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

Joint Authors

Ye, Xiao-Wei
Dong, C. Z.
Liu, T.

Source

Journal of Sensors

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-11-06

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Ye, Xiao-Wei& Dong, C. Z.& Liu, T.. 2016. A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications. Journal of Sensors،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1110582

Modern Language Association (MLA)

Ye, Xiao-Wei…[et al.]. A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications. Journal of Sensors No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1110582

American Medical Association (AMA)

Ye, Xiao-Wei& Dong, C. Z.& Liu, T.. A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1110582

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1110582