Displacement Monitoring Research Articles

A Continuous Tilt Sensor Based on UWFBG Technology for Landslide Real-Time Monitoring

Displacement monitoring is the key work of landslide disaster early warning. Distributed and real-time displacement monitoring can provide a more accurate and timely reference for landslide instability evaluation. However, existing technologies have deficiencies in combining distributed and real-time capabilities. Given this, a novel continuous ultra-weak fiber Bragg grating (UWFBG)-based tilt sensor is proposed. First, the tensile test is designed and carried out to investigate the strain transfer mechanism of the UWFBG cable. Then, calibration experiments are used to verify the monitoring performance of the sensors. Finally, the UWFBG tilt sensors are applied in the Majiagou landslide, a typical reservoir landslide located in Three Gorges Reservoir Area (TGRA). The results show that the sliding surface of the landslide is located at 33 m, and the maximum displacement value is 8.1 mm during the monitoring period. When the landslide is in a stable deformation state, the dynamic range of displacement is 1.4 mm. The UWFBG tilt sensors with distributed and real-time monitoring characteristics can achieve accurate landslide displacement measurement and provide outlets for early warning.

INTERFEROMETRIC PROCESSING OF A DEVELOPED MIMO GBSAR FOR DISPLACEMENT MONITORING

Abstract. This study demonstrates the interferometric processing experiments of our developed multiple-input multiple-output ground-based synthetic aperture radar (MIMO GBSAR) system. GBSAR systems are known as precise noncontact instruments for monitoring earth dynamics. In recent years W band MIMO radars have shown interesting potential in this field due to their low cost, compact size, and high phase sensitivity. MIMO capability enables the angular discrimination of multiple targets in the same range as the radar sensor. In our previous works, we developed a high-resolution MIMO GBSAR system based on the combination of MIMO radar and mechanical rail. Accordingly, this study investigates the developed system’s displacement monitoring capability by presenting a controlled experiment, using fixed and moving corner reflectors and gathering 36 time series of data. We compare and discuss the results obtained from MIMO GBSAR and MIMO radar configurations. The results show that our developed system highly agrees with MIMO radar’s interferometric measurements while providing a better target discrimination capability and higher signal noise ratio.

Stress and Deformation Characteristics of Tunnel Surrounding Rock under Alteration

Based on a typical project in an altered rock area, this study carried out numerical simulations using the FLAC3D software to calculate the changes in the stress field, deformation field, and plastic zone of the surrounding rock during the unsupported and supported excavation of a water transfer tunnel. The degree of alteration of the surrounding rock was considered as the base point. The following results were obtained: in the unsupported state, the tunnel surrounding rock was affected by different degrees of alteration, and compressive stress concentration appeared within a certain range at the bottom of the chamber. The value of all-directional stress decreased with the deepening of the degree of alteration, while the opposite was the case for the depth of influence. The displacement changes at the bottom and side walls of the chamber were large and increased significantly with the deepening of the degree of alteration; the displacement monitoring points distributed around the tunnel exhibited the same deformation trend. The plastic zone of the surrounding rock obviously expanded as the degree of alteration deepened. The stress, deformation field, and plastic zone of the tunnel surrounding rock were effectively controlled after the adoption of support measures. The results obtained by this study can be used as a reference for similar projects in altered rock areas.

A novel steel bulkhead based on the method of prefabrication and assembly and its first application to the Yuliangzhou immersed tunnel

Temporary bulkheads installed at the end of each tunnel element are indispensable for immersed tunnel elements to be watertight and float. Currently, welded steel bulkheads and cast-in-place concrete bulkheads have been applied in the installation of most immersed tunnels; however, these bulkheads have many inherent drawbacks. For example, existing cast-in-place concrete bulkheads are bulky and cannot be recycled after demolition. In addition, existing welded steel bulkheads, which cannot be fully reused, are installed and dismantled with a large number of on-site welding operations. Relying on the Yuliangzhou Immersed Tunnel in China, a novel steel bulkhead based on the method of prefabrication and assembly, namely, a piece-assembled steel bulkhead, was developed to address the abovementioned problems. The structural components of the new steel bulkhead applied to realize full recycling mainly include steel bulkhead panels, ethylene-propylene-diene-monomer (EPDM) sealing gaskets, steel bearings, and steel connecting bolts. The water tightness function of the new bulkhead was achieved through the compression deformation of the designed EPDM sealing gaskets inside the assembly seams, which were designed as multihole structures to save manufacturing material. Nonlinear finite element simulations were conducted to investigate the gasketed seam mechanical and sealant behavior. It was concluded that the control threshold value of gasketed seam compression displacement needed to satisfy the design requirement for a 250 kPa waterproof capacity could be taken as 15 mm, while that for seam offset displacement was set to 40 mm. To achieve the fast and efficient construction of the new steel bulkhead, a strategy of symmetrically installing and removing steel bulkhead panels piece by piece at one carriageway bore was proposed, and an automatic installation trolley that adjusts the bulkhead panel position in three directions was designed and developed. Finally, the on-site monitoring of the assembly seam displacements and the stress and deformation of the H-shaped steel beam verified that the new steel bulkhead was in a safe state and displayed good watertightness. This bulkhead was successfully applied in the Yuliangzhou Immersed Tunnel project, and this test application supports the use of these technologies in immersed tunnel construction.

Pavement Structure Characteristics and Behaviour Analysis with Digital Image Correlation

Digital image correlation (DIC) is a method of point displacement measurement by an optical system. If two cameras are used for capturing the same point displacement, three-dimensional data are obtained using the 3D-DIC method. The areas of application of this method in pavement construction are diverse, but it is mainly used for displacement monitoring during standard tests of the failure of specimens due to load application. Furthermore, DIC technology was used only for testing particular material characteristics and assuming their influence on the overall pavement system. Within this research, DIC was applied in two areas: defining material mechanical characteristics and analyses of pavement structure behaviour under cyclic loading. The scope of this research was to gain more insights into DIC’s potential application within pavement behaviour analyses, specifically on cement-bound granular material (CBGM) characterisation. Results from this study confirm the suitability of 3D-DIC technology for pavement material characterisation. Furthermore, it is shown that certain trends of material behaviour defined on the simple material level of each independent pavement layer will significantly differ when it is placed in the system, and this kind of complex analysis is possible by using 3D-DIC technology.

Stress Calculation Method Designed of Pipeline in Landslide Section Based on SBAS-Insar and Finite Element Method

The permanent ground displacement of geological disasters is the main reason inducing large additional axial stress of pipelines. This paper presents a surface displacement measurement method above the pipeline based on SBAS-InSAR remote sensing technology, which realizes millimeter-level high-precision monitoring of surface displacement of pipeline in kilometer range. Based on the spatial coordinate data of the pipeline center line and the geometric feature data of the pipeline, combined with the cubic spline interpolation algorithm, a reconstruction method of the pipeline three-dimensional space routing is proposed. Considering the real routing of the pipeline and the process load conditions such as temperature and pressure, the finite element model of pipeline stress analysis is established by using the space pipe element and the nonlinear pipe soil element. Taking the remote sensing landslide displacement as the accurate boundary condition, the calculation method of pipeline stress in landslide section is proposed. The practice of a high-risk landslide section in Liangxiang-Xishatun of Shaanxi-Beijing Pipeline from 2021 to 2022 shows that the maximum relative error between the pipeline stress results obtained by this method and the distributed strain gauge monitoring results does not exceed 16%, which can effectively realize the spatial reconstruction and safety evaluation of the pipeline stress state in the landslide section, and provide a technical basis for the establishment of digital twins of pipeline safety state in future geological disaster sections.

МОНІТОРИНГ ВЕРТИКАЛЬНИХ ЗМІЩЕНЬ ЗЕМНОЇ ПОВЕРХНІ ПРАВОБЕРЕЖЖЯ КАНІВСЬКОГО ВОДОСХОВИЩА

Monitoring of vertical displacements of the earth's surface on the right bank of the Kaniv Reservoir in the Vytatchiv-Stajky region was carried out using the differential radar interferometry (DinSAR) technique. According to the results of observations during the spring period from 2015 to 2023, active landslide areas are displayed. The DinSAR method is briefly described, emphasising data filtering steps for landslide activation mapping. A high data correlation was recorded, and the presence of zones of active shifts on the shore of the reservoir was confirmed. The spread and intensity of landslide manifestations are determined by the peculiarities of the geological and geomorphological structure of the territory, its tectonic, neotectonic and seismic regimes, and hydrological and climatic conditions. Limitations of the method arising from the temporal decorrelation of the radar signal in regions with a large amount of vegetation are determined. Due to the significant decorrelation between the obtained results of forested and watered areas, the DinSAR technique, a digital elevation model (DEM), analysis of base surface maps and the results of spectral index calculations were combined to identify regions of active landslides caused by waterlogging of the Dnieper slopes. The study demonstrates the feasibility of using DinSAR to detect and monitor surface deformation.

Mechanical Performance Study of Pipe-Liner Composite Structure Based on the Digital Image Correlation Method

Repair of reinforced concrete drainage pipes is often performed using polyethylene (PE) lining. To investigate the bearing capacity characteristics of a repaired composite structure, this study conducted experiments on three groups, namely, PE pipes, reinforced concrete pipes, and composite-reinforced concrete PE pipes (count = 9). The cracking and ultimate loads of the three groups under plate loads were evaluated and analyzed. A displacement monitoring method based on two-dimensional digital image correlation (2-D-DIC) and three-dimensional digital image correlation (3-D-DIC) techniques is proposed, and the quantitative laws of strain distribution at the end face of the specimen are obtained. Furthermore, the damage mechanism of the reinforced concrete pipe and the interface spalling damage mechanism of the composite-reinforced concrete PE under load were investigated to reveal the effect of PE lining improvement on the bearing capacity of the reinforced concrete pipe. The maximum deviation of the specimen vertical displacement results obtained using the new noncontact 3-D-DIC method is 2.6% compared with that of the traditional physical sensor method, and this method can successfully capture the deformation and strain data of the target specimen. Therefore, the noncontact DIC method has a broad application prospect in municipal pipeline early warning monitoring systems.

Real-Time and Near Real-Time Displacement Monitoring With GNSS Observations in the Mining Activity Areas

Real-Time and Near Real-Time Displacement Monitoring With GNSS Observations in the Mining Activity Areas

A Functional Model for Determining Maximum Detectable Deformation Gradients of InSAR Considering the Topography in Mountainous Areas

The maximum detectable deformation gradients (MDDG) for interferometric synthetic aperture radar (InSAR) technology is important for the selection of SAR images and processing algorithms to perform accurate slope displacement monitoring, which is strongly influenced by terrain factors in mountainous areas. In this paper, a functional model is proposed to determine the MDDG of InSAR with respect to arbitrary slope gradients/aspects and wavelengths. Based on this model, regional MDDG characteristics are explored and compared in Mao County, Sichuan Province, China. The MDDG distribution regarding on Sentinel-1, ALOS-2/PALSAR-2 and TerraSAR-X SAR satellite data using arbitrary slope gradient/aspect are derived. Furthermore, the MDDG from variable satellites for three different bands (X/C/L-band) are compared and the influence factors with respect to the wavelength and resolution on MDDG are discussed. The proposed model is helpful in selecting of SAR data or processing algorithms based on calculated MDDG, in the meanwhile, it has significant implications on the understanding and analyzing real slope displacement monitored by InSAR regarding on different SAR images in mountainous areas.

A New Benchmark for Vibration Displacement Detection of Rotor

Vision-based structural displacement monitoring of rotor has attracted extensive attention from scholars due to its non-contact, non-damage, and multi-point synchronous measurement advantages. However, there is a lack of one comprehensive dataset and benchmark for rotor detection since the problem of limited acquisition equipment or on-site environment in the industrial field. For that, a large benchmark for rotor’s vibration displacement detection is introduced in this paper. Firstly, a rotor vibration displacement detection network (RDNet) for rotating structures is proposed and state-of-the-art performance is achieved. Secondly, the evaluation criteria are designed to evaluate the rotor image detection accuracy using the mean Average Precision@0.5:0.95 (mAP@0.5:0.95), the Frames Per Second (FPS), and the Normalized Root Mean Squared Error (NRMSE) as performance indicators. Thirdly, a dataset namely Rotor V1.0 is built, which contains three frames (high, middle, and low) of 13,500 rotor images. It is the rotor dataset for vibration displacement monitoring of rotating structures. Lastly, the baseline performance resulted from traditional methods (i.e., match template and support vector machines) and deep learning methods (i.e., CenterNet, Faster Region-convolutional neural networks (Faster R-CNN), RetinaNet, Single Shot MultiBox Detector (SSD), and You only look once (YOLO)) are reported and analyzed. It is hoped that RDNet, evaluation criteria, and the novel Rotor V1.0 dataset can promote the implementation of visual vibration measurement tasks in industrial sites.

Legendre Polynomials-Based Displacement Field Reconstruction of Plate-Type Structures With Quasi-Distributed FBG Sensors

Structural deformation estimation is of great interest for many engineering fields, such as aerospace structures, antenna panels, and so on. During operation, however, the direct measurement of global displacements is often difficult, due to the limits of installation space and electromagnetic interference. This article proposed a displacement field reconstruction method for deformed plate-type structures using discrete curvature measurements and a polynomial superposition approach. Specifically, the displacement field is expressed as a linear superposition of the Legendre polynomial basis functions, where the weight coefficients are calculated using the discrete curvatures captured by a quasi-distributed fiber Bragg grating (FBG) sensor array and the given boundary conditions. This method overcomes the drawback of error accumulation in other curvature-based methods due to the use of recursion operations. In addition, the curvature fitting and the determination of the number of polynomial basis functions were also presented to obtain the best reconstruction quality. Simulations and experiments have been conducted to validate the proposed method. The simulation results show that the displacement reconstruction precisions are more than 99% for two types of complex deformations. Experiments were carried out on an aluminum plate and a phased-array antenna panel, respectively. The results show that the reconstructed displacements of the reference points match well with those measured displacements, and the reconstruction precision exceeds 96%. This proposed curvature-based approach has high potential to global displacement monitoring of plate-type structures used in aerospace and antenna industrial fields.

RFID Landslide Monitoring: Long-Term Outdoor Signal Processing and Phase Unwrapping

Localization of passive Radio-Frequency Identification (RFID) tags has been used to monitor landslide surface displacement since 5 years. This method, applied on slow displacements lower than 1cm per day, allows a high spatio-temporal resolution at a relatively low cost. With the feedback of the previous years, this paper proposes to summarize the various challenges encountered with the long-term outdoor RFID localization method, and presents data-processing solutions that were implemented to overcome these challenges. We propose a complex-smoothing unwrapping algorithm, a multi-frequency merging operation, as well as multi-tag and multi-antenna phase combining method. The concept of an unwrapping reference guide is presented and applied with groups of tags showing coherent displacements, or with absolute reference measurements. These approaches allow a higher data availability up to 38% for one site over multiple years, and a better phase unwrapping. Earth surface displacement monitoring with RFID proves to be a robust and accurate solution, with four equipped sites across France and Switzerland.

Transfer learning based physics-informed neural networks for solving inverse problems in engineering structures under different loading scenarios

Recently, a class of machine learning methods called physics-informed neural networks (PINNs) has been proposed and gained prevalence in solving various scientific computing problems. This approach enables the solution of partial differential equations (PDEs) via embedding physical laws into the loss function. Many inverse problems can be tackled by simply combining the data from real life scenarios with existing PINN algorithms. In this paper, we present a multi-task learning method using uncertainty weighting to improve the training efficiency and accuracy of PINNs for inverse problems in linear elasticity and hyperelasticity. Furthermore, we demonstrate an application of PINNs to a practical inverse problem in structural analysis: prediction of external loads of diverse engineering structures based on limited displacement monitoring points. To this end, we first determine a simplified loading scenario at the offline stage. By setting unknown boundary conditions as learnable parameters, PINNs can predict the external loads with the support of measured data. When it comes to the online stage in real engineering projects, transfer learning is employed to fine-tune the pre-trained model from offline stage. Our results show that, even with noisy gappy data, satisfactory results can still be obtained from the PINN model due to the dual regularization of physics laws and prior knowledge, which exhibits better robustness compared to traditional analysis methods. Our approach is capable of bridging the gap between various structures with geometric scaling and under different loading scenarios, and the convergence of training is also greatly accelerated through not only the layer freezing but also the multi-task weight inheritance from pre-trained models, thus making it possible to be applied as surrogate models in actual engineering projects.

Research on the Landslide Prediction Based on the Dual Mutual-Inductance Deep Displacement 3D Measuring Sensor

Landslides are frequent and catastrophic geological hazards, and forecasting their movement is an important aspect of risk assessment and engineering prevention. Based on the integrated deep displacement three-dimensional measuring sensor with sensing unit array structure, an improved multivariable grey model based on dynamic background value and multivariable feedback is proposed to build predictive models for the evolutionary condition of landslides. In the modeling process, the traditional grey model was replaced by extracting the trend information of each variable, instead of summing up each independent variable after assigning weights to it, besides, the Whale Optimization Algorithm (WOA) is used to modify the default value in the model’s background variables. By predicting more than 1000 sets of deep displacement monitoring data collected in the landslide simulation test conducted at the landslide simulation test device, the displacement prediction accuracy of our purposed model is 26%, 47%, and 87% respectively higher than the optimizing grey model (OGM) for three sensing units at different depths. Moreover, a new landslide risk assessment approach based on the orientation vector angle is proposed to make stability discriminations which is less susceptible to volatile data than the TOPSIS-Entropy weight theory and avoids the problem of lack of uniform standards due to the complexity of environmental factors.

Assessment of the accuracy of low-cost multi-GNSS receivers in monitoring dynamic response of structures

The monitoring of bridges is a crucial operation for their structural health examination and maintenance. GNSS technology is one of the methods which are applied with the main advantage that the direct measurement of the bridge displacement is conducted in an independent global coordinate system. However, the high cost of the GNSS stations, which are consisted of dual-frequency receivers and geodetic GNSS antennas, is the main reason of the limited application of GNSS for bridge monitoring. In this study, we assessed the performance of low-cost multi-GNSS receivers in monitoring dynamic motion, similar to that of bridge response. The performance of the low-cost GNSS receivers was assessed based on controlled experiments of horizontal and vertical motion. For the horizontal motion, controlled experiments of circular motion of various predefined radius between 5 and 50 cm were executed where the low-cost GNSS receivers were assessed against dual-frequency geodetic receivers. For the vertical motion, manually controlled experiments of vertical oscillations of amplitude 8 and 15 mm were executed where the low-cost GNSS receivers were assessed against the Robotic Total Station (RTS). Finally, a low-cost monitoring system formed by two closely spaced low-cost GNSS receivers was applied in dynamic displacement monitoring of the Wilford Suspension Bridge. The analysis of the low-cost GNSS data revealed the beneficial contribution of (i) the multi-constellation on the accuracy and precision of the GNSS solution and (ii) the combination of closely spaced low-cost GNSS receivers, to limit potential cycle slips and the low-cost GNSS noise level and reach accuracy and precision similar to that of geodetic-grade GNSS receivers. This was confirmed in the bridge monitoring application, where the main modal frequency and the response amplitude of the bridge were identified successfully by the low-cost GNSS receivers’ data analysis.

Competitive interfacial behavior in sodium caseinates-hydroxypropyl cellulose mixed systems

In this work, interactions between hydroxypropyl cellulose (HPC) and sodium caseinates (Na-cas) at the air-water interface were studied. The surface tension, surface rheology, and film compatibility of the mixed protein/polysaccharide system were investigated. Tensiometry experiments showed that HPC is more surface-active than proteins, and is preferentially adsorbed at the interface. This molecule is able to migrate to the interface faster than Na-cas despite its larger size. At low HPC concentration, proteins adsorb first but HPC being more surface-active will eventually substitute them at the interface. The use of the pendant drop tensiometer allowed the real-time monitoring of protein displacement; an immediate decrease in surface tension was observed when HPC was added to a Na-cas solution. The analysis of the compression isotherms of Na-cas/HPC mixed films revealed partial miscibility between the two species within the monolayer; the films were less expanded than expected from the ideal behavior of binary mixtures. The dilatational rheology experiments showed that the presence of a very small amount of HPC had a significant effect on the viscoelastic properties of the interface. This work reported for the first time the competitive adsorption between Na-cas and HPC at the A/W interface.

Multi-block synchronous prediction of concrete dam displacements using MIMO machine learning paradigm

The integration of numerous monitoring points poses a significant challenge to the efficient modeling of dam displacement behavior, and multi-point synchronous prediction is an effective solution. However, traditional approaches usually construct site-specific data-driven models for each monitoring point individually, which focus on single-target regression and discard the underlying spatial correlation among different displacement monitoring points. This study therefore proposes a multi-input multi-output (MIMO) machine learning (ML) paradigm based on support vector machine (SVM) for synchronous modeling and prediction of multi-point displacements from various dam blocks. In this method, a novel multi-output data-driven model, termed as multi-target SVM (MSVM), is formulated through a deep hybridization of classical SVM architecture and multi-target regression. During the initialization of MSVM, the intercorrelation of multiple target variables is fully exploited by decomposing and regulating the weight vectors. The proposed MSVM is designed to capture the complex MIMO mapping from influential factors to multi-block displacements, while taking into account the correlation between multi-block displacement outputs. Additionally, in order to avoid obtaining the unreliable prediction results due to the empirical selection of parameters, an efficient optimization strategy based on the parallel multi-population Jaya (PMP-Jaya) algorithm is used to adaptively tune the hyperparameters involved in MSVM, which contains no algorithm-specific parameters and is easy to implement. The effectiveness of the proposed model is verified using monitoring data collected from a real concrete gravity dam, where its performance is compared with conventional single-target SVM (SSVM)-based models and state-of-the-art ML-based models. The results indicate that our proposed MSVM is much more promising than the SSVM-based models because only one prediction model is required, rather than constructing multiple site-specific SSVM-based models for different dam blocks. Moreover, MSVM can achieve better performance than other ML-based models in most cases, which provides an innovative modeling tool for dam multi-block behavior monitoring.

Example of using long-term monitoring and non-invasive measurements for Structural Health Monitoring. Cause study of St. Anna's Church in Warsaw

Heritage objects are affected by many factors that affect degradation over time and damage to historical sites. For this reason, it is necessary to carry out continuous monitoring using non-invasive techniques for Structural Health Monitoring and plan the conservation works. This article aims to present the results of a project that involved long-term monitoring using surveying techniques such as precise tacheometric measurements, precise levelling, inclinometric measurements and crack measurements using crack gauges. This paper presents the results of multisensor monitoring of displacements and cracks in the building, which contributed to the conservation efforts and prevent works. A research object is St. Anne's Church in Warsaw. It is one of the few in Warsaw that wasn't destroyed during World War II.

Monitoring of the Deposit Displacements and the Settlement Behavior in Simionești Village Location, Cordun Commune, Neamţ County

Abstract Monitoring the displacements and settlements of tailings deposits is necessary due to stability problems that may arise over time. The paper deals with the monitoring by means of topographical measurements of two tailings deposits located on a site in Simionești village, Cordun commune in Neamț county. Topographic measurements are used to monitor the movement of landmarks located on these deposits and the settlement behavior of the deposit, so that any stability problems can be detected in time.