shm for buildings - bridge & structure webpage wireless or wired? • long term application –...

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SHM for BuildingsSHM for Buildings

Mita LabKeio University

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Akira MitaKeio University

APSS July 27, 2010

Sensing, processing and prognosisSensing, processing and prognosis

Typhoon

Smart sensorsFOS

Analog, digitalfilters

Subspace methodARMAX

Mode parametersSignals

SVMNeural net

Dataacquisition

CleansingCuration

DiagnosisPrognosis

Systemidentification

Featureextraction


頭脳

Quake

Typhoon

DamageSnap!

2

A/D

PC

Sensor

Typical sensor configurationTypical sensor configuration


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Long analog cables

・Many cables・Noise

・ Long and tedious installation labors

Experiment with analog sensorsExperiment with analog sensors


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Experiments conducted at E-Defense6 storey RC building

892 sensors

Many sensor cables

Issues for sensor networksIssues for sensor networks

• Thousands of sensors are needed for large experiments.

• Wired sensor network requires cables as many as sensors.

• Digital sensor network is a good choice


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• Digital sensor network is a good choice to reduce cables.

• However, it does not ensure time synchronization.

Digital sensor networkDigital sensor network

RouterData acquisition host


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Wireless

Local sensor network

Wireless

Data acquisition hostRouter

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Wireless or Wired?Wireless or Wired?

• Long term application– Wireless : battery issues– Wired : permanent power supply

• Robustness under noisy conditionsWireless : weak


– Wireless : weak– Wired : very strong

• Stability– Wireless : instable– Wired : stable

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Time synchronization for Time synchronization for wireless systemwireless system


yy

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IEEE802.11bWireless STA

Ethernet NICStations(AD,CPU,etc.)

OffOff--thethe--shelf wireless systemshelf wireless system


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IEEE802.11bWireless AP

Sensors

PC

Ethernet NIC

Period：10msecIEEE802.11（CSMA/CA）

Accelerometer

Sensor 1

Sensor 2

Sensor 3

Synchronization testSynchronization test


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Sensor stationsSensor 0

Sensor 1

Access point

Host PC

Achievement of wireless sensorsAchievement of wireless sensors


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Broadcast signal was used for synchronization

First prototype using CU netFirst prototype using CU net


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3

・New protocol

・Synchronization pulse

・Well controlled

・Accurate time

・Less cables・Multi-drop

・Digital ・Less noise

Virtual common memoryVirtual common memory


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Global Memory512 bytes

Max 64 CPUs

CPU

CPU CPU

CPU

CPU

CPU

CommandFG

CPU

A/D

RS232C

CPUCPU

A/D

CPU

A/D

Logger

Time synchronizationTime synchronization


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Sensor 1 Sensor 2 Sensor 3 Monitor

100BASE-T

LSI LSILSI LSI

SA=1 SA=2 SA=3 SA=4

Same signal Synchronization check

0

0.005

0.01phase of transfer function

ad]

ResultsResults


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0 50 100 150 200-0.02

-0.015

-0.01

-0.005

frequency[Hz]

phase

[ra

unit1 to unit2unit1 to unit3unit2 to unit3

3 ～ 8μs delays

-0 015

-0.01

-0.005

0

0.005

0.01phase of transfer function

phase

[rad]

unit1 to unit2unit1 to unit3

Removing aliasing filterRemoving aliasing filter


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Be careful on the filter.

30～70[nsec]

0 50 100 150 200-0.02

0.015

frequency[Hz]

unit2 to unit3

Second prototypeSecond prototypeArmadillo and MEMSArmadillo and MEMS


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PIC16F84

RS232 driver

LAN cable

Second prototypeSecond prototype


Armadillo-J

ADXL202

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Current prototypeCurrent prototypeSUZAKUSUZAKU--V and servo sensorsV and servo sensors


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• SUZAKU-V– Memory（８ＭＢ）– PowerPC405（3.6ＭＨｚ）– 3.3ｖ

• A/D converter• Servo accelerometer

SUZAKU‐VPower supply

Current prototypeCurrent prototype


Linux is mounted on SUZAKU-V.

– 3 ch– High resolution– 2G maximum

AD converter

Accelerometer

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• Networked Structural health monitoring system. (SHM system)

– Web based data analysis components have been developed.

• There is no scheme of collecting data.

• There is no data model for SHM

Issues

EasyEasy--toto--use sensor networkuse sensor network


There is no data model for SHM.

• Low versatility of sensor networks- large size, expensive, cumbersome

configuration

“Zero-Configuration” Sensor systemscoordinates sensor networks and database

with the data models for automatic data acquisition

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Develop data models for SHM

Phase 1

Phase 2

Task phasesTask phases


Using highly versatile and smart sensors，

develop a sensor systemwhich coordinates sensor network and database

With the data models for automatic data acquisition

Phase 3

Verification tests

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RDB (Relational DataBase)

Stores data as 2D table

Primary keys and Foreign keys link a number of table

User doesn’t need to know Physical location of data.

RDB for sensor networkRDB for sensor network


RDB

Sensor_ID Sensor_name User_name

01 C-MOS G.Sato

02 MOTE Abrucchi

Type_ID Sensor_ID Type_name

05 01 Acceleration

09 02 Displacement

RDBMS（RDB Management System）controls RDB.

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Str Info

StrID(PK)

StrName

TotalSiteArea

Fl N b

Acc data

AccID(PK)

SensorID(FK)

Date

Filename

Direction

SensorInfo

Sensor ID(PK)

A l t ID(FK)

Channel Info

Record condition ID(PK)

Sampling frequency

Duration

Triggermode

PK – Primary KEY

FK – Foreign KEY

UserProfile

RoleProfile

Data model for sensorsData model for sensors


FloorNumber

EaveHeight

Application

StrType

Damping Equipment

CompletionDate

Administrator

Location

CreateDate

LastUpdate

Constructor

Direction

ACCMax

RecordConditionID(FK)

AccelerometerID(FK)

ADID(FK)

SUZAKUID(FK)

Sampling frequency

Settleposition

StrID(FK)

IPadress

MACadress

Trigger mode

Accelerometer Info A/D device Info Suzaku Device Info

Sens sync data

SDID(PK)

SensorID(FK)

Date

Filename

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5

• Application map

measure

sensor_read

server

A/D Converter

(Port 9000)

Network DatabasepostgreSQL

Data

measure

server DatabasepostgreSQL

A/D Converter

sensor_read


ServoAccelerometer

receiver (Port 9001)

postgreSQL

Sensor (client) Server

postgreSQLServo

Accelerometer

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• Split and save files– X acc data

– Y acc data

– Z acc data

– Sensor synchronization data

– File format sensorID_IPadress_accdata_yyyy_mmdd hh mm ss direction txt

Socket()

bind()

listen()

accept()

Socket()

connect()

recv()

write()

クライアントからの接続待機

コネクション確立

fopen()

fprintf()write()

データ

データ

loop

Parent process

Data reception


dd_hh_mm_ss_direction.txt

– 2_192.168.1.14_accdata_2006_12

22_0_12_4_X.txt

• Inserting Meta-data to DB– Inserting sensor meta-data to

acc_data table at server

recv()

fprintf()

fclose()

close()

exec sql insert

exec sql connect

exec sql disconnect

close()

ファイル終了(EOF)通知

Child process

Database

process

Sensor(Client)

Server

Split and save files

Inserting Meta-dataＤＢ

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Smart Sensor Data

Data transferData transfer


Smart Sensor Data

measure!!

Data acquisition completed!

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Acc_data table

MetaMeta--data inserted into tabledata inserted into table


Automated data collection and insertion to DB

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Maximum No. of sensorsMaximum No. of sensors• Measure a condition of server for simulation

– Emulate sensors by softwares.

– Measure CPU usage, free memory, and load average

Findings


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• The maximum number of sensor nodes is approx. 1000.

• The bottleneck of system is the process of inserting Meta-data into database

⇒ need to limit the number of connection node to approx. 500 for ensuring

of data reliability

Hierarchization of sensor network resolve this problem ???

Cell structure configurationCell structure configuration• Cell structured sensor network

– Consists of sensor units called “cell”

– Network is an hierarchic structure of cell.

– Root node which belongs to top cell gathers data of lower cell and connects to

server


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ServerServer

CELL

CELL CELL CELL

CELL CELL CELLCELLCELLCELLCELL CELLCELLCELLCELL

Root

1st level

2nd level

CELL

Mother node

Child node

Child node

Child nodeChild node

Child node

Child node

Child node

6

010020030040050060070080090010005

10

15

20

25

30

the number of root nodes

Exe

cut

ion

Tim

e (

sec)

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1000 nodes transmit 1-sec data

The execution time

decreases

The number of Root node decreases


31Smaller number of root nodes is preferred.

2 4 6 8 10 12 14 16 18 200

10

20

30

40

50

60

70

Execution time (sec)

Load

Ave

rage

1000nodes

500nodes100nodes50nodes

10nodes1node

Load decreas

e

31



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• All sensors should have the same clock.


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A5s.

B3s.

C10s.

A5s.

B5s.

C5s.

FeaturesFeatures

• Time synchronization of the sensor network is evaluated.

• Time synchronization system is implemented in real machine.


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• About 10% of resources in FPGA were consumed by time synchronization system.

Implementation detailsImplementation details

• The A/D converter in the sensor node needs 1KHz timing signals.

• Small jitter of the 1KHz timing signals make better measurement.


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• The 1KHz timing signals need under 10μs jitter.– 10μs jitter makes 1% jitter for the 1KHz

timing signals.

Cell structureCell structure

• Our sensor network consists of cells.

• Tree structure configuration

CellRoot


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Cell

Cell Cell

Cell

Cell

Cell CellCellCellCellCellCellCellCell Cell

Root

1st level

2nd level

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Hub connections for a cellHub connections for a cell

From: upper level cellUpper level cell port

Mother sensor node port

Child sensor node port


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To: mother sensor node

To: child sensor node or lower level

cellSensor node

Transmission of time Transmission of time synchronization signalssynchronization signals

(4,5) lines in the cable is connectedto (7,8) lines in the cable.(7,8)

linesin the

From:the upper level cell

This is a hub.These are linesSensor network in this implementation

is a wired network by 100BASE-TX.2 f 4 i d li i th t 5 bl

The synchronization signals come from the upper level

The synchronization signals are input to the mother sensor node.In mother sensor node, time is synchronized by using the time synchronization signalsThe new time synchronization i l li f

Finally the new time synchronization signals are input to the child sensor nodes and lower level cells.In the child sensor nodes, time is


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(4,5) linesIn the cable

(7,8)linesin thecable






cable

Themothersensornode

Thechild

sensornode

Thechild

sensornode

Thechild

sensornode To:

the lower level cells

2 of 4 paired lines in the category-5 cable arenot used in the 100BASE-TX network.The time synchronization signals were

transmitted in the 2 pair lines.

come from the upper level cell through lines 7&8 of

the cable.

using the time synchronization signals.The mother sensor node then generates new time synchronization signals.

signals are output to lines 4&5 of the cable.

Lines 4&5 of the cable join to lines 7&8 in the hub.

In the child sensor nodes, time is synchronized by using the new time synchronization signals.

Real machine environmentReal machine environment

• Modified commercial hubs and cables were used.

• RS-485 was used for time synchronization signal transmission


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signal transmission.

• Maximum distance between nodes was 190m.

Hub Hub Hub

190m

Real machine resultReal machine result

• All sensor nodes were synchronized correctly.

• An ID and commands were transmitted correctly.


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• Maximum jitter was 1.53μs .

Current SHM systemCurrent SHM system


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Prototype SHM systemPrototype SHM system

TCP/IP

Diagnosis serverSystem ID

Diagnosis conditions

Building Mita lab servers User

Diagnosis results


Sensor gatewayCommunication with sensorsNTP severData converter

Data serverData baseWeb serverSensor interfaceSystem control

This system can automatically runfrom data acquisition to feature extraction.

Browse and control

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Smart sensor unitSmart sensor unit

• Automatic operation– Communication with a server

– Measuring data

• Three timings to measure– Over trigger value

Set time


Power supply

Accelerometer

SUZAKU-V

A/D converter

– Set time

– Use command

• Command system– Trigger value

– Microtremor on/off

– Start anytime

x yz

Data modelData model

Measurement

ServerEvent

SensorAnalysisUser


BuildingAuth

It became possible to search necessary information quickly,and to analyze corresponding to various buildings.

Data flowData flow

Smart sensor

cv_read cv_read new_environment SHMDB

Store

Add metadata

To decimal

Mita Laboratory

Add metadata

Metadata.xmlMeas_data.txt

Database registration

Data ServerSensor gateway


/media/HD-PSU/raw_datarsync

A/D converter

Sensor

Signal

To physical

Synchronization

Diagnosis Server

The user does not need to insert the relevant metadata for each measurement.

/media/HD-PSU/edit_data /media/HD-PSU/edit_data

KK--SHM consortiumSHM consortium

• 14 companies are supporting the consortium based at Keio U. starting from FY2008 for three years.

• Smart sensor network is used as an


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infrastructure for this SHM

• Companies include largest design firms and many construction companies.

• The system will be available as a commercial product soon.

Application to real structuresApplication to real structures

Name A building B building C building D building

No. of story 6 story 11 story 3 story 14 story


Sensor 1 - 11th floor - 14th floor

Sensor 2 5th floor 1st floorseismic isolator

1st floor

Installation date

Nov. 9, 2009 Feb. 5, 2010 Apr. 7, 2010 Apr. 21, 2010

Application to real structures (1/4)Application to real structures (1/4)

• A building– S structure (6-story)

– Seismic isolated building

– 2009/11/09~


– 1 sensor (5th floor)

– 14 seismic data were acquired

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• B building– SRC structure (11-story)

– 2010/02/05~

– 2 sensors (1st, 11th floor)




• C building– RC structure (3-story)

– Seismic isolated building

2010/0 /0


– 2010/04/07~

– 1 sensor (seismic isolator)

– 1 seismic data was acquired


• D building– S structure (14-story)

– Damping system

– 2010/04/21~


– 2 sensors (1st, 14th

floor)


– mobile data transfer system

Database and data Database and data managementmanagement


gg

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EDgridEDgrid for Efor E--DefenseDefense

Firewall

Internet

RHL4(64bit)

EDgrid Central

Grid Auth

mysql

RHL4(64bit)

EDgrid Central

Grid Auth

mysql

RHL4(64bit)

EDgrid Centraledcentral0 edcentral1 edcentral2

RHL4(32bit)

EDgrid pop(NEESpop)edgrid

RDV

mysql

開発マシンホットスタンバイ(EDgrid Central)

EDgrid アーキテクチャ2006.12

開発マシン


Firewall RHL4(64bit) RHL4(64bit) RHL4(64bit)RHL4(32bit)

RHL4(64bit)

DNS/Maildns

DNS

Mail

RHL4(32bit)

backup

RHL4(64bit)

Repositorystorage

Repository

PostgreSQL

Windows(32bit)

Data inputClientTerminal

Converter

RHL4(64bit)

TelepresenceServervideo

RBNB

mysql

flexTPS

RHL4(64bit)

RBNB

mysql

flexTPS

video0

負荷分散Telepresence Server

開発マシンhttps で接続

NFS

ntp

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sensor

sensor

sensorsensor

sensorsensor

Sensor gridDamage data, please!

Here you are.This is easy to understand, right?

Give me data!

What is this?Current system

Smarter way for SHMSmarter way for SHM


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sensorsensor sensor

sensor

sensor

sensor

sensorsensor

sensor sensor

sensorsensor

targetLab.Smart sensor network can understand what you want!

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Our current research focusOur current research focusBioficationBiofication of living spacesof living spaces


g pg p

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Adaptive buildingsAdaptive buildings


Sensory adaption• Air conditioning• Lighting• Water supply• Parking system

Adaption by learning• Automatic switch

for TV• Air conditioning fit

to residents• Pattern control for

lighting

Physiological adaption• Adaptive to family

members• Adaptive to

elderly people• Adaptive to

season s• Security based on

immune system

Evolutionary adaption• Creation of new

living space that is different from LDK system

• Portable and flexible space design

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Major functions for Major functions for bioficationbioficationSensors• Acquisition of environmental

information• Sensory adaption

Brain• Centralized control system• Adaption by learning


Immune system• Distributed intelligence• Physiological adaption

DNA• Creation of next generation• Evolutionary adaption

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ee--puckpuckEcole Polytechnique Fédérale de Lausanne as collaboration between the Autonomous Systems Lab, the Swarm-Intelligent Systems group and the Laboratory of Intelligent System

Specifications


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Micropohone×3Bluetooth commnication

xy

z VGA camera(640×480)3-axis accelerometerProcimity sensor×8

Specifications

Robot 1 for Robot 1 for bioficationbiofication


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Robot 2 for Robot 2 for bioficationbiofication


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Teach B,C,D positions

Instruct B,C,DA person has entered！

Step 1: Collaboration

Step 2: Monitoring environmental change

Step 3: DNA for next generation

Acquisition of environmental Acquisition of environmental data using multiple robotsdata using multiple robots


C B

A D

C B

A D

Furniture has moved！

CB

AD

Record important InformationAs

“Spatial DNA”

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SummarySummary

• Smart sensors have been developed and are currently under feasibility study.

• An SHM platform has been completed and is currently under test with many companies.

• Data management is most important


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• Data management is most important.

• The system will be jointly used with sensor agent robots.

• Biofication of living spaces is a natural evolution of SHM.

shm for buildings - bridge & structure webpage wireless or wired? • long term application –...

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