Temperature effects on vision measurement system in long-term continuous monitoring of displacement

Zhou, H. F.; Zheng, Jianhong; Xie, Zhihong; Lu, Lin Jun; Ni, YQ; Ko, J. M.

doi:10.1016/j.renene.2017.07.104

Cited by 15 publications

(19 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results showed only 1% variation in camera‐based measurement with respect to accelerometers. Zhou et al aimed at understanding the use of videogrammetry under temperature variations on vision measurement systems. The study found a temperature variation in axial displacement in different directions.…”

Section: Next‐generation Sensing Methodsmentioning

confidence: 99%

A literature review of next-generation smart sensing technology in structural health monitoring

Sony

Laventure

Sadhu

2019

Struct Control Health Monit

422

183

View full text Add to dashboard Cite

Summary Advent of computationally efficient smartphones, inexpensive high‐resolution cameras, drones, and robotic sensors has brought a new era of next‐generation intelligent monitoring systems for civil infrastructure. Vibration‐based condition assessment has garnered as a prominent method of evaluating the health of large‐scale infrastructure. The use of contact‐based sensors for acquiring vibration data becomes uneconomical and tedious due to their instrumentation cost, centralized nature, and densification required to collect sufficient data for system identification of modern complex structures. A need to advance and develop alternative methods for efficient sensing system results in next‐generation measurement technology of structural health monitoring. The abundance of handheld smartphones with easily programmable framework has helped in modifying relevant software to acquire vibration data using embedded sensors in the smartphone. The inexpensive cameras have been used to capture images and videos that are utilized to understand the structural behavior with the aid of advanced signal processing techniques. The inaccessible components of structures require noncontact sensors such as unmanned aerial vehicles (UAVs) or so‐called drones and mobile sensors to acquire structural data. To the authors' knowledge, this paper first time presents a comprehensive review of a suite of next‐generation smart sensing technology that has been developed in recent years within the context of structural health monitoring. The state‐of‐the‐art methods have been presented by conducting a detailed literature review of the recent applications of smartphones, UAVs, cameras, and robotic sensors used in acquiring and analyzing the vibration data for structural condition monitoring and maintenance.

show abstract

Section: Next‐generation Sensing Methodsmentioning

confidence: 99%

A literature review of next-generation smart sensing technology in structural health monitoring

Sony

Laventure

Sadhu

2019

Struct Control Health Monit

422

183

View full text Add to dashboard Cite

show abstract

“…[ 32 ] In recent work, quantification of the induced error based on mathematical model is demonstrated in a vision‐based measurement test of a long‐span bridge, [ 33 ] and the temperature effects on vision measurement system in long‐term monitoring of displacement were reported. [ 34 ]…”

Section: Discussionmentioning

confidence: 99%

“…[32] In recent work, quantification of the induced error based on mathematical model is demonstrated in a vision-based measurement test of a long-span bridge, [33] and the temperature effects on vision measurement system in long-term monitoring of displacement were reported. [34] To investigate the measurement error by the atmospheric disturbance in this study, we analysed the displacement before the train passage during 5 s (50 data). In this case, both the displacement in the x and y directions should be 0.…”

Section: Error By Atmospheric Disturbancementioning

confidence: 99%

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

Wang

Tsuda

et al. 2020

Strain

View full text Add to dashboard Cite

Measuring 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.

show abstract

“…12, and the volume of equipment is smaller than LVDT equipment. As indicated in previous research, the temperature is the dominant factor of the variation of the slab displacement [24]. Therefore, we investigate the displacement monitoring data of both systems under different temperature conditions.…”

Section: In-situ Instrumentation and Performance Validationmentioning

confidence: 90%

Long-Term Monitoring for Track Slab in High-Speed Rail via Vision Sensing

Liu

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Track slab deformation has become a challenging issue in high-speed rail (HSR) operation in recent years. This paper proposed a novel approach for track slab deformation monitoring based on computer vision techniques. The basic principle of visual measurement of track slab displacement is first introduced. Then the detailed process of slab displacement calculation from the on-site images is presented, including region of interest (ROI) extraction, determination of the target edge, and displacement calculation. In this process, considering the actual operation environment of in-service HSR lines, an improved Canny algorithm, which can adaptively extract the location information of the target is proposed and employed in the image processing. Based on the modular design method, an online monitoring system for the displacement of the track slab is established. The devised system is installed on an in-service HSR line for long-term slab deformation monitoring. The performance of the proposed system is verified by one-year monitoring data of slab displacement. The measurement results of the proposed system are compared with an existing linear variable differential transformer (LVDT) system, demonstrating that it can accurately report track displacement with lower cost and easier instrumentation. This research is expected to provide insights to the railway maintenance-of-way department for better management and maintenance of slab deformation, especially under high temperature. INDEX TERMS Computer vision; High-speed rail (HSR) slab track; Improved Canny algorithm; Online monitoring.

show abstract

Temperature effects on vision measurement system in long-term continuous monitoring of displacement

Cited by 15 publications

References 27 publications

A literature review of next-generation smart sensing technology in structural health monitoring

A literature review of next-generation smart sensing technology in structural health monitoring

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

Long-Term Monitoring for Track Slab in High-Speed Rail via Vision Sensing

Contact Info

Product

Resources

About