center for tetrahedral elements. Compared with other methods, EC-SSE not only constructs a linear strain field within elements without introducing extra DOFs, but also ensures the strain consistency at the centers of intersecting edges or interfaces, which help to tremendously improve the smoothness of strain/stress distribution in the whole field. The EC-SEE passes basic element tests, including standard patch test, zero energy mode and linear independent tests. Subsequently, some attractive performances of EC-SSE, such as high accuracy and convergence rates for both displacement and strain energy, smoother stress field and the absence of temporal instability problems, are demonstrated through a variety of practical numerical examples.

Deep DIC: Deep learning-based digital image correlation for end-to-end displacement and strain measurement

Digital image correlation (DIC) has become an industry standard to retrieve accurate displacement and strain measurement in tensile testing and other material characterization. Though traditional DIC offers a high precision estimation of deformation for general tensile testing cases, the prediction becomes unstable at large deformation or when the speckle patterns start to tear. In addition, traditional DIC requires a long computation time and often produces a low spatial resolution output affected by filtering and speckle pattern quality. To address these challenges, we propose a new deep learning-based DIC approach--Deep DIC, in which two convolutional neural networks, DisplacementNet and StrainNet, are designed to work together for end-to-end prediction of displacements and strains. DisplacementNet predicts the displacement field and adaptively tracks a region of interest. StrainNet predicts the strain field directly from the image input without relying on the displacement prediction, which significantly improves the strain prediction accuracy. A new dataset generation method is developed to synthesize a realistic and comprehensive dataset, including the generation of speckle patterns and the deformation of the speckle image with synthetic displacement fields. Though trained on synthetic datasets only, Deep DIC gives highly consistent and comparable predictions of displacement and strain with those obtained from commercial DIC software for real experiments, while it outperforms commercial software with very robust strain prediction even at large and localized deformation and varied pattern qualities. In addition, Deep DIC is capable of real-time prediction of deformation with a calculation time down to milliseconds.

Source Parameters and Slip Distribution of the 2019 Mw 5.8 Mirpur (Pakistan) Earthquake Inferred from the Corrected InSAR Observations

AbstractOn 24 September 2019, an Mw 5.8 earthquake occurred on the Mangla-Samwal anticline near Mirpur city, Pakistan. Because the seismogenic fault is hidden and the near-field seismic data are scarce, the magnitude and slip distribution of this earthquake are not determined. Furthermore, due to small deformation and significant atmospheric noise in the coseismic interferograms, it is difficult to accurately determine source parameters and slip distribution using the original single ascending and descending Interferometric Synthetic Aperture Radar observations. In this article, we used Sentinel-1A satellite Synthetic Aperture Radar data to generate 60 ascending and 56 descending coseismic interferograms and performed atmospheric error correction including Kriging interpolation correction and displacement stacking to obtain more accurate coseismic displacement fields for the 2019 Mw 5.8 Mirpur earthquake. Considering the local geological structures, focal mechanism solutions, and the optimal fault parameters obtained from the coseismic displacement inversion, we determine that the strike and dip of the fault of the 2019 Mirpur earthquake are 296.3° and 4.0°, respectively. Based on this fault model, the fault plane was extended to 12.0 km long and 11.0 km wide and divided into subfaults of 1.0×1.0 km2. We inverted the coseismic displacement fields to obtain slip distribution on the fault plane. Slip is mainly distributed at a depth of 4.7 ∼ 5.0 km, with a maximum of 0.95 m at a depth of 4.88 km. The slip distribution shows that this earthquake was a thrust event with right-lateral strike-slip components, which is consistent with the focal mechanism solution from the U.S. Geological Survey. The estimated geodetic moment is about 7.14×1017 N·m, equivalent to Mw 5.8.

PPP-derived tropospheric ZWD augmentation from local CORS network tested on bridge monitoring points

This paper developed the tropospheric correction augmented PPP for the purpose of bridge displacement monitoring. ZWD is estimated from undifferenced observations collected by UK CORS, and further applied to augment PPP client for displacement at the bridge surveying points. Coordinate time series obtained by GPS DD are treated as the true bridge displacement, which is used to assess the standard and CORS ZWD augmented PPP solutions obtained by varying cutoff angles. The experimental results reveal that the displacement precision of standard PPP severely depends on the satellite geometry. Meanwhile, the CORS ZWD augmented PPP results are less affected. The RMSE of improved PPP time series in the vertical component drops by 12%, 49% and 66% for the 5°, 10° and 15° cutoff angle cases, respectively. CORS ZWD augmented PPP can improve the monitoring precision and eliminate irregular displacement time series due to poor satellite geometry.

EXPERIMENTAL STUDY OF STRAIN RATES EFFECTS ON STRAIN LOCALIZATION CHARACTERISTICS OF SOFT ROCKS

The effects of strain rates on the strain localization characteristics of soft rocks in plane strain compression tests were studied. Using digital image correlation method based on image analysis technique, digital photographs of the specimen taken by CCD camera mounted in a microscope at different stages of loading were analyzed and displacement and strain fields were obtained. The accuracy of displacement and strain measurements are found to be 2.625 μm and 0.0525% (for 5 mm x 5 mm grid), respectively. By analyzing the strain fields, important information regarding strain localization characteristics at three different strain rates were obtained. The results of the study indicate that strain rate has significant influence on the localization modes. Strain localization was observed before the peak stress. The switching of localization mode from highly concentrated strain accumulation mode for higher strain rate to diffuse and complex strain accumulation mode for lower strain rate were observed. The evolutions of strain fields during creep tests at different loads were also studied.

AN APPLICATION OF SOFT COMPUTING TECHNIQUES TO PREDICT DYNAMIC BEHAVIOUR OF MOORING SYSTEMS

A spread mooring system (SMS) allows a ship or a floating platform to moor the seafloor using multiple mooring lines at a restricted region with a fixed heading in harsh weather. These systems can be used for the operations of ships of different tonnage at different sea depths. The optimal design of these systems is a challenging engineering problem because of the effects of many design parameters and changing environmental conditions. Modern soft computing techniques allow difficult engineering problems to be solved easily and precisely and are becoming more and more popular. In this paper, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as soft computation techniques have been chosen to estimate the hawser tensions and displacements of a spread mooring system. The attained results show both techniques can give consistent indicators for the modelling of dynamic systems. Although these techniques performed very well, the ANFIS model is relatively superior to the ANN technique, considering the accuracy of hawser tensions and displacements in terms of the relative errors and coefficient of correlation obtained for the ANN and ANFIS.

Acoustic Emission of Sand during Creep under Oedometric Compression

Abstract Creep of sand is a consequence of micromechanical processes within the granular soil skeleton. These processes are known sources of acoustic emissions. Therefore, acoustic emission analysis provides additional information about the time-dependent mechanisms, even if conventional deformation measurements reach their limit of applicability (i.e., resolution, accuracy). The present study investigates the relationship between acoustic emission events and creep deformation. For this purpose, multistage creep tests at axial stresses up to 6,000 kPa are conducted on loose and dense quartz sand under oedometric conditions. During creep acoustic emission are recorded and processed and the results are compared to conventional displacement measurements. The deformations during creep are measured using a highly accurate displacement transducer. The creep behavior is characterized by the creep-coefficient C relating the change of the strains with the logarithmic increment of time. The experimental results show that the time-evolution of the acoustic emissions and the evolution of strain during creep are qualitatively similar. In analogy to the coefficient of C, a coefficient CAE relating the cumulated number of acoustic emissions with the logarithm of time is defined. In the conducted experiments, we observe that both the coefficients of C and CAE show a dependence on stress, the initial density, and the strain rate at the beginning of creep. Nevertheless, the influence of the initial strain rate on C and CAE reduces over time and both quantities approach constant values for increasing time.

A novel gradient-based matching via voting technique for vision-based structural displacement measurement

The effectiveness of vision-sensing system for field applications in remote measurements of structural displacement can be adversely affected by environmental factors, leading to an incomplete recording of a moving feature target in recorded video frames. The result is a non-ideal solution using traditional template matching techniques, which presents significant challenges for accurate measurements. This paper proposes a novel gradient-based matching via voting (GMV) technique to overcome environmental and operational conditions and provide reliable tracking of moved targets with different degrees of feature loss. When evaluating the region similarity between the template and a subset (called the overlapping region) of video frames in which the moved target is located to obtain a similarity score of the subset, the traditional template matching does not ascribe weights to the similarity at the pixel level, whereas GMV uses a voting scheme to weight all the pixel similarities. Three experiments were used to test GMV, evaluating its tracking accuracy and verifying its robustness with different levels of target feature loss based on a comparison with two commonly used template matching techniques. GMV proved to be capable of retrieving accurate displacement data with a high degree of accuracy, even for a moved target with up to 90% feature losses.