A structural monitoring system comprises a plurality of modular, battery powered data acquisition devices which transmit structural information to a central data collection and analysis device over a wireless data link. The data acquisition devices each comprise mechanical vibration sensors, data acquisition circuitry, a digital wireless transmitter, and a battery for providing electrical power to the device. The central data collection device comprises a digital wireless receiver that receives data sent from the data acquisition devices, and a microprocessor for processing the data. A more powerful computer may be interfaced with the central device to provide more sophisticated analysis after a natural hazard or other extreme event. A methodology for operating the monitoring system is also disclosed.

A modular, wireless damage monitoring system for structures

Optimal sensor placement methodology for parametric identification of structural systems

A statistical methodology is presented for optimally locating the sensors in a structure for the
purpose of extracting from the measured data the most information about the parameters of the model used
to represent structural behavior. The methodology can be used in model updating and in damage detection
and localization applications. It properly handles the unavoidable uncertainties in the measured data as well
as the model uncertainties. The optimality criterion for the sensor locations is based on information entropy,
which is a unique measure of the uncertainty in the model parameters. The uncertainty in these parameters is
computed by a Bayesian statistical methodology, and then the entropy measure is minimized over the set of
possible sensor configurations using a genetic algorithm. The information entropy measure is also extended
to handle large uncertainties expected in the pretest nominal model of a structure. In experimental design,
the proposed entropy-based measure of uncertainty is also well-suited for making quantitative evaluations
and comparisons of the quality of the parameter estimates that can be achieved using sensor configurations
with different numbers of sensors in each configuration. Simplified models for a shear building and a truss
structure are used to illustrate the methodology.

Entropy-Based Optimal Sensor Location for Structural Model Updating

SUMMARY
Careful selection and placement of sensors are the critical issue in the construction and implementation of an effective structural health monitoring system. A hybrid method termed the optimal sensor placement strategy (OSPS) based on multiple optimization methods is proposed in this paper. The initial sensor placement is firstly obtained by the QR factorization. Then, using the minimization of the off-diagonal elements in the modal assurance criterion matrix as a measure of the utility of a sensor configuration, the quantity of the sensors is determined by the forward and backward sequential sensor placement algorithm together. Finally, the locations of the sensor are determined by the dual-structure coding-based generalized genetic algorithm (GGA). Taking the scientific calculation software matlab (MathWorks, Natick, MA, USA) as a platform, an OSPS toolbox, which is working as a black box, is developed based on the command-line compiling and graphical user interface-aided graphical interface design. The characteristic and operation method of the toolbox are introduced in detail, and the scheme selection of the OSP is carried out on the world's tallest TV tower (Guangzhou New TV Tower) based on the developed toolbox. The results indicate that the proposed method is effective and the software package has a friendly interface, plenty of functions, good expansibility and is easy to operate, which can be easily applied in practical engineering. Copyright © 2011 John Wiley & Sons, Ltd.

Optimal sensor placement for structural health monitoring based on multiple optimization strategies

The important role played by the duration of ground shaking in the response of saturated soil deposits is universally acknowledged, but no such consensus exists regarding the degree of influence that duration exerts on structural damage. There are several hundred papers in the literature that link structural damage to parameters related either directly or indirectly to the duration of strong ground motion. The conclusions of these studies differ widely with regard to the influence of strong-motion duration on structural demand. This paper provides a summary and critical review of the literature on this subject. It is found that studies employing damage measures related to cumulative energy usually find a positive correlation between strong-motion duration and structural damage, while studies employing damage measures using maximum response generally do not find strong correlations between duration and damage.

A State-of-Knowledge Review of the Influence of Strong-Motion Duration on Structural Damage

A criterion is proposed for making decisions regarding the optimal location of a given number of sensors to record the seismic response of a structure for identification purposes. The optimal location of the sensors is selected so that the expected value of a Bayesian loss function, expressed in terms of the Fisher information in the recordings, is minimized. The criterion is applied to the case of multi-degree-of-freedom systems with uncertain structural properties subjected to earthquake ground motions modelled as stationary stochastic processes. The use and capabilities of the criterion are thoroughly illustrated by means of an example. Results are used to assess the influence of record duration, recording noise, and ground motion frequency content and amplitude, on the optimal location of accelerometers as well as on the reduction of prior uncertainty about the structural parameters. © 1998 John Wiley & Sons, Ltd.

Optimal instrumentation of uncertain structural systems subject to earthquake ground motions

Methodology is presented for simulating properly correlated earthquake ground motions at an arbitrary set of closely spaced points, compatible with known or prescribed motions at other locations. The input consists of the spectral density function and frequency-dependent spatial correlation function in several nonoverlapping ground-motion segments. Linear-prediction estimators are used to generate a set of statistically independent, frequency-specific, spatial random processes, based on which ground motions are composed by means of a fast-Fourier-transform algorithm. The method’s advantage over existing linear-estimation techniques, known as Kriging, is that it correctly reproduces the specified space-time correlation structure of the ground motion. Examples are given to illustrate the features of the simulation methodology; in particular, response spectra and dynamic response ratios are compared for recorded and simulated motions at the site of the SMART 1 strong-motion accelerograph array.

Conditional Simulation of Spatially Correlated Earthquake Ground Motion

A randomvibration methodology is formulated for the seismicresponse analysis of linear multisupportstructural systems. It reduces the response evaluation to that of a series of linear onedegree sys...

Ernesto Heredia-Zavoni

Papers

Optimal instrumentation of uncertain structural systems subject to earthquake ground motions

Conditional Simulation of Spatially Correlated Earthquake Ground Motion

Seismic Random‐Vibration Analysis of Multisupport‐Structural Systems

Environmental contours using copulas

Development of environmental contours using Nataf distribution model