Hig

1 D

ABST

warnin

health

not pu

found

Test S

The m

contin

traffic

the hi

there a

Fig

An SH

(DYB

establ

Figure

SHM

The h

load c

the rig

gh-speed Ra

Dept. of Civil Eng

3 Key Laborat

TRACT: This

ng method of

h monitoring (

ublished form

d in the previou

Structure and

monitoring ob

nuous rigid ar

c was opened

ghest loading

are three rows

gure 1: Nanjing

HM system, w

B in Figure 2)

ished for the

es 1~2 [1]. He

Methodology

anger’s vibrat

cases) were me

gid hanger’s d

Collectio

ailway Brid

Yonghui An

gineering, Dalian2

Dept. of Civi

tory of C&PC Str4

Dept. of Civi

case report su

hanger anoma

(SHM) system

mally here, it i

us work [1-2].

d Measured D

bject, Nanjin

rch bridge wit

in the year of

capacity and

s of hangers in

g Dashengguan

which contains

), velocity sen

long-term m

ere 11# hanger

y and Results

tion responses

easured from

dynamic perfor

on of SHM Cas

dge MonitoYangtze

n*1, Delong Gu

n Univ. of Techno

il Engineering, D

ructures of the M

il Engineering, D

ummarizes the

alies based on

m installed on

s a summary

.

Data

ng Dashenggu

th the design

f 2011; this br

longest main

n the bridge, an

Yangtze river b

temperature s

nsors (ZD in

monitoring of t

r is the middle

s

and their infl

the SHM syst

rmance in rea

se Studies by A

oring Casee River Briuan2, Youlian

ology, Dalian, Ch

Dalian Univ. of Te

Ministry of Educati

Dalian Univ. of Te

e rigid hanger

n long-term mo

a high-speed r

of the author

uan Yangtze

speed of 300

ridge is the fir

n span of 336m

nd each row o

bridge Figur

sensors (GWD

Figure 2), an

the bridge. T

e one in the mi

uence factors

tem. The objec

l environment

ASCE SEI Meth

e Report: Nidge

ng Ding3, Jinp

hina. *Correspond

echnology, Dalian

tion, Southeast Un

echnology, Dalian

r’ dynamic cha

onitoring data

railway bridge

rs’ previous st

River Bridge

0 km/h, as illu

rst six-track ra

m in the world

owns 21 hange

re 2: Sensor lay

D in Figure 2),

nd accelerome

The detailed se

iddle row of th

(including en

ctive of this st

t and to propo

hods of Monito

Nanjing Da

ping Ou4

ding author: anyh

n, China. University, Nanjing

n, China.

aracteristics an

a collected from

e. The present

tudies and the

e, is a high-

ustrated in Fig

ailway arch br

d. As shown i

ers in a main s

yout diagram in

, steel dynami

eters (JSD in

ensor layout

he left main sp

nvironmental f

tudy is to help

ose a fast warn

oring Committe

ashengguan

h@dlut.edu.cn

g, China.

nalysis and fa

m the structur

t short report

e details can b

-speed railwa

gure 1 [1]. Th

ridge and it ha

in Figure 2 [1

span.

n section #11

ic strain senso

Figure 2), wa

is described i

pan.

factors and trai

p understandin

ning method fo

ee

n

ast

ral

is

be

ay

he

as

1],

rs

as

in

in

ng

for

 

hange

factor

Firstly

which

param

two st

the ha

Dynam

With t

(Figur

case

param

displa

load f

in eac

and

obviou

Corre

longit

displa

transv

each

Influe

carria

param

are

tempe

influe

transv

From

the

transv

invers

The ha

In abo

studie

found

case 3

train-i

exclud

er anomalies. T

rs and the esta

y, several dyn

h have influen

meters and the

tudies have be

anger’s referen

mic character

the train load

re 3 [2]) of 11

is an importa

meters [2],

acement amp

factor and vib

ch load case i

transverse

us probabilist

lations betwe

tudinal/transve

acement and

verse dynamic

load case

ences of the

ge number on

meters and the

analyzed.

erature is f

nce factor

verse dynam

Figure 4 [1]

train-induced

verse dynamic

se correlations

anger’s refere

ove analysis,

ed, and the co

d. Then, the ha

3 for example

induced TDD

de the effect

Collectio

Therefore, the

ablishment of

namic paramet

ces on dynam

e influence fac

een finished: t

nce service con

istics analysis

cases classifi

# hanger’s (Fi

ant factor for

i.e. dyn

plitude, dyn

bration ampli

in the longitu

directions

tic characteri

een the han

erse dyn

the main gir

c displaceme

are investig

carriageway

n the hanger’s

eir statistical t

Moreover,

found to be

for han

mic displacem

it can be seen

d 11# han

displacement

s with the temp

nce service co

the influence

orrelation betw

anger’s referen

e, the basic p

DCA and influ

of influence

on of SHM Cas

e hanger’s dyn

hanger’s refe

ters which are

mic parameters

ctors are extra

the characteris

ndition databa

s: transverse d

cation, Ding e

igure 1) transv

r hanger’s dy

namic

namic

itude,

udinal

have

stics.

nger’s

namic

rder’s

nt in

gated.

y and

three

trends

the

e an

nger’s

ment.

n that

nger’s

t changes amp

perature.

ondition datab

e of train load

ween the temp

nce service co

procedures can

uence factors

factors; (3)

Figu

hang

eight

Figur

hang

se Studies by A

namic charact

erence service

e important fo

s, are selected

acted based o

stics of differe

ase is establish

dynamic displa

et al. [2] obtai

verse dynami

ynamic chara

plitudes (TDD

base and fast w

d cases on ha

perature and t

ondition datab

n be summar

when the br

obtain the ha

re 3: Probabi

ger’s transverse

t train load case

re 4: Correlat

ger’s train-induc

ASCE SEI Meth

teristics analy

condition dat

or structural p

in this study.

on the long-ter

ent dynamic p

hed for fast wa

acement

ined the prob

ic displaceme

acterisitics. Th

DCA) in all the

warning for an

anger’s dynam

train induced

ase can be est

rized as follow

ridge is in no

anger’s refere

ility density f

e dynamic dis

es 

tion between t

ced TDDCA for

hods of Monito

ysis under diff

tabase have b

performance,

Then, the han

rm monitorin

parameters are

arning of hang

ability densit

ent amplitude

he hanger’s

e eight train lo

nomalies

mic character

hanger’s TD

tablished [1].

ws: (1) extrac

ormal service

ence displacem

fitting curves

splacement amp

the temperatur

r eight train loa

oring Committe

ferent influenc

been conducte

and the facto

nger’s dynam

g data. Finall

e analyzed, an

ger anomalies.

ty distribution

e. The train loa

three vibratio

oad cases sho

ristics has bee

DDCA has bee

Take train loa

ct the hanger

condition; (2

ment conditio

of the 11#

plitudes for

re and the

ad cases 

ee

ce

d.

rs

mic

ly,

nd

.

ns

ad

on

w

en

en

ad

r’s

2)

on

 

databa

condit

fast.

Figure

and co

and th

Lesso

In the

lesson

(1) T

tempe

consid

a good

(2) Af

of fiel

memb

fast w

Ackn

The a

Scienc

(2015

author

Refer

[1] A

H

P

[2] D

h

ase in differen

tion database

e 5: Reference s

orrelation betwe

he warning thres

ons Learned

case report o

ns are learned

he dynamic

erature; the inf

der the influen

d foundation f

fter the establi

ld monitoring

ber can be con

warning of othe

owledgement

authors would

ce Foundation

CB060000),

rs would like t

rences

An Y. H., Gua

High-Speed R

Performance o

Ding, Y. L., A

high-speed rai

Collectio

nt environmen

and the warni

service conditio

een the temper

shold after rem

of the rigid han

and concluded

performance

fluences are an

nces in order t

for the further

ishment of a b

data collecte

nducted. The f

er members in

ts

d like to expr

n of China (

and the Natio

to thank the br

an D. L., Din

Railway Arch

of Constructed

An, Y. H., and W

ilway steel arc

on of SHM Cas

ntal conditions

ing threshold l

on sub-database

ature and the h

moving the trend

nger’s dynami

d:

of hangers i

nalyzed and th

to obtain accu

analysis of tra

bridge member

d in the norm

fast warning m

n high-speed ra

ress their grat

(51508070), t

onal Natural

ridge owner an

ng Y. L., and O

Bridge Usin

d Facilities, 20

Wang, C., Fie

ch bridge. Sma

se Studies by A

s and train loa

line (Figure 5

e of the hanger

hanger’s train-i

d.

ic performanc

is influenced

hey have differ

urate structural

ain-induced ha

r’s reference s

mal service sta

method for rig

ailway bridges

titude for fina

the National

Science Foun

nd manager fo

Ou J. P., Fast

ng Long-Term

17, 31(6): 040

ld monitoring

art Structures

ASCE SEI Meth

ad cases. Base

[1]), the hang

r’s TDDCA in t

induced TDDC

ce analysis and

obviously by

rent statistical

l dynamic ana

anger vibratio

service condit

atus, fast warn

gid hangers [1

s.

ancial support

Key Basic R

undation of C

or the support

t Warning Me

m Monitoring

017103.

g of the train-in

and Systems,

hods of Monito

ed on the han

ger anomalies

(a)

(b)

rain Load Case

CA; (b) the refer

d anomalies w

y train load

l properties. It

alysis results.

on and control.

tion database b

ning for the an

1] can be simi

t from the N

Research Prog

China (517781

throughout th

ethod for Rigid

g Data. ASC

nduced hange

2016, 17(6):

oring Committe

nger’s referenc

s can be warne

e 3: (a) the tren

rence correlatio

warning, sever

cases and th

t is necessary t

This study lay

.

based on plent

nomalies of th

larly applied i

National Natur

gram of Chin

106). Also, th

he research.

d Hangers in

CE Journal o

er vibration in

1107-1127.

ee

ce

ed

nd

on

ral

he

to

ys

ty

he

in

ral

na

he

a

of

a