Next Article in Journal
Study of the Integration of the CNU-TS-1 Mobile Tunnel Monitoring System
Next Article in Special Issue
Plane Wave SH0 Piezoceramic Transduction Optimized Using Geometrical Parameters
Previous Article in Journal
Sensitive and Flexible Polymeric Strain Sensor for Accurate Human Motion Monitoring
Previous Article in Special Issue
Integration of High-Resolution Laser Displacement Sensors and 3D Printing for Structural Health Monitoring
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(2), 419; https://doi.org/10.3390/s18020419

Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition

Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
*
Authors to whom correspondence should be addressed.
Received: 31 October 2017 / Revised: 26 January 2018 / Accepted: 29 January 2018 / Published: 1 February 2018
(This article belongs to the Special Issue Sensor Technologies for Health Monitoring of Composite Structures)
View Full-Text   |   Download PDF [1835 KB, uploaded 1 February 2018]   |  

Abstract

The stress in structural steel members is the most useful and directly measurable physical quantity to evaluate the structural safety in structural health monitoring, which is also an important index to evaluate the stress distribution and force condition of structures during structural construction and service phases. Thus, it is common to set stress as a measure in steel structural monitoring. Considering the economy and the importance of the structural members, there are only a limited number of sensors that can be placed, which means that it is impossible to obtain the stresses of all members directly using sensors. This study aims to develop a stress response prediction method for locations where there are insufficent sensors, using measurements from a limited number of sensors and pattern recognition. The detailed improved aspects are: (1) a distributed computing process is proposed, where the same pattern is recognized by several subsets of measurements; and (2) the pattern recognition using the subset of measurements is carried out by considering the optimal number of sensors and number of fusion patterns. The validity and feasibility of the proposed method are verified using two examples: the finite-element simulation of a single-layer shell-like steel structure, and the structural health monitoring of the space steel roof of Shenzhen Bay Stadium; for the latter, the anti-noise performance of this method is verified by the stress measurements from a real-world project. View Full-Text
Keywords: structural health monitoring; stress capturing; pattern recognition; stress prediction; Shenzhen Bay Stadium structural health monitoring; stress capturing; pattern recognition; stress prediction; Shenzhen Bay Stadium
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Lu, W.; Teng, J.; Zhou, Q.; Peng, Q. Stress Prediction for Distributed Structural Health Monitoring Using Existing Measurements and Pattern Recognition. Sensors 2018, 18, 419.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top