Chapter 123 Modular Architecture of SHM System for Cable ...zn903.com/benchmarkstudy/Reference...

Chapter 123Modular Architecture of SHM Systemfor Cable-supported Bridges

Kai-Yuen Wong1 and Yi-Qing Ni21 Highways Department, Government of Hong Kong, China2 Department of Civil and Structural Engineering, Hong Kong Polytechnic University, Kowloon,Hong Kong, China

1 Introduction 12 System Architecture of WASHMS 23 Operation of WASHMS 154 Conclusions 16

References 16

1 INTRODUCTION

Bridge health monitoring is the tracing of thestructural health conditions of the bridge in termsof the physical parameters categorized as environ-mental loads and status, traffic loads, bridge features,and bridge responses by reliably measured data andevaluation techniques, in conjunction with inductive

Encyclopedia of Structural Health Monitoring. Edited byChristian Boller, Fu-Kuo Chang and Yozo Fujino 2009John Wiley & Sons, Ltd. ISBN: 978-0-470-05822-0.

reasoning and experience so that the current andexpected future performance of the bridge, for at leastthe most critical limit events, can be predicted orevaluated. Bridge health monitoring system has beenadopted in the past decade to monitor and evaluatethe structural health conditions of cable-supportedbridges in Hong Kong [1–5]. The bridge health moni-toring system in Hong Kong is referred to as windand structural health monitoring system (WASHMS ).Bridge health monitoring system is currently consid-ered as an integral part of bridge operation, bridgeinspection, and bridge maintenance and has beenincluded as a standard mechatronic system in thedesign and construction of most large-scale andmultidisciplinary bridge projects such as Stonecut-ters Bridge (SCB) in Hong Kong [6], and SutongBridge [7] and Donghai Bridge in mainland China[8]. The experience gained in the design, installa-tion, operation, maintenance, and development of theWASHMS for Tsing Ma Bridge (TMB), Kap ShuiMun Bridge (KSMB), Ting Kau Bridge (TKB), andthe cable-stayed bridge in Hong Kong side of theHong Kong-Shenzhen Western Corridor (HSWC) hasa significant influence on the design of new structural

2 Civil Engineering Applications

health monitoring systems (SHMSs) in Hong Kongand in mainland China. The WASHMS in HongKong, which is based on modular design concept,has been improved particularly in the aspect of datainterpretation, health evaluation, and data manage-ment and such improvements have been incorporatedin the design and installation of the WASHMS forSCB (SCB-WASHMS) [6].

2 SYSTEM ARCHITECTUREOF WASHMS

The modular concept of WASHMS [9–11], whichis devised to monitor structural condition andevaluate structural degradation as it occurs ratherthan to detect structural failures, is composed ofsix integrated modules, namely, module 1—sensorysystem (SS); module 2—data acquisition andtransmission system (DATS); module 3—dataprocessing and control system (DPCS); module4—structural health evaluation system (SHES);module 5—structural health data managementsystem (SHDMS); and module 6—inspection andmaintenance system (IMS). Figure 1 illustrates

the modular architecture and input/output blockdiagram of WASHMS. Of these six modules,modules 1–3, which are the key modular systemsfor the execution of real-time structural healthmonitoring, are composed of different types of SSs,data/video logging systems, cabling network systems,servers and software facilities for data acquisition,transmission, and processing. The schematic layoutof typical connections among modules 1–3 is shownin Figure 2. Modules 4 and 5, which are key modularsystems for the execution of offtime structural healthevaluation, are composed of servers, workstations,and software facilities for data interpretation, healthevaluation, data management, and generation ofreports. Module 6 is a set of portable computers (thatstore the system design information and operationand maintenance manual of WASHMS) and tools forcarrying out inspection and minor maintenance of theWASHMS itself.

2.1 Module 1—sensory system (SS)

The SS that refers to the sensors and their corre-sponding interfacing units for input signals gathered

Module 1Sensory system

Module 2Data acquisition andtransmission system

Mod

ule

6In

spec

tion

and

mai

nten

ance

sys

tem Module 3

Data processing andcontrol system

Module 4Structural health

evaluation system

Module 5Structural health datamanagement system

Wind and structural health monitoring system (WASHMS)

Analytical models:Finite element modelsSurrogate models

Monitoring reports:Instant display reportsDetailed reportsSpecial reportsBridge rating reports

Bridge data and information:Bridge design criteriaBridge monitoring criteriaAs-built bridge recordsBridge inspection and Maintenance recordsMeasurement quantities:

Environmental statusTraffic loadsBridge characteristicsBridge responses

System inspection Data and information transmission Updating of data and information

Figure 1. Modular architecture and input/output block diagrams of WASHMS.

Modular Architecture of SHM for Cable-supported Bridges 3

DPCS

DAU orDVC

Adm

inis

trat

ion

build

ing

SensorsSensors SensorsSensorsSensorsSensors SensorsSensors

SensorsSensorsSensorsSensorsSensorsSensors SensorsSensors

Global cabling network system—ring-type single mode optic fiber

DAU Data-acquisition unit

Brid

ge s

ite

DVC Digital video converter

DPCS Data processing and control system

DAU orDVC

DAU orDVC

DAU orDVC

DAU orDVC

DAU orDVC

DAU orDVC

DAU orDVC

Figure 2. Schematic layout of module 2—data acquisition and transmission system.

from various monitoring equipment and sensors iscategorized into four groups: (i) sensors for moni-toring of environmental loads and/or status, whichinclude anemometers (three-dimensional ultrasonictype and two-dimensional propeller type), tempera-ture sensors (for the measurement of temperatures inrespective air, asphalt pavement sections, structuralconcrete sections, structural steel sections, suspensioncables, and stay cables), corrosion cells, hygrome-ters, barometers, and rainfall gauges; (ii) sensors formonitoring of traffic loads, which include dynamicweigh-in-motion stations, digital video cameras, anddynamic (weldable foil type) strain gauges; (iii)sensors for monitoring of bridge characteristics,which include fixed and removable/portable servo-type accelerometers, global positioning systems, levelsensing stations, and dynamic strain gauges; and(iv) sensors for monitoring of bridge responses,which include dynamic strain gauges, static (vibratingwire type) strain gauges, displacement transducers,global positioning systems, tiltmeters, fixed servo-type accelerometers, buffer sensors, bearing sensors,and elastomagnetic sensors.

In the design/selection of the types and locationsof SSs, the following six basic criteria should befulfilled: (i) the SS should have the ability to capturethe local- and system-level responses, which could be

correlated or compared with the design values; (ii) theSS is required to integrate the predictive modelingand data interrogation processes with the sensingsystem design process; (iii) the SS should have thefunction to acquire data in a consistent and retriev-able manner for long-term statistical data processingand analysis; (iv) all sensors should be chosen fromthe contemporary commercially available sensors thatbest match the defined sensing performance require-ments; (v) the SS should include additional measure-ments by removable/portable sensors to quantifychanging operational and environmental conditions;and (vi) at key locations, different types of sensorsshould be deployed so that cross calibration of sensorscould be carried out.

The major parameters monitored by each typeof sensors are listed in Table 1. Figures 3–7 illus-trate the layouts of the SSs in TMB, KSMB,TKB, HSWC, and SCB on their respective fullthree-dimensional finite element models, which arebuilt by MSC-PATRAN. The layouts of the SSsas shown in Figures 3–7 are deployed or arrangedin such a manner that the measured raw data canbe used to derive the information or parametersas listed in the fourth column of Table 1. Thesederived information and parameters are then used tocompare/correlate with (i) the corresponding bridge


Table 1. List of required sensory systems and physical parameters for processing and derivation

Monitoringcategory

Physicalquantity

Required types ofsensory systems

Physical parameters forprocessing and derivation

Environments Wind loadmonitoring

• Ultrasonic-type anemometers• Propeller-type anemometers• Barometers(a,b)

• Rainfall gauges(a,b)

• Hygrometers(a,b)

• Wind speed and wind direction plots(time-series data)

• Wind speeds (mean and gust) anddirections (histograms)

• Terrain factors and wind speed profile plots• Wind rose diagrams• Wind incidences at deck level• Wind turbulence intensities and intensity

profile plots• Wind turbulent time- and length-scale plots• Wind turbulent spectrum and cospectrum

plots• Wind turbulent horizontal and vertical

coherence plots• Wind response and wind load transfer

function• Wind-induced accumulated fatigue damage• Histograms of air pressure, rainfall, and

humidity

Temperature loadmonitoring

• Platinum resistancetemperature detector (RTD)type for temperaturemeasurements in structuralsteel, concrete, asphaltpavement, and air

• Thermocouplers for cables

• Effective temperatures in towers, deck, andcables

• Differential temperatures in deck and tower• Air temperatures and asphalt pavement

temperatures• Temperature response• Temperature load transfer function

Seismic loadmonitoring

• Fixed servo-typeaccelerometers

• Acceleration spectra near tower andanchorage

• Deck and tower response spectra• Seismic response and seismic load transfer

function

Corrosion statusmonitoring(a,b)

• Corrosion sensors(a,b)

• Hygrometers(a,b)

• Potential risk of rebar corrosion in concretetowers, concrete piers in side spans, andconcrete deck in side spans

Traffic loads Highway trafficload monitoring

• Dynamic weigh-in-motionstations (bending-plate type)

• Dynamic strain gauges• closed circuit television

(CCTV) cameras(c – e)

• Digital video cameras(a,b)

• GVW spectrum in each traffic lane• AW spectrum in each traffic lane• Equivalent number of SFV spectrum in

each traffic lane• Equivalent number of SFA spectrum in

each traffic lane• Highway-induced accumulated fatigue

damage—SFV• Highway-induced accumulated fatigue

damage—SFA• Overload vehicles detection• Traffic composition in each traffic lane• Traffic load response and traffic load

transfer function


Table 1. (continued )

Monitoringcategory

Physicalquantity



Railway traffic loadmonitoring(c,d)

• Dynamic strain gauges(c,d)

• CCTV video cameras(c,d)• Bogie loads in each line of train• Train loading spectrum• Equivalent standard load (train) spectrum• Train-induced accumulated fatigue damage• Train load response and train load transfer

function

Bridge features Static influencecoefficientmonitoring

• Level sensing stations(c,d)

• global positioning system(GPS)(b – e)

• Dynamic strain gauges

• Lane stress history in each traffic lane—eachvehicular type

• Stress range of each type of vehicle in eachtraffic lane

• Influence surfaces for combined deck platesand troughs

• Line stress history of each type of train• Stress range of each type of train• Influence coefficients at tower tops and deck

midspan

Global dynamiccharacteristicsmonitoring

• Fixed and portable servo-typeaccelerometers

• Global bridge modal frequencies• Global bridge vibration modes• Global bridge modal damping ratios (derived)• Global bridge modal mass participation factors

(derived)

Bridgeresponses

Cable forcesmonitoring

• Portable servo-typeaccelerometers

• Cable frequencies and hence cable forces• Cable damping ratios

Geometrymonitoring

• GPS(b – e)

• Level sensing stations(c,d)

• Displacement transducers• Servo-type accelerometers• Static strain gauges(c)

• Thermal movements of cables, deck, andtowers

• Wind movements in cables, deck, and towers• Seismic movements in deck and towers• Highway load movement in deck and cables• Railway load movement in deck and cables(c,d)

• Creep and shrinkage effects in concretetowers(a,b)

Stress monitoring • Dynamic strain gauges• Static strain gauges(a,b)

• Elastomagnetic sensors(b)

• Stress historical plots of instrumentedcomponents

• Stress demand ratio plots of instrumentedcomponents

• Principal stress plots of instrumentedcomponents

• Force demand ratios plots of concrete–steelinterfaces

Fatigue lifemonitoring

• Dynamic strain gauges • Total accumulated fatigue damage and hence,remaining fatigue life due to combined loadeffects

• Accumulated fatigue damage and henceremaining fatigue life estimation due toindividual load effects

(continued overleaf )


Table 1. (continued )

Monitoringcategory

Physicalquantity



Articulation monitoring • Dynamic strain gauges • Stress histories in bearings(c,e)

• Displacement transducers • Stress demand ratios in bearing• Bearing sensors(b) • Motion status in movement joints• Buffer sensors(b) • Stress and motion status in buffers(b)

GVW, gross vehicular weight; AW, axle weight; SFV, standard fatigue vehicle; SFA, standard fatigue axle.(a) HSWC.(b) SCB.(c) TMB.(d) KSMB.(e) TKB.

Anemometers (6)Accelerometers (19)Temperature sensors (115)Weldable strain gauges (110)Global positioning systems (14)Displacement transducers (2)Level sensing stations (10)Data-acquisition outstations (3)

Tsing Yi Tower

Man Wan Tower

Tsing YiAnchorage

Lantau Anchorage

Figure 3. Layout of sensory system and data-acquisition system in Tsing Ma Bridge.

design information and parameters for detection ofany significant deviation from design values; (ii)previous similar measured/derived values for detec-tion of any abnormal or adverse structural perfor-mance; and (iii) analytical results from numerical orphysical models for estimating the extent of damage,if any. Portable or removable servo-type accelerom-eters are also deployed with the main purposes of (i)calibration of the full three-dimensional finite elementmodel of the bridge and (ii) extraction of high-orderfrequencies and mode shapes from time history accel-eration data for facilitating future damage detection

works. The deployment of the measurement systemshould also be able to quantify the changing opera-tional and environmental conditions and to provideinformation for developing future loading predictionmodels.

2.2 Module 2—data acquisitionand transmission system (DATS)

The DATS is composed of four subsystems, namely,data-acquisition system (DAS), local cabling network


Anemometers (2)Accelerometers (3)Temperature sensors (224)Weldable strain gauges (30)Global positioning systems (6)Displacement transducers (2)Level sensing stations (5)Data-acquisition outstations (2)

Lantau Pylon

Ma Wan Pylon

Figure 4. Layout of sensory system and data-acquisition system in Kap Shui Mun Bridge.

Anemometers (7)Accelerometers (45)Temperature sensors (83)Weldable strain gauges (88)Global positioning systems (7)Displacement transducers (2)Data-acquisition outstations (3)Ting Kau Tower

Tsing Yi Tower

Central Tower

Figure 5. Layout of sensory system and data-acquisition system in Ting Kau Bridge.

system (LCNS), global cabling network system(GCNS), and commercial cabling network system(CCNS). The DAS is composed of fixed data-acquisition units (DAUs), portable DAUs, and digitalvideo converters (DVCs) for collection of respective

random and digital video signals. All DAUs andDVCs are PC-based equipment. The fixed DAUs andDVCs are permanently installed in the bridge deckand bridge towers for collection and processing of thesignals received from SS (excluding corrosion cells).


Anemometers (8)Accelerometers (44)Temperature sensors (118)Weldable strain gauges (212)Displacement transducers (4)Barometers (3), rainfall gauges (3) andHygrometers (3)Corrosion cells (24)Digital video cameras (6)Data-acquisition outstations (3)

Hong Kong

Shenzhen

Figure 6. Layout of sensory system and data-acquisition system in Hong Kong–Shenzhen Western Corridor (Hong Kongside cable-stayed bridge).

WIM

WIM

Anemometers (24)Fixed and removable accelerometers (58)Temperature sensors (388)Dynamic strain gauges (678)Static strain gauges (158)Global positioning systems (20)Displacement transducers (34)Buffer sensor (18)Bearing sensor (12)Tensile magnetic gauge (32)Barometers, rainfall gauges and hygrometers (28)Corrosion cells (33)Digital video cameras (18)Dynamic weigh-in-motion sensors (4)WIM

East Tower

West Tower

Figure 7. Layout of sensory system and data-acquisition system in Stonecutters Bridge.


Sensor-signalsSensor-signals

Dig

ital s

igna

lsD

igita

l sig

nals

Ana

log

sign

als

Ana

log

sign

als Dynamic

strain gaugesDynamic

strain gauges

Propeller-typeanemometers

Ultrasonic-typeanemometers

Global positioningsystems

Global positioningsystems

Displacementtransducers

Displacementtransducers

Light/currentconverter




InterfacingelectronicInterfacingelectronic

Fiber-optic network interfacingFiber-optic network interfacing

CopperCopper

wirewire

CopperCopper

wirewireFiber-optic cableFiber-optic cable Fiber-optic cableFiber-optic cable

PCI-controllerPCI-controller

Networkcard

Networkcard

Hard diskHard disk

Sensor-based for airconditioning controlSensor-based for airconditioning control

Typical data-acquisition unitTypical data-acquisition unit

Dig

ital i

nput

/out

put

card

Dig

ital i

nput

/out

put

card

Air temperaturecontroller

Air temperaturecontroller

Fault reportFault report

AccelerometersAccelerometers

Analog/digitalconverter

(simultaneously orsequentially)

Analog/digitalconverter

(simultaneously orsequentially)

Sig

nal c

ondi

tioni

ngS

igna

l con

ditio

ning

Interfacing cardInterfacing card

Inte

rfac

ing

med

iaIn

terf

acin

g m

edia

Staticstrain gauges

Staticstrain gauges

InclinometersInclinometers

Figure 8. Schematic layout of typical connection among DAU, SS, and GCNS.

The portable DAUs are used to collect signals fromportable servo-type accelerometers and corrosioncells during ambient vibration measurements and/orspecified field measurement works.

Figure 8 shows the schematic layout of a typicalconnection among SS, DAU, and GCNS (fiber-opticcable). The major components in the DAU are theperipheral components interconnect (PCI)-controller,the signal conditioning device, and the analog-to-digital converter, and the proper selection/designof these components are the key steps to obtainmeasurement data with high quality. The LCNS iscomposed of two local cabling networks, namely, thecopper cabling network for transmission of the signalsfrom SS (excluding global positioning systems anddigital video cameras, which are transmitted by fiber-optic cables) to DAUs for random signals and DVCsfor digital video signals, as shown in Figure 2.

The GCNS is composed of two backbone cablingnetworks, namely, the random signal transmissioncabling network for transmission of digitized signals(excluding digital video cameras) from individual

DAUs to DPCS-1 and the digital video signal trans-mission cabling network for transmission of digitalvideo signals from individual DVCs to DPCS-2. Bothbackbone cabling networks are ring-shaped single-mode fiber-optic cabling networks with a data trans-mission capacity of 1 Gbps.

The CCNS is the leased high-speed line with adata transmission rate of not less than 40 Mbps fordata communication (i) between the data-acquisitionoutstations in bridge site of HSWC and the bridgemonitoring room in West Control Building and(ii) between the bridge monitoring room in the TsingYi Administration Building at North Tsing Yi and thebridge monitoring room in West Control Building inSouth Tsing Yi (or Tsing Ma Control Area).

2.3 Module 3—data processingand control system (DPCS)

Figure 2 shows that the measured data collectedfrom module 1 are preprocessed and transmitted bymodule 2 to module 3 or DPCS, which is composed


of two high-performance servers, namely, DPCS-1and DPCS-2 for data processing and control ofrandom (digital) signals and video (digital) signals,respectively. The DPCS is devised to carry out fouroperational functions, namely, system control, systemoperation display, bridge operation display, and postprocessing and analysis of data. Figures 9 and 10illustrate the respective functions of DPCS-1 andDPCS-2 in block diagrams.

2.4 Module 4—structural healthevaluation system (SHES)

Figure 2 shows the comparison part on evaluationcriteria or the offtime structural health evaluation thatis devised to be taken up by the SHES or module 4,which is composed of two high-performance servers(one mainly for MSC and MATALB software toolsand the other mainly for ANSYS and MATALB

software tools) equipped with appropriate softwaretools to carry out the following operational functions:

• Finite element software interfacing capabilityThat is, finite element models built by MSC/PATRANcan be transferred to and executed in ANSYS soft-ware without any manual modifications, and viceversa.

• Integration of finite element models andmeasured dataThe automatic input of measured data into relevantfinite element models and under relevant (predefined)solvers for execution is therefore required.

• Analytical and experimental modal analysesThe automatic extractions and plots of the globaldynamic features of global bridge structural systemand local bridge components from the measuredtime history acceleration data are required. Figure 11

DAU1 to DAU8

Data-acquisition units

Glo

bal c

ablin

g ne

twor

k sy

stem

for

elec

trom

agne

tic s

igna

l tra

nsm

issi

on

System operation display

Postprocessing and analysis of data

DPCS-1

DPCS-2Data interfacing with:• Analyzed video data

HEDDB

CMDDB

NADDB

SADDB

MPDDB

Databases inSHDMS

DWIMS1 to DWIMS4

Dynamicweigh-in-motion stations

Data-acquisitionsystem for

random signals

Offi

ce e

ther

net

System controlSensor operation modesSampling rate adjustmentChannel mappingData transferTemporary data storage

Bridge operation displayEnvironmental loads and statusTraffic flows and loads statusKinematic quantitiesMonitoring criteria comparison

Environment loads and status derivationTraffic loads derivationBridge features extractionBridge responses derivation

Sensor operation statusDAUs operation statusNetwork operation statusData preprocessing activitiesData temporary storage statusFailure reports

Figure 9. Functional block diagram of DPCS-1—module 3 for random signals.


DVC1 to DVC8G

loba

l cab

ling

netw

ork

syst

em fo

r el

ectr

omag

netic

sig

nal t

rans

mis

sion

System operation displayCameras operation statusVideo converter operation statusNetwork operation statusVideo preprocessing activitiesVideo temporary storage statusFailure reports

Postprocessing and analysis of dataImage analysis of traffic characteristicsStatistical analysis of traffic flows and loadsInfluence analyses of traffic load-effectsDerivations of potential traffic load-effects

DPCS-2

DPCS-1Data interfacing with:

DWIM stationsDynamic strain gaugesGPS

HEDDB

CMDDB

NADDB

SADDB

MPDDB

Databases inSHDMS

Digital video converters

Offi

ce e

ther

net

System controlControl of cameras (P/T/Z)Channel mappingVideo transferTemporary video storage

Bridge operation displayEnvironmental loads and statusTraffic flows and load statusOver-weighed vehiclesSpeeding vehicles

Data-acquisitionsystem for digital

video signals

Figure 10. Functional block diagram of DPCS-2—module 3 for video signals.

Physicalbridge model

Measurementdata in SHDMS

Finite element analysisdata in SHDMS

Finite elementmodel

Transformation/mapping

Analyzedstatic data

Measuredstatic data

Analyzedvibration mode

shapes

Derivedexternal forces

Frequencyresponsefunctions

Measuredvibration

mode shapes

Measuredexternalforces

Frequencyresponsefunctions

Static parameters correlation

Update stiffness (K)

Undamped modal parameterscorrelation

Damped modal parameterscorrelation

External forces correlation

Update stiffness (K), mass (M)

Update stiffness (K), mass (M),damping ratio (C)

Identify external forces (F )

Synthesis Synthesis

Solver

Sol

ver

Mod

al s

uper

posi

tion

Modal analysis and modelupdating in SHES

Figure 11. Modal analysis and model updating in SHES by interfacing with SHDMS.


shows the typical modal analysis and model updatingworks in SHES by interfacing with SHDMS.

• Structural diagnosis modeling analysesFor any key structural component or location witha measured and/or derived stress and/or displace-ment that exceeds 60–75% of its predefined moni-toring criteria, structural diagnosis or assessmentof the current state of the bridge structure andits history will be carried out in order to assessany adverse effects on the global structural systembased on the current and historical environmental,and operational loading conditions. For the sakeof facilitating such assessments, it is required toperform automatic execution of finite element anal-yses on those prebuilt models and under predefinedtypical types of structural analysis such as geometricnonlinear analysis of traffic and temperature loads,random response analysis of dynamic wind seismicloads, etc.

• Structural prognosis modeling analysesThe aim of structural prognosis is to assess theability of the bridge structural system to carryout future loading conditions (derived on the basisof past and current measured loads) or extremeevents. The applications of structural prognosis inWASHMS are (i) to predict/assess the remainingfatigue life of structural steel components based ona combination of finite element analyzed results,BS5400: Part 10: fatigue assessment rules, andmeasured strain results from WASHMS [12]; (ii) toinvestigate the different types of potential failuremodes and the associated predictable and unpre-dictable loading conditions that cause damage andsubsequent failure; (iii) to determine the potentialconsequences of each failure event or multipleevents acting simultaneously; and (iv) to facilitate theplanning of scheduled inspection and maintenanceactivities.

• Visualization of analyzed resultsIn order to increase the efficiency and accuracy inidentification and quantification of abnormal featuresor defects, all the analyzed, measured, and derivedresults are presented in comparative plots (withanimation, where necessary) and tabulated in thematrix form.

The execution of the above operational func-tions requires the development of a customizedfinite element interfacing software system (FEISS)to manipulate the operation of different softwaretools (including both finite element analysis toolsand random data processing and analysis tools)under different hardware and software operating plat-forms. The FEISS is composed of five modules,i.e., modules A, B, C, D, and E, as shown inFigure 12. Module A includes the prebuilt finiteelement models of (i) full 3D global bridge model,(ii) full 3D local foundation bridge model, (iii) 3Dglobal spine-beam or gird-beam bridge model, and(iv) full 3D local segmental bridge models. Module Bincludes the preconfigured finite element analysistypes such as normal mode analysis, linear static anal-ysis (influence coefficients’ determination), nonlinearstatic analysis, random response analysis (buffetingand seismic responses determination), fatigue anal-ysis, and impacting analysis. Module C includes thefinite element and statistics solvers such as MSC-NASTRAN, ANSYS-Vertical Physics, MATLAB dataanalysis suite, etc. Module D includes post-postingand display software for generation of analyzedresults and reports. Module E includes the inter-facing and control software for the execution of(i) automatic/manual retrieval of measured/analyzeddata from the relevant database in module 5 to module4 for processing/analysis; (ii) automatic/manual inp-utting of the retrieved data into relevant prebuiltfinite element or statistical model/models for prede-fined types of finite element or statistics analysis;and (iii) automatic/manual display and storage of theanalyzed results.

2.5 Module 5—structural health datamanagement system (SHDMS)

The SHDMS is composed of a high-performanceserver equipped with data management software, andis the interfacing platform for the interoperability ofdata and information so that the efficiency of fusionof data and information for decision making can besignificantly enhanced.

The following five major databases are devised tobe executed in the SHDMS for interfacing works:


Measured and processeddata database (MPDDB)

SHDMS(under the control of a RDBMS

and MSC simmanager)

Statistical analyzeddata database (DADDB)

Numerical analyzeddata database (NADDB)

Computer modelingdata database (CMDDB)

Health evaluationdata database (HEDDB)

Finite element interfacing software system or FEISSin SHES (i.e., SHES-1 and SHES-2)

Module APre-built finite

element models

Module BPreconfiguredfinite elementanalysis types

Module CAutomatic settingand execution of

appropriateanalysis Solver

Module EFinite element

interface and control

Module DAutomatic processing,analysis and display of

analyzed results

JAVA environment

Figure 12. Layout of FEISS in SHES and its interfacing with the databases in SHDMS.

• Measured and processed data database(MPDDB)All time-series data obtained from measuring sensors.

• Statistical analyzed data database (SADDB)All data generated from signal/data processing andanalysis software tools such as MATLAB—data anal-ysis suite, NI—data processing and reporting, SDtools, etc.

• Numerical analyzed data database (NADDB)All finite element analyzed/output data generatedfrom finite element analysis software tools such asMSC-NASTRAN, ANSYS-Vertical Physics, MIDAS,LUSAS, etc.

• Computational modeling data database(CMDDB)All finite element modeling/input data generated fromfinite element analysis tools such as MSC-PATRAN,ANSYS-Preprocessor, ANSYS-Workbench, etc.

• Health evaluation data database (HEDDB)All updated structural health monitoring and evalu-ation criteria and concise monitoring and evaluationresults of environmental loads and status, traffic loads,bridge features, and bridge responses.

These five databases are manipulated and managedby a data warehouse system, which is customizedbasing on “IBM DB2 UDB Warehouse Enterprise”,and is equipped with data management and data anal-ysis tools for integrating enterprise-wide corporatedata into a single repository from which users orengineers can easily run queries, perform analysis,and produce reports. The data warehousing systemin SHDMS is devised to carry out the followingfunctions:

1. Systematic cleansing, reconciliation, derivation,matching, standardization, transformation, andconformity of data and information from all datasource systems such as DPCS servers and SHESservers as shown in Figure 13.


DPCS-1(LFC)

DPCS-1(TKB)

DPCS-1(SWC)

DPCS-1(SCB)

DPCS-2(SCB)

DPCS-2(SWC)

Internal

External

Others

Data sourcesystems

Extract

Data storage• Relational• Fast

Processing• Clean• Reconcile• Derive• Match

- Combine- Remove dups

• Standardize• Transform• Conform

- DimensionsExport todata warehouse

Data staging area(operational data

store)

Ad hoc querytools

Report writersEnd usersapplications

Statisticalmodeling tools

Numericalmodeling tools

FEMinterfacingtools

OLAP toolsData miningtools

Visualizationtools

Data and metadatastorage area

End-userpresentation

tools

Health evaluationdata database (HEDDB)

Computational modelsdata database (CMDDB)

Numerical analyzeddata database (NADDB)

Statistical analyzeddata database (SADDB)

Measured and processeddata database (MPDDB)

Enterprisedata warehouse

Feed and load

Summarized data(multidimensional database)

Cleaneddimension

data

SHDMS server

End-usersSHDMSworkstationsSHES serversSHESworkstationsOther servers andworkstations

Summarized data(relational database)

Load

LoadExtract

Extract

Extract

Extract

Extract

Extract

•

Feed and load

Feed and load

Feed and load

Figure 13. Architectural layout of SHDMS and its interfaces.

2. Manipulation of all types of correlation analysesand features extraction plots, by online analyticalprocessing tools and appropriate data miningtools, based on all data and information generatedfrom the software tools in DPCS-servers andEnd-users’ servers and workstations as shown inFigure 13.

3. Creation of data marts (summarized data inFigure 13), based on the results of afore-mentioned correlation analyses and plots, forthe execution of the following monitoring andevaluation works:

(a) reporting the current and future loadingconditions (such as wind, temperature,seismic, and traffic) acting on the bridge;

(b) reporting the current and future corrosionstatus on specified bridge components;

(c) reporting the current and future structuralhealth conditions of the bridge in termsof the physical parameters as listed in thefourth column of Table 1;

(d) planning of scheduled bridge inspection andmaintenance activities with bridge mainte-nance team; and

(e) updating/calibrating the bridge rating sys-tem and computational (numerical and stat-istical) models for processing and analysisof data and information, where necessary.

4. Forming the center of data interrogation and met-amodeling for bridge health diagnosis and prog-nosis through the integration of data and informa-tion from both measurement and computationalsystems. (Metamodels refer to the functionalforms of statistical-based models, finite elementmodels, neural networks, etc.)

2.6 Module 6—inspection andmaintenance system (IMS)

The IMS is composed of two notebook computers(IMS-1 and IMS-2) and a tool-box (IMS-3). Its


function is devised to carry out inspection and main-tenance works on SSs, DAUs, display facilities,LCNSs, and GCNSs. All information (drawings andrecords) regarding system design, system installation,system operation, and system maintenance is storedand operated in IMS-1 and IMS-2. The IMS-3 is atool-box for carrying out inspection and minor reme-dial works.

3 OPERATION OF WASHMS

The system operation block diagram of WASHMS isshown in Figure 14, where the monitoring of kine-matic quantities refers to the monitoring of bridgefeatures and bridge responses. The figure showstwo levels of monitoring, namely, the sensor-basedcomparison of the measured results and the moni-toring criteria, and the model-based comparison of thederived results and the evaluation criteria. The former

refers to the comparison of the measured resultswith the predetermined monitoring criteria (i.e., atabout 60–75% of the design values at serviceabilitylimit state), whereas the latter refers to the compar-ison of the derived results with the evaluated criteria(i.e., at 100% of the design values at serviceabilitylimit state). The criteria for monitoring and evalu-ation are defined and calibrated in accordance withthe updated requirements of the damage types asdefined in the criticality and vulnerability ratings, i.e.,structural damage (due to structural actions), envi-ronmental damage (corrosion), accidental damage,and wearing damage [13]. In Figure 14, it is shownthat if the measured results exceed the monitoringcriteria, structural diagnosis and prognosis works willbe carried out. Both the structural diagnosis modelsand structural prognosis models are finite-element-based and/or empirical/statistical-based models, ofwhich the former is used to assess the current and/orhistorical state of the global bridge structural system

Environmental loadsand status monitoring

Traffic loadsmonitoring

Kinematic quantitiesmonitoring

Future environmentalloads and status models

Structural diagnosisand prognosis models

Future trafficloads models

Initiating/checkinganalytical and/orempirical models

Updated/calibratedanalytical and/orempirical models

Real-time structuralhealth monitoring

System information:Structural characterizationBridge performance recordsBridge maintenance records

Measuredresults—monitoring criteria

comparison

No exceedance

Exceedance

Derivedresults—evaluation criteria

comparison

Estimations of:Remaining service lifeTime to failureTime to maintenance

No exceedance

Decision for actions:Carry out detailed inspection of suspected componentsInvestigate causes of defects and estimate time to maintenanceDetermine scope of maintenance works, if required

Exceedance

Tak

e ac

tion,

upd

ate

syst

em a

nd c

ontin

ue th

e pr

oces

s

Offtime structuralhealth evaluation

Updating, if any

Bridge inspection andmaintenance team

Updating, if any

Figure 14. System operation block diagram of WASHMS.


and/or local structural components whereas the latteris used to predict the consequences under the assumedfuture operational and environmental loads and status.

4 CONCLUSIONS

This article has described a modular architecture thathas been used in the design of SHMS for cable-supported bridges in Hong Kong. The architectureof the SHMS described consists of six integratedmodules, namely, SS, DATS, DPCS, SHES, SHDMS,and IMS. Each module is well defined and encapsu-lated. In order to ensure the reliability of measuredresults, different types of sensors should be deployedat the same key locations and/or components wherelarge displacements and stresses are expected to occurso that the measured results can be validated throughcorrelation among themselves.

Since the hardware configuration of the DAShas a significant influence on data quality, theperformance requirements on the linearity, temper-ature drift, accuracy, direct current resolution, band-width, etc., of the signal conditioning and the data-acquisition device should be identified and quantified.Appropriate customized software systems should alsobe developed and configured to process or derive themeasured data in the data formats applicable to bridgehealth monitoring and evaluation.

Structural health monitoring and evaluation worksshould be executed through the correlation analysesand features extractions of (i) measured and analyzedresults, (ii) current and previous measured results,(iii) previous and updated analyzed results, (iv) andderived results (from analysis and/or measurements)and assigned bridge performance criteria. As thecorrelation analyses and features extractions involvethe synchronized processing of two or more datafiles/sets, the use of data warehouse system equippedwith online analytical processing tools and appro-priate data mining tools will facilitate the automaticexecution of such synchronized data processing andanalysis works.

It is concluded that the WASHMS for cable-supported bridges should at least be able to monitorthe loading and structural parameters set by the bridgedesigner so that the bridge performance under currentand future loading conditions can be evaluated, andsuch evaluated results should be able to facilitate the

planning of bridge inspection activities, and be ableto determine not only the cause of the damage butalso the extent of remedial work, once the damage isidentified.

REFERENCES[1] Highways Department, Wind and Structural Health

Monitoring System, Particular Specification for theElectrical and Mechanical Services in Lantau FixedCrossing, Highway Contract No. HY/93/09, 1993.

[2] Highways Department, Wind and Structural HealthMonitoring System, Particular Specification for theConstruction of Ting Kau Bridge and ApproachViaduct, Highway Contract No. HY/93/38, 1993.

[3] Highways Department, Wind and Structural HealthMonitoring System for Lantau Fixed Crossing andTing Kau Bridge, Consultancy Agreement No. CE75/94, 1997.

[4] Wong KY, The wind and structural health monitoringsystem (WASHMS) for cable-supported bridgesin Tsing Ma Control Area. an invited paper,Proceedings of the IFAC Conference on NewTechnology for Computer Control. Hong Kong, 2001.

[5] Highways Department, Wind and Structural HealthMonitoring System, Appendix W of the Partic-ular Specification for the Construction of HongKong—Shenzhen Western Corridor, HighwayContract No. HY/2002/21, 2002.

[6] Highways Department, Wind and Structural HealthMonitoring System, Section 33 of the ParticularSpecification for the Construction of StonecuttersBridge, Highway Contract No. HY/2002/26, 2002.

[7] Dong X, Zhang Y, Xu H, Ni YQ. Research anddesign of structural health monitoring systemfor the Sutong Bridge. In Structural HealthMonitoring 2005: Advancements and Challengesfor Implementation, Chang F-K (ed). DEStechPublications: Lancaster, PA, 2005, pp. 1736–1742.

[8] Sun L, Dan D, Sun Z, Health monitoring systemfor Donghai Bridge in Shanghai, Proceedings ofthe Asia-Pacific Workshop on Structural HealthMonitoring. Yokohama, Japan, 2006.

[9] Wong KY. Instrumentation and health monitoringof cable-supported bridges. Journal of StructuralControl and Health Monitoring 2004 11:91–124.

[10] Wong KY, Recent development of structural healthmonitoring system. a keynote paper, Proceedingsof the International Workshop on Integrated Life-Cycle Management of Infrastructure, The Hong Kong


University of Science and Technology: Hong Kong,September 2004.

[11] Wong KY. Design of a structural health monitoringsystem for long-span bridges. Structure andInfrastructure Engineering 2007 3:169–185.

[12] Wong KY, Stress and traffic loads monitoring ofTsing Ma Bridge. China Bridge Congress 2007,

28–30 March. Chongqing, 2007, organized byMerisis.

[13] Wong KY, Criticality and vulnerability analysis ofTsing Ma Bridge, Proceedings of the InternationalBridge Conference on Bridge Engineering. TheHong Kong Institution of Engineers: Hong Kong,November 2006.

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