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

Ye, X.W.; Yi, Ting‐Hua; Dong, Chuan‐Zhi; Liu, T.

doi:10.1016/j.measurement.2016.01.024

Cited by 114 publications

(48 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the DIC technique, the essential importance in preparing the specimens is the uniqueness of the speckle pattern, especially the pattern within the subset [23][24][25][26][27]. A commercial software VIC-2D by Correlated Solution is adopted to do the correlation analysis [28].…”

Section: Test Set-upmentioning

confidence: 99%

Crack Propagation and Fracture Process Zone (FPZ) of Wood in the Longitudinal Direction Determined Using Digital Image Correlation (DIC) Technique

Zeng

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

As a state-of-the-art method, the digital image correlation (DIC) technique is used to capture the fracture properties of wood along the longitudinal direction, such as the crack propagation, the strain field, and the fracture process zone (FPZ). Single-edge notched (SEN) specimens made of Douglas fir (Pseudotsuga menziesii) from Canada with different notch-to-depth ratios are tested by three-point-bending (3-p-b) experiment. The crack mouth opening displacements (CMOD) measured by the clip gauge and DIC technique agree well with each other, verifying the applicability of the DIC technique. Then, the quasi-brittle fracture process of wood is analyzed by combing the load-CMOD curve and the strain field in front of the preformed crack. Additionally, the equivalent elastic crack length is calculated using the linear superposition hypothesis. The comparison between the FPZ evolution and the equivalent elastic crack shows that specimens with higher notch-to-depth ratios have better cohesive effect and higher cracking resistance.

show abstract

Section: Test Set-upmentioning

confidence: 99%

Crack Propagation and Fracture Process Zone (FPZ) of Wood in the Longitudinal Direction Determined Using Digital Image Correlation (DIC) Technique

Zeng

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Figure 1, the images including the predefined targets are captured by the digital camera. With the digital image processing and pattern matching algorithm [27][28][29][30], the targets are tracked and the structural displacements at the target positions on the structure can be obtained. In this occasion, the horizontal and vertical displacements, called two-dimensional (2D) displacements, can be obtained with one digital camera by use of the appropriate image processing method, such as digital image correlation [31], mean-shift tracking algorithm [32], CamShift tracking algorithm [33], and Lucas-Kanade method [34].…”

Section: Machine Vision Methodsmentioning

confidence: 99%

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

2016

Self Cite

View full text Add to dashboard Cite

In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.

show abstract

“…15 In addition, most researchers have used a digital image correlation (DIC) algorithm to do vision-based structural displacement measurement along with the manual markers. 14,[16][17][18][19][20][21][22][23][24][25][26] DIC has many disadvantages because it is easily affected by changes in illumination, slight occlusions, blurring due to motion, target shape deformation, scale change, and rotation. These disadvantages are critical issues for field applications and thus have limited the popularization of vision-based monitoring methods.…”

Section: Introductionmentioning

confidence: 99%

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

Dong

Celik

Çatbaş

2018

Structural Health Monitoring

102

View full text Add to dashboard Cite

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.

show abstract

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

Cited by 114 publications

References 26 publications

Crack Propagation and Fracture Process Zone (FPZ) of Wood in the Longitudinal Direction Determined Using Digital Image Correlation (DIC) Technique

Crack Propagation and Fracture Process Zone (FPZ) of Wood in the Longitudinal Direction Determined Using Digital Image Correlation (DIC) Technique

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

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

Contact Info

Product

Resources

About