Multi-point Displacement Measurements Research Articles

A lightweight convolutional neural network for multipoint displacement measurements on bridge structures

A lightweight convolutional neural network for multipoint displacement measurements on bridge structures

A Novel Method for Full‐Field Scale Factor Calculation under Off‐Axis Measurements for Vision‐Based Structural Multipoint Displacement Measurement and Health Monitoring

For vision‐based structural displacement measurement and health monitoring, the scale factor (SF) calculation plays a pivotal role in converting the pixel displacement into the actual one. On the other hand, for the current SF calculation methods, the object distance, between the to‐be‐measured points on the object plane and the optical center of the shooting instrument, has to be measured in advance due to the existence of the pitch and horizontal angle under off‐axis measurement. Unfortunately, it is usually inefficient, difficult, and even impossible to obtain the object distances for all the to‐be‐measured points, especially for the full‐field displacement monitoring on huge scale structures. In this paper, a novel SF calculation method was proposed to calculate the full‐field scale factor of the host structure under off‐axis measurement by combining with the similarity relation of the camera imaging model. With the help of this method, all the scale factors of the to‐be‐measured points can be calculated accurately and highly efficiently, as long as the object distance of any one point or the geometric dimensions of any feature object on the object surface is provided. In addition, to quantitatively assess the SF calculation accuracy of the method, a static vision‐based measurement investigation was firstly conducted, and then, two experimental investigations about the multipoint and full‐field structural displacement measurement on a cable‐stayed bridge model and a simply supported beam model were conducted to validate the effectiveness and feasibility of the proposed method. Finally, all the results demonstrated that the proposed method exhibits an excellent performance on the SF calculation under off‐axis measurement and provides a great potential to be utilized for the vision‐based structural multipoint and full‐field displacement measurement and health monitoring.

Multipoint displacement measurement based on low intracavity-loss FLRD method

In this paper, we propose a method of multipoint displacement measurement using fiber-loop ring-down (FLRD) technology. We demonstrated the feasibility of multipoint displacement measurement using three cascaded FLRDs. Single-mode optical fiber wrapped around the cylinder airbag surface (CA-SMF) is used as the displacement sensor. Due to the low insertion loss of CA-SMF and the high-power modulated signal output of OTDR, it is not necessary to add any device for compensating the pulse signal power in FLRD. Finally, we also consider the errors that arise in the engineering manufacturing process. We have experimentally demonstrated that the length and intrinsic losses of FLRD do not affect the sensing performance of displacement sensors in a reasonable range, which is extremely helpful for practical engineering applications.

A hybrid method for damage detection and condition assessment of hinge joints in hollow slab bridges using physical models and vision-based measurements

The simply supported slab bridge is a typical perfricated reinforced concrete bridge. Under the influence of increasing vehicle loads and natural environmental erosion, the hinge joints between slabs suffer from damage that cannot be easily evaluated, which brings negative effects on the load carrying capacity of bridges. In the present study, a hybrid method for damage detection and condition assessment of hinge joints in hollow slab bridges using physical models and vision-based measurements was proposed. The stiffness reduction of hinge joints is taken as the damage degree and condition level of the inspected hinge joints. An analytical model of a simplified spring-mass system was firstly built to demonstrate the applicability of using the relative displacement ratio as the damage index of hinge joints. The relationship between the relative displacement ratio and the stiffness reduction of hinge joints was then studied thoroughly through a parametric study on finite element models considering different damage levels of hinge joints. Thresholds of the relative displacement ratio were defined to classify the damage states of hinge joints. The damage index of target hinge joints can be calculated from the actual data provided by using computer vision-based multi-camera and multi-point displacement measurements. Lastly, the application of a real-life bridge under normal traffic was demonstrated to verify the feasibility of the quantitative evaluation of the service status of joints in hinged-slab bridges. It indicated that the proposed method could evaluate the damage degree of joints quantitatively, effectively and economically.

Scheimpflug Camera-Based Technique for Multi-Point Displacement Monitoring of Bridges.

Owing to the limited field of view (FOV) and depth of field (DOF) of a conventional camera, it is quite difficult to employ a single conventional camera to simultaneously measure high-precision displacements at many points on a bridge of dozens or hundreds of meters. Researchers have attempted to obtain a large FOV and wide DOF by a multi-camera system; however, with the growth of the camera number, the cost, complexity and instability of multi-camera systems will increase exponentially. This study proposes a multi-point displacement measurement method for bridges based on a low-cost Scheimpflug camera. The Scheimpflug camera, which meets the Scheimpflug condition, can enlarge the depth of field of the camera without reducing the lens aperture and magnification; thus, when the measurement points are aligned in the depth direction, all points can be clearly observed in a single field of view with a high-power zoom lens. To reduce the impact of camera motions, a motion compensation method applied to the Scheimpflug camera is proposed according to the characteristic that the image plane is not perpendicular to the lens axis in the Scheimpflug camera. Several tests were conducted for performance verification under diverse settings. The results showed that the motion errors in x and y directions were reduced by at least 62% and 92%, respectively, using the proposed method, and the measurements of the camera were highly consistent with LiDAR-based measurements.

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.

Displacement measurement of concrete bridges by the sampling Moiré method based on phase analysis of repeated pattern

AbstractMeasuring accurate deformation distribution of large‐scale structures inexpensively and efficiently is a crucial challenge of structural health monitoring. Phase‐based imaging technique has great potential for accurate and robust multipoint displacement measurement in the field. In this study, the sampling Moiré method—one of the promising optical techniques—was applied to the displacement measurement of a concrete bridge for the high‐speed railway in Japan. Using retroreflective Moiré markers, the two‐dimensional in‐plane displacements at multiple locations could be easily measured from recorded digital images at a distance of 20 m regardless of day and night. Results of the dynamic deflection obtained from the sampling Moiré method were in good agreement with those from a conventional laser Doppler vibrometer. The time series of two‐dimensional displacement analyses when the outbound or inbound trains passed at the speed of 150 or 320 km/h through the bridge revealed that the points at the centre and the quarter of the bridge span demonstrated complex deformation behaviour showing elliptical rotation. The effects of random noise of the recorded image were quantitatively investigated, and the air fluctuation was discussed from the field experiments. We proved that measurements using the sampling Moiré method could be more stable at night than daytime.

Dam Structure Deformation Monitoring by GB-InSAR Approach

Ground-based synthetic aperture radar (GB-SAR) has been proved to be one of the cutting-edge techniques for the timely detection of slope failures in both natural and engineered slopes. This paper focuses on the structure deformation monitoring on the dams using GB-SAR data. Temporal sequence data was collected by ground SAR equipment from 29 July to 1 August for the Geheyan dam and the SAR images with high quality were selected through the exhaustive spatial-temporal coherence analysis based on permanent scatterer (PS) theory in this paper. A practical solution for dam structure deformation extraction after the atmospheric effect reduction is proposed in depth. The deformation of the dam spillway gates is greater than that of the dam body monitored by this GB-SAR campaign, and with the increase of the water level in the reservoir area, the displacement increases along the direction of water flow gradually. The surface deformation rate of the dam body is fitted by linear regression analysis, and the interpolated rate results are compared and verified with the plumb line measurements. Finally, the consistency of the dam deformation average rate based on the PS time series analysis technology by GB-SAR and plumb lines is verified in this article, demonstrated the excellent performance of the proposed method for remote multipoint displacement measurements of the dam.

Marker-free monitoring of the grandstand structures and modal identification using computer vision methods

In this study, a vision-based multi-point structural dynamic monitoring framework is proposed. This framework aims to solve issues in current vision-based structural health monitoring. Limitations are due to manual markers, single-point monitoring, and synchronization between a multiple-camera setup and a sensor network. The proposed method addresses the first issue using virtual markers—features extracted from an image—instead of physical manual markers. The virtual markers can be selected according to each scenario, which makes them versatile. The framework also overcomes the issue of single-point monitoring by utilizing an advanced visual tracking algorithm based on optical flow, allowing multi-point displacement measurements. Besides, a synchronization mechanism between a multiple-camera setup and a sensor network is built. The proposed method is first tested on a grandstand simulator located in the laboratory. The experiment is to verify the performance of displacement measurement of the proposed method and conduct structural identification of the grandstand through multi-point displacement records. The results from the proposed method are then compared to the data gathered by traditional displacement sensors and accelerometers. A second experiment is conducted at a stadium during a football game to validate the feasibility of field application and the operational modal identification of the stadium under human crowd jumping through the measured displacement records. From these experiments, it is concluded that the proposed method can be employed to identify modal parameters for structural health monitoring.

Development and Field Testing of a Time-Synchronized System for Multi-Point Displacement Calculation Using Low-Cost Wireless Vision-Based Sensors

This paper presents a contactless multi-point displacement measurement system using multiple synchronized wireless cameras. Our system makes use of computer vision techniques to perform displacement calculations, which can be used to provide a valuable insight into the structural condition and service behavior of bridges under live loading. The system outlined in this paper provides a low-cost durable solution, which is rapidly deployable in the field. The architecture of this system can be expanded to include up to ten wireless vision sensors, addressing the limitation of current existing solutions limited in scope by their inability to reliably track multiple points on medium- and long-span bridge structures. Our multi-sensor approach facilitates multi-point displacement and additional vision sensors for vehicle identification and tracking that could be used to accurately relate the bridge displacement response to the load type in the time domain. The performance of the system was validated in a series of controlled laboratory tests. This paper will significantly advance current vision-based structural health monitoring systems, which can be cost prohibitive and provides a rapid method of obtaining data which accurately relates to measured bridge deflections.

Sensing dynamic displacements in masonry rail bridges using 2D digital image correlation

Dynamic displacement measurements provide useful information for the assessment of masonry rail bridges, which constitute a significant part of the bridge stock in the United Kingdom and Europe. Commercial 2D digital image correlation (DIC) techniques are well suited for this purpose. These systems provide precise noncontact displacement measurements simultaneously at many locations of the bridge with an easily configured camera set-up. However, various sources of errors can affect the resolution, repeatability, and accuracy of DIC field measurements. Typically, these errors are application specific and are not automatically corrected by commercial software. To address this limitation, this paper presents a survey of relevant DIC errors and discusses methods to minimise the influence of these errors during equipment set-up and data processing. A case study application of DIC for multipoint displacement measurement of a masonry viaduct in Leeds is then described, where potential errors due to lighting changes, image texture, and camera movements are minimised with an appropriate set-up. Pixel-metric scaling errors are kept to a minimum with the use of a calibration method, which utilises vanishing points in the image. However, comparisons of DIC relative displacement measurements to complementary strain measurements from the bridge demonstrate that other errors may have significant influence on the DIC measurement accuracy. Therefore, the influence of measurement errors due to lens radial distortion and out-of-plane movements is quantified theoretically with pinhole camera and division distortion models. A method to correct for errors due to potential out-of-plane movements is then proposed.

Experimental study on joint stiffness with vision-based system and geometric imperfections of temporary member structure

In this paper, tests of plug-pin joints are conducted in order to obtain their mechanical parameters, including semi-rigid property. To solve the difficulties of multi-point displacement measurements for small joints, this investigation proposes a vision-based measurement system based on the principle of binocular stereo vision to improve measurement accuracy. Accurate sub-pixel location is achieved according to a template-matching algorithm based on grayscale. Joint performance, including horizontal bar joint tension and compression, semi-rigidity between horizontal bars and upright rods and bracing tension and compression, is investigated in order to acquire joint failure modes as well as load and displacement (or moment and rotation angle) curves. Through data fitting, multi-linear simplified models are proposed to illustrate the joints’ mechanical performance. This paper also investigates geometric imperfection of temporary member structure with plug-pin joints based on several substructure models and temporary grandstand units using a total station theodolite. The probabilistic models of initial member out-of-straightness and story frame out-of-plumb have been acquired, which can be used into Monte Carlo simulation to create stochastic model of the temporary member structure.

Vision-based multipoint displacement measurement for structural health monitoring

Summary A novel noncontact vision sensor for simultaneous measurement of structural displacements at multiple points using one camera is developed based on two advanced template matching techniques: the upsampled cross correlation (UCC) and the orientation code matching (OCM). While existing studies on vision sensors are mostly focused on the time-domain performance evaluation, this study investigates the performance in both time and frequency domains through a shaking table test of a three-story frame structure, in which the displacements at all the floors are measured by using one camera to track either high-contrast artificial targets or low-contrast natural targets on the structural surface such as bolts and nuts. Excellent agreements are observed between the displacements measured by the single camera and those measured by high-performance laser displacement sensors. The results of structural modal analysis based on the measurements by the vision sensor and reference accelerometers also agree well. Moreover, the identified modal parameters are used to update the finite element model of the structure, demonstrating the potential of the vision sensor for structural health monitoring applications. This study further examines the robustness of the proposed vision sensor against ill environmental conditions such as dim light, background image disturbance, and partial template occlusion, which is important for future implementation in the field. Significant advantages of the proposed vision sensor include its low cost (a single camera to remotely measure structural displacements at multiple points without installing artificial targets) and flexibility to extract structural displacements at any point from a single measurement. Copyright © 2015 John Wiley & Sons, Ltd.

１周波ＧＰＳ受信機と無線ＬＡＮを用いた多点変位計測システムの開発

The objective of this research is to develop the multipoint displacement measurement system for infrastructures. This paper describes the developed prototype of this system and shows the results of the field experiments. This system consists of a GPS server and sensor nodes. A low cost Ll GPS receiver and a wireless LAN device are equipped on the sensor nodes. A GPS server is able to gather the GPS data received at sensor nodes and to estimate their accurate positions by analyzing the Ll carrier phases. Field experiments were conducted with three sensor nodes. The results show that the positions of the sensor nodes are monitored by the accuracy of a few centimeters. The integer ambiguities, that are needed to estimate the accurate position, are correctly determined in 10 minutes in the experiment.