The Self-Organising Seismic Early Warning Network (SOSEWN) J. Zschau, C. Milkereit, M. Picozzi, K. Fleming, I. Veit, K.-H. Jäckel, J. Nachtigall, H. Woith,

The Self-Organising Seismic Early Warning Network (SOSEWN)

J. Zschau, C. Milkereit, M. Picozzi, K. Fleming, I. Veit, K.-H. Jäckel,J. Nachtigall, H. Woith, M. Hönig

M. Erdik, C. Zulfikar, O. Ozel

J. Fischer, J.P. Redlich, B. Lichtblau, F. Kühnlenz, I. Eveslage, S. Heglmeier

SAFER Final Meeting, Potsdam, June 2009

Seismic Early Warning – Standard Approach

WLAN

Classical Seismological Station

DSL

Istanbul

Central Side:A normal NodeVisualisationBackup, Monitoring

SAFER Potsdam, June 2009

WLAN

Classical Seismological Station

Central Side:A normal NodeVisualisationBackup, Monitoring

DSL

City

The SOSEWIN Vision

The development of a new seismic network for earthquake early warning (EEW), made up of low-cost sensors that will eventually be purchasable by a range of end users, giving very dense urban networks

The Seismological SOSEWIN will complement existing EEW networks.

Gateways (Internet)

Public NodeLow Cost Node


The much denser seismic network

means the output from the expanded

ShakeMap will rely more on real data, and less on interpolation

schemes

Provide data for high-resolution shake maps,

allowing neighbourhood-scale

rapid damage assessment

The SOSEWIN Vision


Communication layer

LNs will communicate in a 4-5 k-hop

Comm. Target (Gateway)Low wireless metric par.High wireless metric par.

Seismic source

Application layers

50 – 100 m 500 m

Leader Node (LN)Sensing Node (SN) Ground floor

.

.

.

self-organizing ad-hoc wireless mesh network

SOSEWIN Architecture

The mesh sensor net is reliable and also operates if single sensors are destroyed, allowing the system to still detect the earthquake

Routing by the Optimised Link State Protocol


Sensing units (Internal view)

Accelerometers(measurement range (measurement range +/- 1.7 g, noise level 0.5 mg)+/- 1.7 g, noise level 0.5 mg)

GPS engine

Connections forWLAN antennas

4 AD converter

WRAP board underneath

(18.5 - 19 bits)

Prices:PC ~100€Sensor ~100€Casing ~100€GPS ~50€AD-Converter ~100€Battery, cable ~100€

an enbedded PC with a 266 MHz CPU

Power consumption less than 5 W, in totalSAFER Potsdam, June 2009

CH1: Dynamic range dB 104.534




Effective Bits 18.865




Analogue/digital converter (ADC) characteristics


180°

Counts-to-(m/s2): 115597

CH1

CH2

CH3

CH1

Sensitivity of accelerometer ADXL203 by tilt test

ADXL203 – sensitivity 1mg


MicrophoneMicrophone

TemperatureTemperature

VoltageVoltage

In order to add additional functionality to SOSEWIN, sensors for the monitoring of different environmental parameters are tested in the SNs 4th channel

Testing SOSEWIN


Shaking table test, Istanbul, Turkey 17/06/2008

Z

N E

Langebrüke, Potsdam, Germany 06/06/2008

EPISENSOR

SOSEWIN

Test and calibration


AKUKO - IERREWSVERTICAL ARRAY - GFZ-Kandilli Obs. 2D Seismic Noise Array - GFZ

Testing SOSEWIN: Ataköy district, Istanbul


18 Sensing Nodes18 Sensing Nodes

2 Gateways + 2 Gateways + Sensing NodesSensing Nodes

Testing SOSEWIN: Ataköy district, Istanbul


Istanbul Installation – Link qualitiesIstanbul Installation – Link qualities

Istanbul Installation – Routing pathsIstanbul Installation – Routing paths


since July 2008 a Seiscomp Server at GFZ collects data

SN in AtakSN in Atakőyőy

SSNN at at GGFFZZ

SSNN at at GGFFZZ

SSNN at at GGFFZZ

SN in AtakSN in Atakőyőy

Data are retrieved in real time from the different SN

clustersObserved Delay is

less than 2s


20 km – Ml 3

35 km – Ml 3.5

60 km – Ml 4

100 km – Ml 4.5

160 km – Ml 5

200 km – Ml 5.5

10 km – Ml 2.5

Magnitude-Distance limits for detection of events by SOSEWIN (based on instrumental sensitivity)

from Georgia Cua, 2004


EVENT_2008_07_10_7e50 UTCAbout 140 km from Istanbul

B26 – sensor on top of the building

Installation of more nodes for building are plannedaiming to perform monitoring of infrastructers


EVENT_2008_10_05_6e04 UTCAbout 40 km from Istanbul


AnalysisAnalysis

CommunicationCommunication

Storage of dataStorage of data

Data processing for Early Warning

…[aZ,aN,aE], [aZ,aN,aE], [aZ,aN,aE],…

[ ,aN,aE], [vZ,vN,vE], [dZ,dN,dE]

4th order Butterwort Filter[0.075 Hz- 25 Hz]

ring buffer

Integration to velocity & displacement

sensePsenseP

aZ

aN aE

senseSsenseS

[a max, v max, d max, CAV, P, Arias’s Intensity]

[a max, v max, d max, CAV, Arias’s Intensity]

endofEventendofEvent

Energy rate

Final ReportDisaster ManagementDisaster Management (Data are in a format

appropriate for USGS tool ShakeMap)

Event Detection and Event Detection and Early Warning MessagesEarly Warning Messages

Event Characterization Event Characterization and Real-Time Rapid and Real-Time Rapid Response MessagesResponse Messages


Experiences from the testbed in IstanbulExperiences from the testbed in Istanbul

• Problems with the WLAN drivers, Istanbul testbed had to be throttled to 1MBit/s WLAN connections– Good: There is still enough bandwidth for streaming all data out

of the network with seedlink• Problems with the CompactFlash cards

– a new version runs with industrial grade CF cards– Software optimized for CF cards

Main positive results are:

• The performance and the long-term stability of the sensor nodes as strong motion sensors, which have proven to be running stable for several months

• The performance of the installed network and its self-organization capability

• Possibility for tests with synthetic data at the nodes• Remote administration

(Solved) Problems:


Navelli’s municipality center

Soon after the Mw 6.3 Central Italy Earthquake of 6 April 2009, the German Earthquake Task Force supported Italian teams there


SOSEWIN TASK-FORCE mission

Mw 5.4 aftershock of 9 April 2009 (00:53 UTC)

By SOSEWIN nodes the infrastructure can be

monitored and waveform data received after the

occurrence of aftershocks without site visit




By interferometric analysis, rapid estimates of velocity of shear waves and their attenuation, which are the

parameters from whom the response of the building to the shacking is largely determined, can be obtained.



Continuous spectral analysis of the shacking allows the main modal properties of the building to be regularly re-evaluated with great detail, and thus, to monitor the building damage during and

soon after the occurrence of aftershocks.


THANK YOU

Documents

The Self-Organising Seismic Early Warning Network (SOSEWN) J. Zschau, C. Milkereit, M. Picozzi, K. Fleming, I. Veit, K.-H. Jäckel, J. Nachtigall, H. Woith,