Structural Displacement Monitoring Research Articles

Water Level Retrieval Using a posteriori Residual of GNSS Pseudorange and Carrier-Phase Observations

In global navigation satellite system reflectometry (GNSS-R) applications, water level variations could be determined by analyzing one of three types of data: signal-to-noise ratios (SNRs), combinations of carrier-phase observations and combinations of pseudorange and carrier-phase observations. In this study, a new GNSS-R method based on the analysis of a posteriori residual of undifferenced and uncombined (UC) Precise Point Positioning (PPP) and ionosphere free (IF) PPP was proposed. Double peaks were found in the Lomb-Scargle periodogram (LSP) estimates of dual-frequency carrier-phase residuals generated with UC PPP, the pseudorange and carrier-phase residuals generated with IF PPP and the detrended S2 time series. To solve this problem, we present a strict quality control strategy to screen the correct retrievals. Two experimental datasets from a dam and a bridge-deformation monitoring system, respectively, were used to evaluate the performance of this new method in water-level retrieval. The results show that the water level retrievals from the pseudorange and carrier-phase residuals generated by the UC PPP and IF PPP positioning method show a good agreement with the in-situ references, with correlation coefficient exceeding 0.95 and 0.97 in the two experiments, which is comparable to the SNR method. The retrievals showed a root mean square error (RMSE) of 6-7cm in the reservoir experiment and 13-16cm in the Ganjiang river experiment. Meanwhile, the inter-frequency bias for about 0.2m was found in the Xilongchi reservoir water level retrieval experiment, however, it is not the case for the Ganjiang River water level retrieval experiment. The new method enables the simultaneous determination of displacements and water-level variation and is thus applicable for in-situ displacement monitoring of civil engineering structures, such as dam, bridge etc.

Vibration Monitoring of Civil Engineering Structures Using Contactless Vision-Based Low-Cost IATS Prototype.

The role and importance of geodesists in the planning and building of civil engineering constructions are well known. However, the importance and benefits of collected data during maintenance in exploitation have arisen in the last thirty years due primarily to the development of Global Positioning Systems (GPS) and Global Navigation Satellite System (GNSS) instruments, sensors and systems, which can receive signals from multiple GPS systems. In the last fifteen years, the development of Terrestrial Laser Scanners (TLS) and Image-Assisted Total Stations (IATS) has enabled much wider integration of these types of geodetic instruments with their sensors into monitoring systems for the displacement and deformation monitoring of structures, as well as for regular structure inspections. While GNSS sensors have certain limitations regarding their accuracy, their suitability in monitoring systems, and the need for a clean horizon, IATS do not have these limitations. The latest development of Total Stations (TS) called IATS is a theodolite that consists of a Robotic Total Station (RTS) with integrated image sensors. Today, IATS can be used for structural and geo-monitoring, i.e., for the determination of static and dynamic displacements and deformations, as well as for the determination of civil engineering structures’ natural frequencies. In this way, IATS can provide essential information about the current condition of structures. However, like all instruments and sensors, they have their advantages and disadvantages. IATS’s biggest advantage is their high level of accuracy and precision and the fact that they do not need to be set up on the structure, while their biggest disadvantage is that they are expensive. In this paper, the developed low-cost IATS prototype, which consists of an RTS Leica TPS1201 instrument and GoPro Hero5 camera, is presented. At first, the IATS prototype was tested in the laboratory where simulated dynamic displacements were determined. After the experiment, the IATS prototype was used in the field for the purpose of static and dynamic load testing of the railway bridge Kloštar, after its reconstruction according to HRN ISO NORM U.M1.046—Testing of bridges by load test. In this article, the determination of bridge dynamic displacements and results of the computation of natural frequencies using FFT from the measurement data obtained by means of IATS are presented. During the load testing of the bridge, the frequencies were also determined by accelerometers, and these data were used as a reference for the assessment of IATS accuracy and suitability for dynamic testing. From the conducted measurements, we successfully determined natural bridge frequencies as they match the results gained by accelerometers.

Modeling and detection of heat haze in computer vision based displacement measurement

Computer vision has become widely applied for structural displacement monitoring. However, heat haze is one of the major challenges. Image distortions caused by heat haze in hot weather can result in displacement errors. Therefore, a comprehensive study of properties of heat haze-induced distortions and displacement errors is conducted. Firstly, an image distortion estimation method is proposed for estimating heat haze-induced image distortions. Secondly, displacement errors due to heat haze are analyzed. A heat haze error model is formulated to describe the properties of heat haze errors, and the explicit effect of the environmental factor of temperature on the heat haze error model. Thirdly, a heat haze detection method is proposed to enable detection of heat haze’s influence on vision-based displacement sensors by extracting features from distortion measurements and applying a classification algorithm. Field tests in hot weather and experiments with dark heaters for introducing heat haze are conducted for validations.

Experimental Study on the Displacement Sensor of Coal Roadways Roof Settlement Based on Distributed Fiber Optic Sensing

Roof displacement monitoring is an important means to ensure roof stability and prevent roof accidents of Coal Roadways (CRs). In this paper a new sensor of roof settlement displacement (RSD) monitoring of CRs' roof by the pre-stretched optical fiber (PSOF) laid out horizontally at fixed points was proposed. The principle of the sensor is to qualitively and quantitively characterize the RSD by the Fiber Optic Strain (FOS) which is measured based on distributed fiber optic strain measurement. Through theoretical analysis, the mathematical expression for quantifying RSD is derived. The correctness of the sensor is verified by the indoors FOS experiments and the field monitoring of CRs' roof in Yinying Coal Mine. This new sensor can be applied not only to the roof of CRs, but also to the displacement monitoring of other structures with the similar settlement presentation.

Structural displacement monitoring based on mask regions with convolutional neural network

Displacement monitoring is an important part of structural health monitoring. This paper proposes a structural displacement monitoring method based on mask regions with convolutional neural network (Mask R-CNN), which combines deep learning with machine vision to extract the coordinates of calibration object. First, a calibration object dataset was collected. The dataset contains 165 images. Second, the dataset was trained by Mask R-CNN to obtain a monitoring model, which can generate a mask to cover the calibration object in the image. Third, the mask information is extracted from the image to obtain the coordinates of calibration object. Finally, the structure displacement can be obtained by the coordinates. In this paper, the method is applied to the static displacement monitoring and dynamic displacement monitoring. The results showed that average error of static displacement monitoring is 2.05%, and the correlation coefficient between monitoring results of the proposed method and laser displacement sensor monitoring results is as high as 0.9836 in dynamic displacement monitoring. To solve the problem of remote displacement monitoring, a telephoto lens was mounted on a smartphone to monitor displacement of 10 m distance. The results showed that the average error of remote displacement monitoring is 4.18%.

Radar-based multipoint displacement measurements of a 1200-m-long suspension bridge

Structural displacement monitoring remains a challenging problem, especially for long-span bridges. A ground-based microwave interferometric radar system was developed and used to obtain multipoint displacement measurements of a suspension bridge with a main span of 1200 m. First, a microwave interferometric radar system with the merits of low price, straightforward usage, and good stability and robustness was developed. The phase was obtained by performing fast Fourier transform (FFT) of the in-phase/quadrature signals and calculating the displacement according to the phase interference. Second, the radar system was used in field tests of a long-span suspension bridge, including static, ambient vibration, and moving load tests. Multipoint displacements of the bridge girder, tower, and cables were obtained, and simultaneous measurements of the multipoint displacement influence lines of the bridge girder were performed. A method that uses three reference points to measure the bridge girder displacement was proposed. Good agreements between the results from the developed radar system and those from traditional sensors, including connecting pipes and total stations, demonstrated the excellent performance of the proposed method for remote multipoint displacement measurements of long-span bridges.

Experimental Investigation and Error Analysis of High Precision FBG Displacement Sensor for Structural Health Monitoring

High precision structural displacement monitoring is challenging, but an effective method for structural health monitoring and particularly damage evaluation. In this paper, a high precision fiber Bragg grating (FBG) displacement sensor with embedded spring is developed to monitor structural displacement variation even at very small ranges. The principle of such monitoring is based on the central wavelength shifts in accordance with the displacement between measuring points. Calibration experiments are conducted to examine the performance of the innovative displacement sensor. The result indicates that the sensor has excellent linearity and repeatability, with the sensitivity coefficient being 23.96[Formula: see text]pm/mm, and the static relative error is 4.94% after three loading and unloading cycles. The displacement sensor therefore shows an excellent sensitivity and high precision for application. Moreover, it has been verified that this sensor is suitable and applicable for displacement monitoring in quasi-static experiment of structures.

Structural Shape Estimation by Mode Shapes Using Fiber Bragg Grating Sensors: A Genetic Algorithm Approach

Structural shape estimation is of great interest in many engineering fields including aerospace and civil engineering. During operation, however, the monitoring of structural displacements is often difficult. This article discusses structural shape estimation using a minimal number of fiber Bragg grating sensors. A strain to displacement transformation matrix is derived using mode shapes, to estimate the global displacement of a structure from measured discrete strain data. The number of sensors and sensor layout for the shape estimation is optimized using genetic algorithm. Static and dynamic displacement experiments are conducted on an aluminum plate to verify the algorithm. The deformation during static experiments is measured at nine different locations and estimation error was less than 0.5%. The deformation during dynamic excitation is measured at one selected location using a noncontact laser sensor. The shape estimation quality is better for resonance frequencies compared to off-resonance frequencies. The results show that the estimated displacements match well with those measured displacements.

Review of Computer Vision-based Structural Displacement Monitoring

Review of Computer Vision-based Structural Displacement Monitoring

Extended D-TomoSAR Displacement Monitoring for Nanjing (China) City Built Structure Using High-Resolution TerraSAR/TanDEM-X and Cosmo SkyMed SAR Data

The availability of high-resolution spaceborne synthetic aperture radar (SAR) data coupled with the ongoing refinement of tomographic SAR (TomoSAR) technology has made use of radar data feasible for preventive monitoring and assessment of built structures. In this study, we first applied extended differential TomoSAR (D-TomoSAR) to a set of 26 scenes of TerraSAR/TanDEM-X (TSX/TDX) (2013–2015) and 32 scenes of Cosmo-SkyMed (CSK) (2015–2017) images to estimate motions of skyscrapers, bridges and historical monuments in Nanjing City, China. The calculation and isolation of unknown parameters in the D-TomoSAR model, including linear velocity, thermal dynamics and structural heights, helped to estimate millimetric statistics of motion time series. Then, aforementioned two SAR datasets were tentatively tested using amplitude dispersion and phase stability indicators, highlighting the performance and sensitivity of X-band SAR in structural displacement monitoring. Experimental results demonstrated that motion indexes, e.g., heterogeneities of thermal amplitudes and spatiotemporal displacements, were useful to evaluate the conditions of built structures being monitored, in particular when their structural topology were visible owing to the enhanced density of persistent scatterer (PS) measurements. This study implies the value of high-resolution D-TomoSAR tools in the preventive monitoring and health diagnosis of built structures elsewhere over the world.

Detection of Structural Vibration with High-Rate Precise Point Positioning: Case Study Results Based on 100 Hz Multi-GNSS Observables and Shake-Table Simulation.

This contribution presents and assesses the methodology aiming at the characterization of the structural vibrations with high-rate GNSS measurements. As commonly employed precise point positioning (PPP) based on ionosphere-free linear combination of undifferenced signals may not meet the high requirements in terms of displacement precision, a modified processing strategy has been proposed. The algorithms were implemented in the own-developed GNSS processing software and validated using the designed experiment. For this purpose, we have set up a field experiment taking advantage of the prototype shake-table, which simulated the dynamic horizontal displacements of the GNSS antenna. The device ensured a periodic motion of the antenna with modifiable characteristics, namely amplitude and frequency. In this experiment, we have set the amplitudes from 1.5 to 9 mm and the frequency to 3.80 Hz. As a dataset, we have used 100 Hz GPS, Galileo, and BDS measurements. The results confirmed a high applicability of the enhanced PPP processing strategy for precise displacement detection. Specifically, it was feasible to obtain the dynamic displacements with precision at the level of millimeters. The differences between the PPP-derived amplitude and the true amplitude of the simulated displacements were in the range of 0.5–1.3 mm, whereas the difference between the detected and benchmark frequency did not exceed 0.026 Hz. Hence, the proposed methodology allows meeting the specific demands of structural displacement monitoring.

Structural displacement monitoring using deep learning-based full field optical flow methods

Current vision-based displacement measurement methods have limitations such as being in need of manual targets and parameter adjustment, and significant user involvement to reach the desired result. This study proposes a novel structural displacement measurement method using deep learning-based full field optical flow methods. The performance of the proposed method is verified via a laboratory experiment conducted on a grandstand structure with a comparative study, where the same data samples are analysed with a commonly used vision-based method, and a displacement sensor measurement is used as the ground truth. Statistical analysis of the comparative results show that the proposed method gives higher accuracy than the traditional optical flow algorithm and shows consistent results in compliance with displacement sensor measurements. Image collection, tracking, and non-uniform sampling are investigated in the experimental data and suggestions are made to obtain more accurate displacement measurements. A field-validation on a footbridge showed that the measurement error induced by the camera motion is mitigated by a camera motion subtraction procedure. The proposed method has good potential to be applied by structural engineers, who have little or no experience in computer vision and image processing, to do vision-based displacement measurements.

Notice of Removal: Structural Displacement Monitoring Using Smartphone Camera and Digital Image Correlation

Smartphones, which houses various onboard sensors and a camera, can be leveraged for structural health monitoring. In this paper, an iPhone’s camera coupled with a custom iOS app, D- Viewer , is employed for 3-D structural displacement monitoring. Based on the digital image correlation technique, the camera is used to track a circular target, and the app determines its in-plane, out-of-plane, and arbitrary direction displacements within the field of view. A series of static and dynamic experiments is conducted to validate the proposed technique.

Monitoring of Bridges by a Laser Pointer: Dynamic Measurement of Support Rotations and Elastic Line Displacements: Methodology and First Test.

Deck inclination and vertical displacements are among the most important technical parameters to evaluate the health status of a bridge and to verify its bearing capacity. Several methods, both conventional and innovative, are used for structural rotations and displacement monitoring; however, none of these allow, at the same time, precision, automation, static and dynamic monitoring without using high cost instrumentation. The proposed system uses a common laser pointer and image processing. The elastic line inclination is measured by analyzing the single frames of an HD video of the laser beam imprint projected on a flat target. For the image processing, a code was developed in Matlab® that provides instantaneous rotation and displacement of a bridge, charged by a mobile load. An important feature is the synchronization of the load positioning, obtained by a GNSS receiver or by a video. After the calibration procedures, a test was carried out during the movements of a heavy truck maneuvering on a bridge. Data acquisition synchronization allowed us to relate the position of the truck on the deck to inclination and displacements. The inclination of the elastic line at the support was obtained with a precision of 0.01 mrad. The results demonstrate the suitability of the method for dynamic load tests, and the control and monitoring of bridges.

An enhanced inverse finite element method for displacement and stress monitoring of multilayered composite and sandwich structures

The inverse finite element method (iFEM) is an innovative framework for dynamic tracking of full-field structural displacements and stresses in structures that are instrumented with a network of strain sensors. In this study, an improved iFEM formulation is proposed for displacement and stress monitoring of laminated composite and sandwich plates and shells. The formulation includes the kinematics of Refined Zigzag Theory (RZT) as its baseline. The present iFEM methodology minimizes a weighted-least-squares functional that uses the complete set of strain measures of RZT. The main advantage of the current formulation is that highly accurate through-the-thickness distributions of displacements, strains, and stresses are attainable using an element based on simple C0-continuous displacement interpolation functions. Moreover, a relatively small number of strain gauges is required. A three-node inverse-shell element, named i3-RZT, is developed. Two example problems are examined in detail: (1) a simply supported rectangular laminated composite plate and (2) a wedge structure with a hole near one of the clamped ends. The numerical results demonstrate the superior capability and potential applicability of the i3-RZT/iFEM methodology for performing accurate shape and stress sensing of complex composite structures.

Dynamic characteristic of tall industrial chimney estimated from GPS measurement and frequency domain decomposition

This paper is concerned with the analysis of the capabilities and limitations of the use of horizontal dynamic displacements measured by the Global Positioning System (GPS) technology along a vertical profile of a tall industrial chimney under wind excitations to investigate its dynamic characteristics, i.e. the natural frequencies, mode shapes and structural damping ratios. The analysis was performed using Frequency Domain Decomposition (FDD) approach. The basic characteristics of the background noise of GPS technology are examined in the time and frequency domain based on the result of a static test. The field tests were conducted on the chimney, located in Belchatow Power Plant in Poland, using three GPS rover units. The GPS units were installed at three levels of the chimney to measure its horizontal deformation along a vertical profile due to the wind. The GPS receivers were able to measure only the first natural frequency of the chimney. The reasons of the harmful multipath and shielding effects and their influence on the reliability of the measurement results were explained. In order to mitigate the spectral leakage effects as well as to improve the accuracy of damping ratio estimation the windowing procedure was adopted with a selected number of samples LN, determining the duration of a window function. The influence of the LN number on the damping ratio estimation was examined and suitable LN number was recommended. The dynamic characteristics of the chimney were investigated based on the dynamic wind response considered in selected directions in the horizontal plane. The obtained experimental results were compared with the predicted values derived from the finite element analysis as well as with the experimental results based on a measured tip displacement of the chimney by GPS technique using Random Decrement Method. It was shown that the structural dynamic characteristics as well as displacement monitoring of tall slender structures under wind excitations can be effectively determined based on GPS measurements at various levels along the vertical profile.

Dynamic displacement monitoring of flexural structures with distributed long-gage macro-strain sensors

A new method is proposed to monitor dynamic displacement for flexural structures especially. In this method, the distributed macro-strain is first obtained using long-gage fiber Bragg grating sensors. Then, the conjugated beam theory is applied to calculate the displacement. To verify the method, a cantilever beam, installed with the proposed sensors, is subjected to free vibrations. The results from the proposed method agree well with those measured by the traditional displacement transducer as the error for the first three peak values is less than 5%. A finite element model of a simply supported multi-girder bridge is also simulated with a truck load. The results show that the proposed method can evaluate dynamic displacement accurately as the error for the maximum displacement is less than 3% in all the cases. Finally, the method is verified using simply supported beam models subjected to random dynamic loads. However, the sensor gage length shows some influence on the results. To ensure exact measurements, the sensor gage length should be limited to be smaller than 1/20 of the beam length. Considering other advantages of fiber optic sensing, the proposed method shows promise in the field of long-term structural health monitoring.

Laser pose calibration of ViSP for precise 6-DOF structural displacement monitoring

To estimate structural displacement, a visually servoed paired structured light system (ViSP) was proposed in previous studies. The ViSP is composed of two sides facing each other, each with one or two laser pointers, a 2-DOF manipulator, a camera, and a screen. By calculating the positions of the laser beams projected onto the screens and rotation angles of the manipulators, relative 6-DOF displacement between two sides can be estimated. Although the performance of the system has been verified through various simulations and experimental tests, it has a limitation that the accuracy of the displacement measurement depends on the alignment of the laser pointers. In deriving the kinematic equation of the ViSP, the laser pointers were assumed to be installed perfectly normal to the same side screen. In reality, however, this is very difficult to achieve due to installation errors. In other words, the pose of laser pointers should be calibrated carefully before measuring the displacement. To calibrate the initial pose of the laser pointers, a specially designed jig device is made and employed. Experimental tests have been performed to validate the performance of the proposed calibration method and the results show that the estimated displacement with the initial pose calibration increases the accuracy of the 6-DOF displacement estimation.

Structural displacement and strain monitoring based on the edge detection operator

To decrease the cost of instrumentation for the strain and displacement monitoring method that uses sensors as well as considers the structural health monitoring challenges in sensor installation, it is necessary to develop a machine vision-based monitoring method. For this method, the most important step is the accurate extraction of the image feature. In this article, the edge detection operator based on multi-scale structure elements and the compound mathematical morphological operator is proposed to provide improved image feature extraction. The proposed method can not only achieve an improved filtering effect and anti-noise ability but can also detect the edge more accurately. Furthermore, the required image features (vertex of a square calibration board and centroid of a circular target) can be accurately extracted using the extracted image edge information. For validation, the monitoring tests for the structural local mean strain and in-plane displacement were designed accordingly. Through analysis of the error between the measured and calculated values of the structural strain and displacement, the feasibility and effectiveness of the proposed edge detection operator are verified.

High-speed 6-DOF structural displacement monitoring by fusing ViSP (Visually Servoed Paired structured light system) and IMU with extended Kalman filter

In previous studies, a visually servoed paired structured light system (ViSP) was proposed to estimate structural displacement with high accuracy at low cost. Although the performance of the system has been verified from various simulations and experimental tests, it has a limitation that high-speed dynamic displacement cannot be measured properly due to the relatively low sampling rate. To speed up ViSP, in this paper, an inertial measurement unit (IMU) with a high sampling rate is concurrently used with ViSP in a Kalman filtering framework. By combining measured accelerations and angular velocities from the IMU with the estimated 6-DOF displacement from ViSP, high-speed structural movement can be monitored with high accuracy. In the proposed data fusion method, named ViSP-IMU, random biases of the IMU are calibrated by using the estimated displacement results from ViSP-IMU. We perform experimental tests and verify the efficacy of the proposed algorithm as a promising structural displacement estimation method which guarantees high accuracy and a high sampling rate. Also, the proposed bias compensation method can effectively reduce the displacement estimation error by minimizing the difference between estimated displacements from the IMU and ViSP-IMU. Copyright © 2016 John Wiley & Sons, Ltd.