A Variation Model Method for Real Time System Identification in Bridge Health Monitoring

2018 ◽  
Author(s):  
Ngoc Trung ◽  
Luu ◽  
Al‐Hakam Hamdan ◽  
Michael Polter ◽  
Tobias Mansperger
Keyword(s):  
System Identification ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Model ◽  
Real Time System ◽  
Structural Health ◽  
Multi Stage ◽  
Bridge Structures ◽  
Damage Data ◽  
Variation Model

The Structural Health Monitoring of bridge structures is becoming increasingly important. Due to new developments in the field of sensor and data processing technology, a new method will be introduced, which enables prognosis of the bridge lifespan through system identification based on the monitoring process. Therefore, the damages of the bridge, which are modelled in an appropriate damage model, will be linked with its BIM Model. The damage data will then be variated by using a separate Variation Model. Using this method results in the automatized creation of numerous input models for mass simulation. This forms the basis for a multi‐stage procedure, which identifies the structural bridge state by using the simulation results for a numerical best‐fit method. Thereby engineers can utilize the evaluated models to make more precise decisions and improve the Structural Health Monitoring of bridge structures.

Optimal Accelerometer Locations for Structural Health Monitoring Using Time-Domain System Identification

2006 ◽  
Vol 321-323 ◽  
pp. 273-277 ◽  
Author(s):  
Soon Jung Kwon ◽  
Hae Sung Lee ◽  
Soo Bong Shin
Keyword(s):  
System Identification ◽  
Structural Health Monitoring ◽  
Fisher Information ◽  
Health Monitoring ◽  
Time Domain ◽  
Fisher Information Matrix ◽  
Structural Parameters ◽  
Hessian Matrix ◽  
Information Matrix ◽  
Structural Health

The paper presents two algorithms for determining optimal accelerometer locations for structural health monitoring when structural condition is assessed by a system identification scheme in time-domain. The accelerometer locations are determined by ranking the components of an effective independent distribution vector computed from a Fisher information matrix. One of the proposed algorithms formulates a Fisher information matrix by multiplying acceleration matrix with its transpose and the other as a Gauss-Newton Hessian matrix composed of acceleration sensitivities with respect to structural parameters. Since the structural parameters cannot be known exactly in an actual application, a statistical approach is proposed by setting an error bound between the actual and the baseline values. To examine the algorithm, simulation studies have been carried out on a two-span planar truss. The results using locations selected by the two algorithms were compared.

Experimental System Identification of the Vibro-Impact Dynamics Towards Structural Health Monitoring and Damage Detection

2013 ◽  
Author(s):  
Heng Chen ◽  
Young S. Lee ◽  
Mehmet Kurt ◽  
D. Michael McFarland ◽  
Lawrence A. Bergman ◽  
...  
Keyword(s):  
System Identification ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Mode Shape ◽  
Health Monitoring ◽  
Correlation Spectroscopy ◽  
Impact Dynamics ◽  
Shape Functions ◽  
Modal Assurance Criterion ◽  
Structural Health

We perform nonlinear system identification (NSI) on the acceleration signals that were experimentally measured at ten, almost evenly spaced positions along a cantilever beam undergoing vibro-impacts between two rigid stops with clearances. The NSI methodology is based on the correspondence between analytical and empirical slow-flow dynamics, with the first step requiring empirical mode decomposition (EMD) analysis of the measured time series leading to sets of intrinsic modal oscillators (IMOs) governing the vibro-impact dynamics at different time scales. By comparing the spatiotemporal variations of the nonlinear modal interactions (and hence the IMOs), we examine how vibro-impacts influence the low- and high-frequency modes in global and local senses. In applications of the NSI results to structural health monitoring and damage detection (SHM / DD), we calculate typical measures such as the modal assurance criterion (MAC) and the coordinate modal assurance criterion (COMAC) by extracting information about the mode shape functions from the spatiotemporal IMO solutions. Whereas the MAC provides a global aspect of damage occurrence (i.e., which modes are more affected by induced defects), the COMAC can narrow down the damage locations (i.e., where in the structure defects exist that yield low correlation values in specific modes). Finally, we discuss the use of the 2-dimensional correlation spectroscopy technique to SHM / DD, which is frequently used in optical chemistry areas. With the spatiotemporal IMOs the 2-D correlation intensity for the linear beam is proportional to the product of the two mode shape functions at the respective positions; hence any deviations from that may indicate the occurrence and locations of damage in the structure.

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