Restoration and structural health monitoring of Manitoba's Golden Boy

2003 ◽  
Vol 30 (6) ◽  
pp. 1123-1132 ◽  
Author(s):  
Aftab A Mufti
Keyword(s):  
Structural Health Monitoring ◽  
Knowledge Base ◽  
Health Monitoring ◽  
Civil Engineering ◽  
Paper Briefly ◽  
Engineering Applications ◽  
Engineering Structures ◽  
Structural Health ◽  
Existing Structures ◽  
History Of

Although bridges were among the first civil engineering structures to use structural health monitoring (SHM) technologies, research is now expanding to explore other types of applications, including Manitoba's famous Golden Boy statue. Global research is identifying the value of using SHM technologies for civil engineering applications. Structural health monitoring uses a variety of sensors to gather information about the behaviour of a structure. The information creates a valuable knowledge base that can be analyzed to help identify potential structural risks, develop safer and more efficient new structures, and determine more effective ways to rehabilitate existing structures. This paper briefly describes the history of the Manitoba Legislative Building and the Golden Boy and also the use of SHM technologies to help preserve the Golden Boy statue, an icon of provincial heritage.Key words: history, Golden Boy, statue, sculptors, architects, engineers, shaft, corrosion, sensors, monitoring.

scholarly journals Smart Sensing Technologies for Structural Health Monitoring of Civil Engineering Structures

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
M. Sun ◽  
W. J. Staszewski ◽  
R. N. Swamy
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Smart Materials ◽  
Civil Engineering ◽  
Piezoelectric Sensors ◽  
Sensors And Actuators ◽  
Engineering Structures ◽  
Structural Health ◽  
Civil Engineering Structures ◽  
Smart Sensing

Structural Health Monitoring (SHM) aims to develop automated systems for the continuous monitoring, inspection, and damage detection of structures with minimum labour involvement. The first step to set up a SHM system is to incorporate a level of structural sensing capability that is reliable and possesses long term stability. Smart sensing technologies including the applications of fibre optic sensors, piezoelectric sensors, magnetostrictive sensors and self-diagnosing fibre reinforced composites, possess very important capabilities of monitoring various physical or chemical parameters related to the health and therefore, durable service life of structures. In particular, piezoelectric sensors and magnetorestrictive sensors can serve as both sensors and actuators, which make SHM to be an active monitoring system. Thus, smart sensing technologies are now currently available, and can be utilized to the SHM of civil engineering structures. In this paper, the application of smart materials/sensors for the SHM of civil engineering structures is critically reviewed. The major focus is on the evaluations of laboratory and field studies of smart materials/sensors in civil engineering structures.

scholarly journals Parameter Identification for Structural Health Monitoring with Extended Kalman Filter Considering Integration and Noise Effect

2018 ◽  
Vol 8 (12) ◽  
pp. 2480 ◽  
Author(s):  
Liyu Xie ◽  
Zhenwei Zhou ◽  
Lei Zhao ◽  
Chunfeng Wan ◽  
Hesheng Tang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Structural Health Monitoring ◽  
Parameter Identification ◽  
Extended Kalman Filter ◽  
Health Monitoring ◽  
Civil Engineering ◽  
Damage Identification ◽  
Engineering Structures ◽  
Structural Health ◽  
Civil Engineering Structures

Since physical parameters are much more sensitive than modal parameters, structural parameter identification with an extended Kalman filter (EKF) has received extensive attention in structural health monitoring for civil engineering structures. In this paper, EKF-based parameter identification technique is studied with numerical and experimental approaches. A four-degree-of-freedom (4-DOF) system is simulated and analyzed as an example. Different integration methods are examined and their influence to the final identification results of the structural stiffness and damping is also studied. Furthermore, the effect of different kinds of noise is studied as well. Identification results show that the convergence speed and estimation accuracy under Gaussian noises are better than those under non-Gaussian noises. Finally, experiments with a five-story steel frame are conducted to verify the damage identification capacity of the EKF. The results show that stiffness with different damage degrees can be identified effectively, which indicates that the EKF is capable of being applied for damage identification and health monitoring for civil engineering structures.

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