Deformation Monitoring Method Research Articles

Methods and research for deformation monitoring of earth and rock dams based on close-range photogrammetry

Abstract Traditional means of monitoring deformation in earth and rock dams encounter challenges such as low monitoring efficiency and limited coverage. Despite the potential of emerging technologies such as GPS and three-dimensional laser scanning, their adoption is expensive and hard to promote. This paper presents a deformation monitoring method for earth and rock dams based on the close-range photogrammetry technique. The proposed approach focuses on analytical algorithm the design and deployment of monitoring points, photographic schemes, camera checking and calibration, as well as deformation analysis methods. Initially, based on the analysis of the parsing algorithms’ applicability, they are fused to address the shortcomings of common image parsing methods in meeting the requirements of high precision and multi-image processing for deformation monitoring of earth and rock dams. Subsequently, the fused algorithm is introduced to analyze the acquired image data for 3D reconstruction, and the deformation in earth and rock dams is assessed based on the generated dense point cloud model. The proposed deformation monitoring method is applied to Pine Bridge Reservoir Dam, and the results demonstrated its capacity to comprehensively analyze the deformation. Furthermore, the required equipment is simple and easy to operate, aligning with the requirements for deformation monitoring accuracy of earth and rock dams.

High-Precision Monitoring Method for Bridge Deformation Measurement and Error Analysis Based on Terrestrial Laser Scanning

In bridge structure monitoring and evaluation, deformation data serve as a crucial basis for assessing structural conditions. Different from discrete monitoring points, spatially continuous deformation modes provide a comprehensive understanding of deformation and potential information. Terrestrial laser scanning (TLS) is a three-dimensional deformation monitoring technique that has gained wide attention in recent years, demonstrating its potential in capturing structural deformation models. In this study, a TLS-based bridge deformation mode monitoring method is proposed, and a deformation mode calculation method combining sliding windows and surface fitting is developed, which is called the SWSF method for short. On the basis of the general characteristics of bridge structures, a deformation error model is established for the SWSF method, with a detailed quantitative analysis of each error component. The analysis results show that the deformation monitoring error of the SWSF method consists of four parts, which are related to the selection of the fitting function, the density of point clouds, the noise of point clouds, and the registration accuracy of point clouds. The error caused by point cloud noise is the main error component. Under the condition that the noise level of point clouds is determined, the calculation error of the SWSF method can be significantly reduced by increasing the number of points of point clouds in the sliding window. Then, deformation testing experiments were conducted under different measurement distances, proving that the proposed SWSF method can achieve a deformation monitoring accuracy of up to 0.1 mm. Finally, the proposed deformation mode monitoring method based on TLS and SWSF was tested on a railway bridge with a span of 65 m. The test results showed that in comparison with the commonly used total station method, the proposed method does not require any preset reflective markers, thereby improving the deformation monitoring accuracy from millimeter level to submillimeter level and transforming the discrete measurement point data form into spatially continuous deformation modes. Overall, this study introduces a new method for accurate deformation monitoring of bridges, demonstrating the significant potential for its application in health monitoring and damage diagnosis of bridge structures.

A Persistent Scatterer Point Selection Method for Deformation Monitoring of Under-Construction Cross-Sea Bridges Using Statistical Theory and GMM-EM Algorithm

Using traditional algorithms to identify persistent scatterer (PS) points is challenging during bridge construction because of short-term changes at construction sites, such as earthworks, as well as the erection and dismantling of temporary structures. To address this issue, this study proposes a PS point selection method based on statistical theory and Gaussian Mixture Model-Expectation Maximization (GMM-EM) algorithm. This method adopts amplitude information as an incoherence evaluation indicator. Furthermore, the statistical median of the amplitude dispersion index and amplitude mean is screened twice to extract a set of candidate points, including PS points that exhibit stable backscattering over long durations. Temporal coherence is simultaneously used as the coherence evaluation indicator. Another candidate point set is obtained by extracting high-coherence PS points using the GMM-EM algorithm. These sets of candidate points are then combined to obtain a final PS points set. In the experiment, the deformation monitoring of the under-construction Shenzhen-Zhongshan Cross-Sea Bridge in China was selected as a case study, with 28 Sentinel-1A images used as the data source for PS selection and deformation information extraction. The results show that the proposed method enhanced the density and quality of PS points on the under-construction cross-sea bridge compared to existing PS selection methods, thus offering higher reliability. Deformation analysis further revealed fluctuating deformation trends at characteristic points of the Shenzhen-Zhongshan Cross-Sea Bridge, indicating the occurrence of elastic deformation during its construction.

A novel videogrammetry-based full-field dynamic deformation monitoring method for variable-sweep wings

A novel videogrammetry-based full-field dynamic deformation monitoring method for variable-sweep wings

Deep Learning CNN-GRU Method for GNSS Deformation Monitoring Prediction

Hydraulic structures are the key national infrastructures, whose safety and stability are crucial for socio-economic development. Global Navigation Satellite System (GNSS) technology, as a high-precision deformation monitoring method, is of great significance for the safety and stability of hydraulic structures. However, the GNSS time series exhibits characteristics such as high nonlinearity, spatiotemporal correlation, and noise interference, making it difficult to model for prediction. The Neural Networks (CNN) model has strong feature extraction capabilities and translation invariance. However, it remains sensitive to changes in the scale and position of the target and requires large amounts of data. The Gated Recurrent Units (GRU) model could improve the training effectiveness by introducing gate mechanisms, but its ability to model long-term dependencies is limited. This study proposes a combined model, using CNN to extract spatial features and GRU to capture temporal information, to achieve an accurate prediction. The experiment shows that the proposed CNN-GRU model has a better performance, with an improvement of approximately 45%, demonstrating higher accuracy and reliability in predictions for GNSS deformation monitoring. This provides a new feasible solution for the safety monitoring and early warning of hydraulic structures.

Research on Deformation Monitoring of Roadway Surrounding Rock Based on Mobile 3D Laser Scanning Technology

Aiming at the problems of low data acquisition efficiency, unintuitive data form, low relative accuracy, and inability to continuously monitor the whole cross-section in traditional roadway rock deformation monitoring methods, a roadway rock deformation monitoring method based on mobile 3D laser scanning technology is proposed. Firstly, the mobile 3D laser scanning technology is used to obtain the real 3D point cloud data of the roadway surrounding rock; secondly, the multi-scale dimensional features are used to classify the 3D point cloud data, filter the invalid point cloud data, and form the accurate point cloud data of the roadway surrounding rock surface; then the 3D laser scanning is carried out on a regular basis for the deformation-prone areas of the roadway, and the Iterative Closest Point Algorithm (ICP algorithm) is used to align the overlapping part of the point cloud to achieve the point cloud splicing and point cloud stitching of the two scans. The point cloud splicing and point cloud overlapping of the two scans are achieved; finally, the multi-scale model-to-model point cloud comparison algorithm (M3C2 algorithm) is used to compare the point cloud data of the two periods of the roadway, and the appropriate parameters are selected to indicate the displacement change of the surface of the roadway rock with the size of the color value, so as to realize the monitoring of the deformation of the roadway rock in the three-dimensional full cross-section of the roadway. The method is applied to the deformation monitoring of the surrounding rock in the return roadway of 21407 working face in a coal mine, and the results show that: the mobile laser scanning technology can be used to obtain the complete point cloud data of the roadway, and the deformation area of the surrounding rock is successfully identified after the classification of the scanned point clouds in different time periods, the alignment of the point clouds, and the comparison of the point clouds, and the deformation condition of the surrounding rock of the roadway is visually reflected in the three-dimensional full-section deformation condition of the surrounding rock of the roadway. This method is suitable for monitoring the overall de-formation of the surrounding rock of the roadway under complex environmental conditions, and the de-formation of the surrounding rock is identified by different color areas.

Zero-Velocity Update-Based GNSS/IMU Tightly Coupled Algorithm with the Constraint of the Earth's Rotation Angular Velocity for Cableway Bracket Deformation Monitoring.

Cableways have been widely used in industrial areas, cities, and scenic spots due to their advantages, such as being a convenient mode of transportation, time-saving, labor-saving, and low cost, as well as offering environmental protection. To ensure the safe operation of a cableway, based on the characteristic that the velocity of the cableway bracket is approximately zero in a static deformation monitoring environment, a deformation monitoring method called zero velocity update (ZUPT)-based GNSS/IMU tightly coupled algorithm with the constraint of the Earth's rotation angular velocity was proposed. The proposed method can effectively solve the problem of a single GNSS being unable to output attitude, which is directly related to the status of wire ropes and cable cars. Meanwhile, ZUPT is used to restrain the Kalman filter's divergence when IMU is stationary. However, the improvements of ZUPT on attitude are not obvious, so the constraint of the Earth's rotation angular velocity was applied. The performance of the proposed method was evaluated through monitoring the cableway bracket of the Yimeng Mountain Tourism area in Shandong. Compared with the ZUPT-based GNSS/IMU tightly coupled algorithm (ZUPT-TC), the proposed method can further constrain the error accumulation of IMU while stationary and, therefore, it can provide reliable position and attitude information on cableway brackets.

A New Method for Deformation Monitoring of Structures by Precise Point Positioning

Although deformations are mostly insignificant, they can be catastrophic when accumulated to certain amounts. Precise point positioning (PPP) can work with one receiver, preventing problems caused by the base station constrain upon employment of current methods such as real-time kinematics (RTK). However, current methods employing PPP focus on high-frequency monitoring such as earthquake or geological calamity monitoring, and these methods are not suitable for structures. Thus, this study proposes a new method for the deformation monitoring of structures via PPP. First, we obtained the coordinate sequence of structures via static PPP when setting the interval. Then, we transformed the coordinates to the same coordinate system with the same basis. Finally, we decomposed the sequences via empirical mode decomposition (EMD) to obtain a low-frequency part, which is the deformation of the target structure. The result of the monitoring experimentation on IGS stations shows that the monitoring index, Sd, of the sequence under different intervals using this method could be 1–2 mm on average in the directions of E, N, and U, which is much better than the original monitoring sequence. Alongside that, it prevented a fall in accuracy when the interval decreased. Therefore, all results proved the feasibility and validity of the method.

Delineation of Backfill Mining Influence Range Based on Coal Mining Subsidence Principle and Interferometric Synthetic Aperture Radar

The present study explores a three-dimensional deformation monitoring method for the better delineation of the surface subsidence range in coal mining by combining the mining subsidence law with the geometries of SAR imaging. The mining surface subsidence of the filling working face in Shandong, China, from March 2018 to June 2021, was obtained with 97 elements of Sentinel-1A data, the small baseline subset (SBAS) technique, and the proposed method, respectively. By comparison with the ground leveling of 46 observation stations, it is shown that the average standard deviation of the SBAS monitoring results is 10.3 mm; with this deviation, it is difficult to satisfy the requirements for the delimitation of the mining impact area. Meanwhile, the average standard deviation of the vertical deformation obtained by the proposed method is 6.2 mm. Compared to the SBAS monitoring accuracy, the monitoring accuracy of the proposed method is increased by 39.8%; thus, it meets the requirements for the precise delineation of the surface subsidence range for backfill mining.

Deformation Monitoring of Monopole Communication Towers Based on Multi-Source Data Fusion

Monopole communication towers play an irreplaceable role in modern communication systems. Because of its high flexibility, lateral loads control the deformation of a monopole communication tower. Dynamic displacement can be used to describe structural vibration characteristics and real-time deformation situations. Therefore, this article proposes a monopole communication tower deformation monitoring method based on multi-source data fusion using dynamic displacement as the evaluation indicator. This method calculates the strain displacement using the strain-mode superposition methodology. Then, the strain displacement and acceleration obtained are processed using Kalman filtering technology to reconstruct the real-time displacements of the monopole communication tower. The effectiveness of this method was verified using numerical simulations and model experiments, respectively. In addition, parametric analysis shows that this method is suitable for processing multi-rate data, has good noise resistance in strong noise environments, and can effectively reconstruct the displacement near the tower bottom. The results indicate that the method has favorable robustness and can accurately reconstruct low-frequency and high-frequency displacements of the monopole communication tower.

A Method for Convergent Deformation Analysis of a Shield Tunnel Incorporating B-Spline Fitting and ICP Alignment

The application of three-dimensional laser scanning technology in the field of tunnel deformation monitoring has changed the traditional measurement method. It provides an automated and intelligent solution for monitoring the geometric deformation of tunnel sections due to its high efficiency and independence from environmental influences. In this paper, based on B-spline fitting and iterative nearest point (ICP) alignment, the calculation of the difference between the radial distance and the design radius of a tunnel is transformed into a curve transformation that iterates over the nearest-neighbor points and calculates the difference in the distance between the corresponding points. The innovation of this paper is that the high-precision tunnel deformation monitoring method integrating B-spline fitting and ICP alignment can automatically compensate for the missing point clouds, is not affected by the point clouds of the tunnel inner and outer liner appendages, is more sensitive in the local deformation feedback and can be applied to a variety of tunnel shapes. The results indicate that our method maximally improves the accuracy of the horizontal convergence calculation by 28.6 mm and the accuracy of the vault settlement by 27.8 mm in comparison with the least squares circle fitting algorithm.

Investigation of deformation coordination between optical fibre and borehole sand backfill

Land subsidence has threatened the safety of municipal infrastructures and even that of inhabitants. As one of the deformation monitoring methods, distributed optical fibre sensing (DOFS) technology has been developed for the investigation of land subsidence. The deformation coordination between the optical fibre and soil (DCf-s) under different conditions is critical for land subsidence monitoring with DOFS. In this paper, a medium-sized triaxial apparatus was modified for testing the DCf-s. Consolidated drained triaxial tests were conducted to investigate the effect of sand types on the DCf-s. By linearly fitting the deformation of the sensing cable with that of the triaxial specimen, the other factors that affect the DCf-s, such as the confining pressure, dry or wet state of the soil and cyclic variation of the loads, can be discussed. The experiments reveal that better DCf-s comes with a larger particle size, poor gradation of sand and larger confining pressure. The DCf-s of wet sand is better than that of dry sand. The DCf-s coefficient tends to be stable with an increase of loading cycles. The DCf-s obtained and its dependence on influencing factors can be used to modify the measured cable strain in practical land subsidence monitoring with DOFS.

Research on Deformation Monitoring of Invert Uplifts in Soft Rock Tunnels Based on 3D Laser Scanning

The soft surrounding rock in tunnels has the characteristics of low strength, easy softening after soaking, and poor self-stability, which makes the inverted arch structure in soft rock tunnels prone to uplift deformations. Therefore, a deformation monitoring method for inverted arch uplifts of soft rock tunnels based on 3D laser scanning technology is studied to improve deformation monitoring. A Leica Scan Station2 3D laser scanner is used to collect 3D point cloud data of soft rock tunnel inverts. Using the automatic matching method of public landmarks and the improved Rodrigues parameter method, the collected 3D point cloud data are spliced and through the Mallat algorithm, the 3D point cloud data are reconstructed and processed after splicing. The whole least square method is used to fit the reconstructed 3D point cloud data. Through the principal component analysis method, the normal vector of the fitting plane is estimated and the best datum plane of the soft rock tunnel invert is found. By calculating and extracting the geometric parameters of the slice point cloud, the monitoring of inverted arch uplift deformations in soft rock tunnels is completed. The experiment shows that this method can effectively collect 3D point cloud data of soft rock tunnel inverts, and complete point cloud stitching and reconstruction. This method can effectively monitor the uplift deformation of inverted arches at different grouting depths.

InSAR-based method for deformation monitoring of landslide source area in Baihetan reservoir, China

As a cascading disaster, the surge caused by the reservoir bank landslide seriously affects the stability of the reservoir bank and the dam body. In addition, large-scale hydropower projects are usually built in mountain and canyon areas with active geological structure movement, which provides rich material sources for the occurrence of landslides, so it is of great significance to monitor the deformation in the landslide source area of the reservoir. As science and technology have been leaping forward, a wide variety of high and novel technologies have been proposed, which can be adopted to monitor landslide deformation. It is noteworthy that InSAR is capable of monitoring target monitoring areas all time under all weathers without the need to install any equipment. In this study, the time series deformation of the main landslide source area of the Baihetan reservoir after water storage was determined based on the time series InSAR method. The average annual deformation rate of the landslide source area of the Baihetan reservoir from April 2021 to January 2023 was determined by combining the Sentinel-1 SAR data of 55 ascending tracks and 46 descending tracks. Moreover, the vegetation cover variations from April 2021 to January 2023 in the study area were determined by combining the remote sensing data of Landsat8-9. A total of four typical source areas were selected based on the field investigation to analyze the deformation monitoring results and the vegetation cover variations. As indicated by the results: 1) After water storage, the slope deformation in all source areas was larger in the short term, and the deformation rate of the lower part turned out to be more significant, and the deformation rate exceeded 334.583 mm/year. 2) On the steep slope, the effect of different types of vegetation on restraining deformation was different. The optimal effect was reported in shrubs, followed by grasslands, and the worst effect was reported in woodlands. The results of this study can provide scientific support for the prevention and control of regional geological disasters.

BDS Dual-Frequency Carrier Phase Multipath Hemispherical Map Model and Its Application in Real-Time Deformation Monitoring.

The BDS multipath delay error is highly related to the surrounding monitoring environment, which cannot be eliminated or mitigated by applying the double difference observation model. In the actual monitoring environment, due to the complexity of the BDS constellation, it is difficult for existing algorithms to consider GEO, IGSO, MEO and other different orbital types of satellites for real-time and efficient multipath error reduction. Therefore, we propose a novel BDS dual-frequency multipath error reduction method for real deformation monitoring for BDS considering various satellite orbit types. This method extracts the single error residual of each satellite based on the assumption of "zero mean" and divides the appropriate grid density of GEO and IGSO/MEO, respectively, to construct a dual-frequency multipath hemispherical map model suitable for BDS satellites with different orbital types. This method can realize the multipath error elimination of the observed values of different orbits and different frequencies. The results of simulation experiments and real deformation monitoring data demonstrate that this method can effectively eliminate low-frequency multipath delay errors in the observation domain and coordinate domain. After multipath correction, the precision of the horizontal coordinates and height coordinates are 1.7 mm and 4.6 mm. The precision of the horizontal coordinate and height coordinate is increased by 50% and 60%, respectively. The fixed rate of ambiguity increased by 5-7%.

Creep Monitoring of Submersible Observation Windows Using Mueller Matrix Imaging.

Safety of the observation window is one of the core concerns for manned submersibles. When subjected to underwater static pressure, extrusion and creep deformation always occur in the observation window, which can pose a threat to both safety and optical performance. To assess the deformation, real-time and non-contact monitoring methods are necessary. In this study, a conceptual setup based on the waveplate rotation and dual-DoFP (division of focal-plane polarimeter) polarization camera is built for the observation window's creep monitoring by measuring the Mueller matrix images of the samples under different pressures and durations. Then, a series of characteristic parameters, such as t1, R, r, R', are extracted from the Muller matrix images by Mueller matrix transformation (MMT), Mueller matrix polar decomposition (MMPD), correlation analysis and phase unwrapping method. The results demonstrate that these parameters can effectively describe the observation window's creep at different pressure levels which are simulated by finite element analysis. Additionally, more characterization parameters, such as ψ, A and D, are given from the Mueller matrix images and discussed to illustrate the method's potential for further applications and investigations. Ultimately, future devices based on this method could serve as a valuable tool for real-time and non-contact creep monitoring of the submersible observation windows.

A Case Study on the Application of 3D Scanning Technology in Deformation Monitoring of Slope Stabilization Structure

Traditional deformation monitoring suffers from issues such as the point-based representation of surfaces and low measurement efficiency. Moreover, the majority of researchers study the deformation of slopes using methods such as 3S technology, synthetic aperture radar interferometry, distributed fiber optic sensing technology, etc. Based on this, a slope stabilization structure deformation monitoring method based on 3D laser scanning technology is proposed. First, with the slope stabilization structure of Caihong Road as the engineering background, point cloud data of the slope stabilization structure is obtained using a Trimble SX10 device. Second, the point deformation, overall deformation, and line deformation of the two-phase slope stabilization structure point cloud data are analyzed. Finally, the measurement accuracy of the 3D laser scanning technology is evaluated. The results show that the deformation analysis of points, lines, and surfaces can complement each other, thereby comprehensively assessing the situation of slope stabilization structure deformation. Moreover, the maximum displacement value in the deformation of points, lines, and surfaces is 8.52 mm, which does not exceed the standard, and 93.61% of the point deformation is between −0.76~0.92 mm, indicating that the slope stabilization structure is in a safe and stable state. The independent sample t-test has a test statistic of t = 2.074, verifying that the 3D laser scanning technology and the total station measurement accuracy are highly consistent and can meet the needs of actual engineering. The results of this study can provide a reasonable theoretical and methodological reference for analyzing similar engineering deformation monitoring in the future.

Wall length-based deformation monitoring method of brick-concrete buildings in mining area using terrestrial laser scanning

Wall length-based deformation monitoring method of brick-concrete buildings in mining area using terrestrial laser scanning

Research on regionalised digital image slope monitoring methods.

The digital image correlation method is a high precision and non-contact ground deformation monitoring method, which is widely used in surface deformation monitoring. However, according to its principle, different surface characteristics have great influence on the monitoring results. In this paper, a regional digital image slope monitoring method is established to meet the monitoring requirements of different areas of the same slope. Firstly, the features of different regions in the image are identified according to the optical region detection, and then the deformation calculation method is matched according to the features of different regions. Finally, according to the binocular vision principle, the three-dimensional displacement of the slope is obtained. Taking a highway slope in Qinhuangdao as an example, we realised all-weather and full-field deformation monitoring of slope, and verified the applicability and feasibility of regional digital image slope monitoring method. The applicability of digital image correlation method in slope monitoring is improved.

Parallel Optimization for Large Scale Interferometric Synthetic Aperture Radar Data Processing

Interferometric synthetic aperture radar (InSAR) has developed rapidly over the past years and is considered as an important method for surface deformation monitoring, benefiting from growing data quantities and improving data quality. However, the handing of SAR big data poses significant challenges for related algorithms and pipeline, particularly in large-scale SAR data processing. In addition, InSAR algorithms are highly complex, and their task dependencies are intricate. There is a lack of efficient optimization models and task scheduling for InSAR pipeline. In this paper, we design parallel time-series InSAR processing models based on multi-thread technology for high efficiency in processing InSAR big data. These models concentrate on parallelizing critical algorithms that have high complexity, with a focus on deconstructing two computationally intensive algorithms through loop unrolling. Our parallel models have shown a significant improvement of 10–20 times in performance. We have also developed a parallel optimization tool, Simultaneous Task Automatic Runtime (STAR), which utilizes a data flow optimization strategy with thread pool technology to address the problem of low CPU utilization resulting from multiple modules and task dependencies in the InSAR processing pipeline. STAR provides a data-driven pipeline and enables concurrent execution of multiple tasks, with greater flexibility to keep the CPU busy and further improve CPU utilization through predetermined task flow. Additionally, a supercomputing-based system has been constructed for processing massive InSAR scientific big data and providing technical support for nationwide surface deformation measurement, in accordance with the framework of time series InSAR data processing. Using this system, we processed InSAR data with the volumes of 500 TB and 700 TB in 5 and 7 days, respectively. Finally we generated two maps of land surface deformation all over China.