Strain measurement based on cooperative operation with different smartphones

Xie, Botao; Zhang, Lixiao; Ding, Mingwei; Li, Weijie; Zhao, Xuefeng

doi:10.1111/mice.12919

Cited by 12 publications

(8 citation statements)

References 48 publications

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“…The length of the MISS sensor was 300 mm, and its left tube was about 105 mm long. More details of the MISS sensor were previously described [ 26 , 28 ]. The smartphone was a Honor 7X with 8 megapixels, and the microscope was a TIPSCOPE with thickness of 0.3 mm.…”

Section: Experiments Setupmentioning

confidence: 99%

“…This is a cheap, convenient and universally applicable strain measuring method. Our previous research concluded that the maximum measurement range of this technique is ±8300 microstrains [ 24 , 25 , 26 ]. A study [ 24 ] proposed the SURF method as a strain measurement method to trace the displacement of feature points in micro-images and obtain the strain in objects.…”

Section: Introductionmentioning

confidence: 99%

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Micro-Image Strain Sensing Method for Displacement and Strain Measurement in One United Sensor

Zhang

Chen

et al. 2022

Sensors

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Micro-image strain sensing (MISS) is an innovative technology to measure strain within a measurement range of ±8300 microstrains. It has been proved to be effective and satisfy all requirements in the field of structural health monitoring. However, there is still room for improvement and extend the range of measurement. In this paper, an improved method is proposed to increase the measurement range of strain and displacement. Moreover, various tests were conducted to verify the efficiency of the improved method. The results showed that the modified method is efficient and accurate and can be readily used to extend the measurement range of both strain and displacement. This research will likely help stimulate the development of multifunctional sensors to obtain abundant useful information about structures in the field of structural health monitoring. It will allow measuring strain and displacement, which require different levels of accuracy, using one unified sensor.

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Section: Experiments Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Micro-Image Strain Sensing Method for Displacement and Strain Measurement in One United Sensor

Zhang

Chen

et al. 2022

Sensors

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“…Xie et al. (2023) proposed a micro image strain‐sensing method using smartphones, but it was not fully automated and did not show potential for application in component dimension measurement. Zhuge et al.…”

Section: Introductionmentioning

confidence: 99%

“…M. Wang et al (2023) proposed a subpixel refinement technique to improve the accuracy of image-based structural displacement measurement, but its practical application in the measurements of structural displacements or construction component dimensions has not been demonstrated. Xie et al (2023) proposed a micro image strain-sensing method using smartphones, but it was not fully automated and did not show potential for application in component dimension measurement. Zhuge et al (2022) proposed a method for the non-contact measurement of bridge deflection using cameras and lasers mounted on unmanned aerial vehicles; however, this technology specialized in time-history displacement measurements at specific points and had limitations when applied to automated component dimension measurement.…”

Section: Introductionmentioning

confidence: 99%

Automated reconstruction model of a cross‐sectional drawing from stereo photographs based on deep learning

Park

2023

Computer aided Civil Eng

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This study presents a novel, deep‐learning‐based model for the automated reconstruction of a cross‐sectional drawing from stereo photographs. Targeted cross‐sections captured in stereo photographs are detected and translated into sectional drawings using faster region‐based convolutional neural networks and Pix2Pix generative adversarial network. To address the challenge of perspective correction in the photographs, a novel camera pose optimization method is introduced and employed. This method eliminates the need for camera calibration and image matching, thereby offering greater flexibility in camera positioning and facilitating the use of telephoto lenses while avoiding image‐matching errors. Moreover, synthetic image datasets are used for training to facilitate the practical implementation of the proposed model in construction industry applications, considering the limited availability of open datasets in this field. The applicability of the proposed model was evaluated through experiments conducted on the cross‐sections of curtain wall components. The results demonstrated superior measurement accuracy, compared with those of current methods of laser scanning or camera‐based measurements for construction components.

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“…On the basis of our previous research, a micrograph strain sensing method based on machine vision algorithms has been introduced for strain measurements using cellular phones. Sleeve-type strain sensors have been designed [48][49][50][51], and the possibility of replacing a cell phone with a digital microscope for long-term monitoring has been explored [52], and these studies have been subjected to preliminary laboratory validation. The system demonstrated the advantages of machine vision-based strain measurement due to its low cost, ease of measurement operation, and high accuracy.…”

Section: Introductionmentioning

confidence: 99%

Design and Verification of a Novel Structural Strain Measuring Method Based on Template Matching and Microscopic Vision

Zhao,

Bai,

Liang

et al. 2023

Buildings

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Strain measurements have a significant role in evaluating the condition of various structural types and have become an essential component in the area of structural health monitoring. However, there are some limitations in the current means of strain measurement, and this study aims to improve these methods. We have designed a novel strain measurement method based on template matching algorithms and microscopic vision techniques, developed a new sliding strain sensor, and paired it with a new microscope to realize strain measurement. The method has the function of remote wireless acquisition with a cell phone, which is more widely applicable. In the laboratory performance testing, the zero drift of the sensor is mainly concentrated in the fluctuation range of ±2 με, and the effective range reaches nearly 40,000 με. In the comparison experiments with the linear variable differential transformer, the maximum error of the static loading is only 5 με, and the maximum error rate of the dynamic loading is less than 1%, which proves that it has a relatively high accuracy. Finally, the short-term real-time monitoring of the local structure of the footbridge was accomplished, and the strain changes on the surface of the structure were captured instantly, stably, and efficiently in the actual measurements. The proposed strain measurement system has the advantages of high accuracy, a low cost, convenient measurement, and wide applicability, and it provides a novel alternative means for strain measurement in the field of structural health monitoring.

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Strain measurement based on cooperative operation with different smartphones

Cited by 12 publications

References 48 publications

Micro-Image Strain Sensing Method for Displacement and Strain Measurement in One United Sensor

Micro-Image Strain Sensing Method for Displacement and Strain Measurement in One United Sensor

Automated reconstruction model of a cross‐sectional drawing from stereo photographs based on deep learning

Design and Verification of a Novel Structural Strain Measuring Method Based on Template Matching and Microscopic Vision

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