Proceedings of the 2015 International Conference on Test, Measurement and Computational Methods

Research on Tower Crane Structure Damage Detection Based on ARX Model

Authors
Shengchun Wang, Ye Zhang, Peiwei Ni, Yan Tian
Corresponding Author
Shengchun Wang
Available Online November 2015.
DOI
https://doi.org/10.2991/tmcm-15.2015.23How to use a DOI?
Keywords
tower crane; statistical recognition technology; ARX model; the damage characteristic parameter
Abstract
In view of the health inspection of tower crane, the paper puts forward an ARX model to detect the status of the tower crane structure which uses the node displacements of tower crane below standard section as input and the up standard section of the node displacements as the output. Combining with statistical recognition technology the states detection of the structure are detected. First, the paper establishes a counterpart finite element model based on the laboratory existing mini tower cranes to obtain the displacement signals of tower crane nodes in intact and damaged states with excitation load. Then it chooses a better identified ARX model to define the damage characteristic parameter. Finally it judges the dynamic response of the good state as a reference to analyze the differences between the response signals of damage status and normal structures, so as to complete the diagnose with the method of statistical analysis. The method shows a high ability of damage identification.
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Proceedings
2015 International Conference on Test, Measurement and Computational Methods
Part of series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-132-2
ISSN
2352-538X
DOI
https://doi.org/10.2991/tmcm-15.2015.23How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shengchun Wang
AU  - Ye Zhang
AU  - Peiwei Ni
AU  - Yan Tian
PY  - 2015/11
DA  - 2015/11
TI  - Research on Tower Crane Structure Damage Detection Based on ARX Model
BT  - 2015 International Conference on Test, Measurement and Computational Methods
PB  - Atlantis Press
SP  - 91
EP  - 95
SN  - 2352-538X
UR  - https://doi.org/10.2991/tmcm-15.2015.23
DO  - https://doi.org/10.2991/tmcm-15.2015.23
ID  - Wang2015/11
ER  -