Vision-based Displacement Measurement Research Articles

Measurement of Three-Dimensional Structural Displacement Using a Hybrid Inertial Vision-Based System

Accurate three-dimensional displacement measurements of bridges and other structures have received significant attention in recent years. The main challenges of such measurements include the cost and the need for a scalable array of instrumentation. This paper presents a novel Hybrid Inertial Vision-Based Displacement Measurement (HIVBDM) system that can measure three-dimensional structural displacements by using a monocular charge-coupled device (CCD) camera, a stationary calibration target, and an attached tilt sensor. The HIVBDM system does not require the camera to be stationary during the measurements, while the camera movements, i.e., rotations and translations, during the measurement process are compensated by using a stationary calibration target in the field of view (FOV) of the camera. An attached tilt sensor is further used to refine the camera movement compensation, and better infers the global three-dimensional structural displacements. This HIVBDM system is evaluated on both short-term and long-term synthetic static structural displacements, which are conducted in an indoor simulated experimental environment. In the experiments, at a 9.75 m operating distance between the monitoring camera and the structure that is being monitored, the proposed HIVBDM system achieves an average of 1.440 mm Root Mean Square Error (RMSE) on the in-plane structural translations and an average of 2.904 mm RMSE on the out-of-plane structural translations.

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.

A Robust Vision-Based Method for Displacement Measurement under Adverse Environmental Factors Using Spatio-Temporal Context Learning and Taylor Approximation.

Currently, the majority of studies on vision-based measurement have been conducted under ideal environments so that an adequate measurement performance and accuracy is ensured. However, vision-based systems may face some adverse influencing factors such as illumination change and fog interference, which can affect measurement accuracy. This paper developed a robust vision-based displacement measurement method which can handle the two common and important adverse factors given above and achieve sensitivity at the subpixel level. The proposed method leverages the advantage of high-resolution imaging incorporating spatial and temporal contextual aspects. To validate the feasibility, stability, and robustness of the proposed method, a series of experiments was conducted on a two-span three-lane bridge in the laboratory. The illumination changes and fog interference were simulated experimentally in the laboratory. The results of the proposed method were compared to conventional displacement sensor data and current vision-based method results. It was demonstrated that the proposed method gave better measurement results than the current ones under illumination change and fog interference.

A non-target structural displacement measurement method using advanced feature matching strategy

Most of the existing vision-based displacement measurement methods require manual speckles or targets to improve the measurement performance in non-stationary imagery environments. To minimize the use of manual speckles and targets, feature points regarded as virtual markers can be utilized for non-target measurement. In this study, an advanced feature matching strategy is presented, which replaces the handcrafted descriptors with learned descriptors called Visual Geometry Group, of the University of Oxford descriptors to achieve better performance. The feasibility and performance of the proposed method is verified by comparative studies with a laboratory experiment on a two-span bridge model and then with a field application on a railway bridge. The proposed approach of integrated use of Scale Invariant Feature Transform and Visual Geometry Group improved the measurement accuracy by about 24% when compared with the commonly used existing feature matching-based displacement measurement method using Scale Invariant Feature Transform feature and descriptor.

Reliability verification of a vision-based dynamic displacement measurement for system identification

In this paper, dynamic experiments of various amplitudes with a broad band of frequencies were carried out using a shaking table in order to validate the wide-range reliability of a vision-based displacement measurement system. In addition, the dynamic characteristics of a multiple-degree-of-freedom model structures were estimated using the vision-based measurement method. As a result of error analysis through comparison with a laser displacement sensor (LDS), it was determined that the accuracy of dynamic displacement measurement by the camcorder in the vision-based system is affected by the frequency of the measurement object. From these results, it is judged that the CMOS sensor type has the rolling shutter effect when the velocity between the model structure and the camcorder is high. The accuracy of dynamic characteristics estimation was determined by comparing the dynamic characteristics estimated using the LDSs and the accelerometers. The vision-based measurement system using the camcorder in both time domain and frequency domains showed very similar results to the existing LDS and accelerometer measurements.

Comparative study on displacement measurement sensors for high-speed railroad bridge

This paper presents a comparative study of displacement measurement using four sensors that are being used in the field: they are a ring gauge, a laser Doppler vibrometer (LDV), a vision-based displacement measurement system (VDMS), and an optoelectronic displacement meter (ODM). The comparative study was carried out on a brand-new high-speed railroad bridge designed to produce displacements within a couple of millimeters under the loading of a high-speed train. The tests were carried out on a single-span steel plate girder bridge two times with different train loadings: KTX and HEMU. The measured displacement is compared as raw and further discussion was made on the measurement noise, peak displacement, and frequency response of four sensors. The comparisonsare summarized to show the pros and cons of the used sensors in measuring displacement at a typical high-speed railroad bridge.

Review of machine-vision based methodologies for displacement measurement in civil structures

Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional displacement sensors in instrumentation cost, installation efforts and measurement capacity in terms of frequency range and spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like system development and improvement, the viability on field applications and the potential for structural condition assessment. The main contribution of this paper is to present a literature review of vision-based displacement measurement, from the perspectives of methodologies and applications. Video-processing procedures in this paper are summarised as a three-component framework: camera calibration, target tracking and structural displacement calculation. Methods for each component are presented in principle, with discussions about the relative advantages and limitations. Applications in the two most active fields, bridge deformation and cable vibration measurement, are examined followed by a summary of field challenges observed in monitoring tests. Important gaps requiring further investigation are presented, e.g. robust tracking methods, non-contact sensing and measurement accuracy evaluation in field conditions.

Visual-inertial displacement sensing using data fusion of vision-based displacement with acceleration

In recognition of the importance of the displacement associated with assessing structural condition, many displacement measurement methods have been proposed to date. With advances in optics and electronics, displacement measurement relying on computer-vision techniques to convert pixel movement into structural displacement has drawn much attention recently, thanks to its simplicity in installation and relatively inexpensive cost. Despite numerous advantages, 2 major obstacles that prohibit the use of vision-based method are (a) resolution, which is a function of distance between the camera and the structure, and (b) limited frame rate, which both lower dynamic displacement-capturing capability. In this paper, to enhance the quality of vision-based displacement measurement, data fusion with acceleration measurement is proposed to improve the dynamic range of displacements while lowering signal noise. To achieve fusion between vision-based displacement and acceleration, complementary filters and a time synchronization method between 2 different sources were proposed. The proposed methods were verified through numerical analysis and an experimental test, the results of which showed the validity of proposed data fusion.

Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges

The displacement responses of a civil engineering structure can provide important information regarding structural behaviors that help in assessing safety and serviceability. A displacement measurement using conventional devices, such as the linear variable differential transformer (LVDT), is challenging owing to issues related to inconvenient sensor installation that often requires additional temporary structures. A promising alternative is offered by computer vision, which typically provides a low-cost and non-contact displacement measurement that converts the movement of an object, mostly an attached marker, in the captured images into structural displacement. However, there is limited research on addressing light-induced measurement error caused by the inevitable sunlight in field-testing conditions. This study presents a computer vision-based displacement measurement approach tailored to a field-testing environment with enhanced robustness to strong sunlight. An image-processing algorithm with an adaptive region-of-interest (ROI) is proposed to reliably determine a marker’s location even when the marker is indistinct due to unfavorable light. The performance of the proposed system is experimentally validated in both laboratory-scale and field experiments.

Computer Vision-based Displacement Measurement Method With Arbitrarily Positioned Camera

Displacement is broadly used in structural health monitoring as a meaningful indicator of structural status. Measuring structural displacement using conventional devices such as the linear variable differential transformer is challenging due to practical issues such as equipment inaccessibility, insufficient measurement accuracy, or expensive system cost. Recently, computer vision-based displacement measurement methods have been developed to build high field applicable measurement system. However, the existing computer vision-based displacement measurementtechniques still have practical issues such as absence of camera installation point, marker attachment, or lightinduced error. This paper presents a computer vision-based displacement measurement system focusing on solving camera positioning issue. The proposed method adopts homography transform to allow cameras to be positioned at arbitrary point. A laboratory scale experiment was conducted to verify accurate displacement measurement of the proposed method with the arbitrarily positioned camera.

Identification of structural stiffness and excitation forces in time domain using noncontact vision-based displacement measurement

The emerging noncontact vision-based displacement sensor system offers a promising alternative to the conventional sensors for quantitative structural integrity assessment. Significant advantages of the noncontact vision-based sensor include its low cost, ease of operation, and flexibility to extract structural displacement responses at multiple points. This study aims to link the measured displacement data to the quantification of the structural health condition, by validating the feasibility of simultaneous identification of structural stiffness and unknown excitation forces in time domain using output-only vision-based displacement measurement. Numerical analysis are first carried out to investigate the accuracy, convergence and robustness of identified results to different noise levels, sensor numbers, and initial estimates of structural parameters. Then, experiment on a laboratory scaled beam structure is conducted. Results show that the global stiffness of the beam specimen as well as external hammer excitation forces can be successfully and accurately identified from displacement measurement at two points using one camera. The proposed output-only time-domain identification procedure utilizing vision-based displacement measurement represents a low-cost method for either periodic or long-term bridge performance assessment.

Vision-based displacement measurement sensor using modified Taylor approximation approach

The development of image sensors and optics lenses has contributed to the rapidly increasing use of vision-based methods as noncontact measurement methods in many areas. A high-speed camera system is developed to realize the displacement measurement in real time. Conventional visual measurement algorithms are commonly subjected to various shortcomings, such as complex processes, multiparameter adjustments, or integer-pixel accuracy. Inspired from the combination of block-matching algorithm and simplified optical flow, a motion estimation algorithm that uses modified Taylor approximation is proposed and applied to the vision sensor system. Simplifying integer-pixel searching with a rounding-iterative operation enables the modified algorithm to rapidly accomplish one displacement extraction within 1 ms and yield satisfactory subpixel accuracy. The performance of the vision sensor is evaluated through a simulation test and two experiments on a grating ruler motion platform and a steering wheel system of a forklift. Experimental results show that the developed vision sensor can extract accurate displacement signals and accomplish the vibration measurement of engineering structures.

사장교 케이블의 장력 추정을 위한 영상변위 측정법의 효율적 적용에 대한 연구

본 논문에서는 사장교 케이블의 장력 추정을 위한 영상변위 측정법의 간편성과 효율성을 보이고 효과적인 적용에 필요한 요구조건에 대해 연구하였다. 간편성과 효율성을 보이기 위해 상용 캠코드를 이용한 최소한의 장비만으로도 필요한 영상변위 측정이 가능함을 증명하였다. 이 경우 최소 장비 구성과 고속촬영에 따른 해상도 저하에 의한 크기오차가 발생할 수 있으나 진동법에 필요한 고유진동수 추정의 정확도 확보는 충분히 가능함을 알 수 있었다. 또한 진동법을 이용한 장력 추정에서 정확한 고유진동수의 검출을 위해서는 적절한 주파수 범위의 확보가 가장 중요함을 확인하였다. 이 결과를 바탕으로, 상용캠 사용 조건하에서 촬영프레임속도에 따른 장력 추정의 정확도 변동에 대한 연구를 수행하였다. 이를 위해 모형사장교의 케이블에 대한 장력 추정 실험을 수행하였다. 모형실험을 통해 다양한 고유진동수를 가지는 케이블에 대해 촬영프레임 속도에 따라 검출 가능한 장력을 정리하였다. 그 결과 에일리어싱 효과와 가진력의 저주파수 왜곡효과를 고려하여 추정될 고유진동수가 적절한 주파수 범위(대략 이론적 범위의 10~75%) 내에 위치하도록 프레임 속도를 결정되어야 함을 보였다. In this study, the convenience and efficiency of vision-based displacement measurement (VBDM) to estimate the cable tension of cable-stayed bridges and the requirements for its effective application were examined. To demonstrate its convenience and efficiency, it was confirmed that VBDM can be accomplished with a minimum amount of equipment using a commercial camcorder. In this case, it was found that the accuracy of estimation of the natural frequencies is sufficient, even though magnitude errors can occur when conducting high-speed recording at the low resolution afforded by the minimal equipment employed. It was also confirmed that the most important factor in detecting the precise natural frequencies is the use of the appropriate frequency range in the tension estimation using vibration. Based on these results, a study was carried out on the accuracy variation of the estimated tension according to the frame rate of a commercial camcorder. For this purpose, an experiment was performed to estimate the cable tension in a cable-stayed bridge model. Through this experiment, the detectable tensions of cables with various natural frequencies as a function of the frame rate were summarized. As a result, it was shown that the frame rate should be determined based on the natural frequency which is estimated to be located within the appropriate frequency range (approximately 10~75% of theoretical range) considering the aliasing and low-frequency distortion due to excitations.

Measurement of Dynamic Characteristics on Structure using Non-marker Vision-based Displacement Measurement System

Measurement of Dynamic Characteristics on Structure using Non-marker Vision-based Displacement Measurement System

Completely contactless structural health monitoring of real-life structures using cameras and computer vision

Summary A newly developed, completely contactless structural health monitoring system framework based on the use of regular cameras and computer vision techniques is introduced for obtaining displacements and vibrations of structures, which are critical responses for performance-based design and evaluation of structures. To provide contactless and practical monitoring, the current vision-based displacement measurement methods are improved by eliminating the physical target attachment. This is achieved by means of utilizing imaging key-points as virtual targets. As a result, pixel-based displacements of a monitored structural location are determined by using an improved detection and match key-points algorithm, in which false matches are identified and discarded almost completely. To transform pixel-based displacements to engineering units, a practical camera calibration method is developed because calibration standard on a physical target no longer exists. Moreover, a framework for evaluating the accuracy of vision-based displacement measurements is established for the first time, which, in return, provides users with the most crucial information of a measurement. The proposed framework along with a conventional sensor network and a data acquisition system are applied and verified on a real-life stadium during football games for structural assessment. The results obtained by the new method are successfully validated with the data acquired from sensors such as linear variable differential transformers and accelerometers. Because the proposed method does not require any type of sensor and target attachment, common field works such as sensor installation, wiring, maintaining conventional data acquisition systems are not required. This advantage enables an inexpensive and practical way for structural assessment, especially for real-life structures. Copyright © 2016 John Wiley & Sons, Ltd.

Vision-based structural displacement measurement: System performance evaluation and influence factor analysis

In the past decade, the emerging machine vision-based measurement technology has gained great concerns among civil engineers due to its overwhelming merits of non-contact, long-distance, and high-resolution. A critical issue regarding to the measurement performance and accuracy of the vision-based system is how to identify and eliminate the systematic and unsystematic error sources. In this paper, a vision-based structural displacement measurement system integrated with a digital image processing approach is developed. The performance of the developed vision-based system is evaluated by comparing the results simultaneously obtained by the vision-based system and those measured by the magnetostrictive displacement sensor (MDS). A series of experiments are conducted on a shaking table to examine the influence factors which will affect the accuracy and stability of the vision-based system. It is demonstrated that illumination and vapor have a critical effect on the measurement results of the vision-based system.

Rotational Angle Measurement of Bridge Support Using Image Processing Techniques

Measuring a very small rotational angle accurately and dynamically is indeed a challenging issue, especially in the case of bridge support. Also, existing inclinometers do not have sufficient resolution and accuracy to measure a bridge’s rotational angle. In this study, a new measurement system was developed to provide a practical means for measuring dynamic rotational angle of a bridge support. It features high resolution and accuracy compared with the available systems on the market. By the combinational use of a laser pointer and a vision-based displacement measurement system, the measurement accuracy was significantly increased. The accuracy and applicability were investigated through laboratory tests. From the laboratory tests, it has been found that the developed system can be applicable to bridge support with very small rotational angle. The effectiveness of the developed system was verified through field tests on real bridges. From the full-scale implementation on two PSC girder bridges, it is observed that the proposed system can measure the rotational angle with a high accuracy and reliability.

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.

"임의의 위치에서 사용가능한 영상 기반 변위 계측 시스템"의 정오표

"임의의 위치에서 사용가능한 영상 기반 변위 계측 시스템"의 정오표

임의의 위치에서 사용 가능한 영상 기반 변위 계측 시스템

In this study, a vision-based displacement measurement system is developed to accurately measure the displacement of a structure with locating the camera at arbitrary position. The previous vision-based system brings error when the optical axis of a camera has an angle with the measured structure, which limits the applicability at large structures. The developed system measures displacement by processing the images of a target plate that is attached on the measured position of a structure. To measure displacement regardless of the angle between the optical axis of the camera and the target plate, planar homography is employed to match two planes in image and world coordinate systems. To validate the performance of the present system, a laboratory test is carried out using a small 2-story shear building model. The result shows that the present system measures accurate displacement of the structure even with a camera significantly angled with the target plate.