Structural Monitoring of the Federico II School of

Engineering

C. Rainieri, G. FabbrocinoG. Manfredi, E. Cosenza

SHM: aims

Aims:

Dynamic Identification

Model updating

Deeper knowledgeabout soil-structureinteraction

Damage detection

Structural control

Deeper knowledge of the dynamicbehaviour and of the ability of structure to withstand seismic events

Level of safety after earthquake: earthquake scenarios and support in decision making processes

The School of Engineering Tower

13 stories (2 underground); 41 m tall; r.c.moment frames structure; strengthenedafter 1980 to bear seismic loads;

The seismic network

The building is embedded in the seismicnetwork issued by AMRA: EW application

Architecture of the systemFeatures:

Redundant vectors (DSL, traditional and cellular phone, satellite)

Reduced need of cables(T-Node)

Local slave: synchronization

Local master: storing validateddata into a MySQL DB and transmit results of analyses

Control Panel: accessedthrough an internet connection

DB structure

Sensors

Kinemetrics Episensor FBA ES-U2: 2.5 V/g sensitivity, ±1 g FS range;

PCB Piezotronics 393B04, 393A03: 1 V/g sensitivity, ±5 g FS range

Sensors

Kinemetrics Episensor ES-T;

Kinemetrics Shallow BoreholeEpisensor SBEPI

DAQ systems

The local master and the KinemetricsK2 Digital Recorder

Control Panels

LabView Application linkedto MySQL DB

Kinemetrics softwares forcontinuos monitoring and visualization

Some records: geotechnical sensors

Some records: structural sensors

The OMA software

LabView software for data processing

The frequency domain method implemented in the software is the Enhanced Frequency Domain Decomposition, based on the singular value decomposition of the cross spectral density matrixof the outputs and on the identification of a SDOF Bell function.

The OMA software

Able to perform ID both in Time and Frequency Domain

The OMA softwareTools

Overlapping and windowingDecimationAuto and cross-power spectraCoherence functionsEFDDSSIMAC, AutoMAC and CrossMACmatricesMode Shape VisualizationReport of the identified modalparameters for each method

ConclusionsUse of redundant vectors (DSL connection, traditional or cellular phones, satellite) for data transmission to assure the effectiveness of the system even if an earthquake occurs.

System easily expandable through installation of T-Nodes and, eventually, local slaves

Data processing software can be easily integrated or updated, making the system versatile and allowing its upgrade with the new methods which could be developed in the field of operational modal analysis and damage detection during the next years

Spread knowledge allows the optimization of the network performances and reduces during ordinary time data flows.

Integration of SHM and EWS is the real medium term objective of the work.