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Frontiers of Structural and Civil Engineering

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Front. Struct. Civ. Eng.    2019, Vol. 13 Issue (3) : 569-604    https://doi.org/10.1007/s11709-018-0498-y
RESEARCH ARTICLE
Frontier of continuous structural health monitoring system for short & medium span bridges and condition assessment
Ayaho MIYAMOTO1(), Risto KIVILUOMA1, Akito YABE2
1. Department of Civil Engineering, Aalto University, Aalto, Finland
2. Sustainable Solutions Dept., KOZO KEIKAKU Eng. Inc., Tokyo, Japan
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Abstract

It is becoming an important social problem to make maintenance and rehabilitation of existing short and medium span(10-20 m) bridges because there are a huge amount of short and medium span bridges in service in the world. The kernel of such bridge management is to develop a method of safety(condition) assessment on items which include remaining life and load carrying capacity. Bridge health monitoring using information technology and sensors is capable of providing more accurate knowledge of bridge performance than traditional strategies. The aim of this paper is to introduce a state-of-the-art on not only a rational bridge health monitoring system incorporating with the information and communication technologies for lifetime management of existing short and medium span bridges but also a continuous data collecting system designed for bridge health monitoring of mainly short and medium span bridges. In this paper, although there are some useful monitoring methods for short and medium span bridges based on the qualitative or quantitative information, mainly two advanced structural health monitoring systems are described to review and analyse the potential of utilizing the long term health monitoring in safety assessment and management issues for short and medium span bridge. The first is a special designed mobile in-situ loading device(vehicle) for short and medium span road bridges to assess the structural safety(performance) and derive optimal strategies for maintenance using reliability based method. The second is a long term health monitoring method by using the public buses as part of a public transit system (called bus monitoring system) to be applied mainly to short and medium span bridges, along with safety indices, namely, “characteristic deflection” which is relatively free from the influence of dynamic disturbances due to such factors as the roughness of the road surface, and a structural anomaly parameter.
Keywords condition assessment      short & medium span bridge      structural health monitoring(SHM)      long-term data collection      system      maintenance      bridge performance      information technology      loading vehicle(public bus)      in-situ loading     
Corresponding Author(s): Ayaho MIYAMOTO   
Online First Date: 10 July 2018    Issue Date: 05 June 2019
 Cite this article:   
Ayaho MIYAMOTO,Risto KIVILUOMA,Akito YABE. Frontier of continuous structural health monitoring system for short & medium span bridges and condition assessment[J]. Front. Struct. Civ. Eng., 2019, 13(3): 569-604.
 URL:  
https://academic.hep.com.cn/fsce/EN/10.1007/s11709-018-0498-y
https://academic.hep.com.cn/fsce/EN/Y2019/V13/I3/569
Fig.1  Basic components of a typical SHM system [8]
Fig.2  Basic elements of BELFA in working position [4]
Length in transportation mode: 22.5 m
Max. length in working position: 35.5 m
Max. distance between supports 18.0 m
Total weight approx. 84.5 t
Max. test load (without additional dead freight) approx. 750 kN
Max. permissible test load 1500 kN
Tab.1  Essential data of BELFA [4]
Fig.3  (a) Arrival of BELFA in transportation mode [4]; (b) Crossing the bridge placing BELFA [4]; (c) BELFA in operation mode, supported at both bridge bearings [4]
Fig.4  View of in-situ loading test by BELFA for an existing bridge [4]
Fig.5  Cross section of a target bridge, BS-bridge (midspan) [4], unit: m
Fig.6  An example of load deflection curves at midspan by BELFA under four various conditions [4]
Fig.7  Side view and midspan cross section of short span bridge, MO-bridge [4], unit: m
Fig.8  View of in-situ monitoring by BELFA for short span bridge in rural area [4]
Fig.9  Reduction path of safety level and coverage of proposed system
Fig.10  Concept of the bus monitoring system
Fig.11  Analysis flow for bus monitoring system
Fig.12  Simple spring-mass model of the bridge-vehicle interaction system
Fig.13  Input to the vehicle system and over-spring and under-spring deformations
Fig.14  Over-spring/under-spring/bridge substructuring scheme
Fig.15  “Characteristic deflection” calculation flow
Fig.16  Examples of characteristic waveforms of estimated deflection
Fig.17  Example of determination of acceleration data extraction range
Fig.18  Example of estimation of deflection
Fig.19  Number of bridges managed by Ube-city located on bus routes run by Ube-city Transportation Bureau(UTB)
Fig.20  Percentage of bridges 50 years or older in all bridges in Ube-city 20 years from now
Fig.21  General views of Ube-city bus route bridges selected for long-term monitoring. (a) Shingondai Bridge (single-span bridge); (b) Shiratsuchi Daini Bridge (two-span bridge); (c) Jase Bridge (five-span bridge)
bridge name completed in type of superstructure span length (m) bridge length (m)
Jase Bridge 1976 span No. start point side 1 prestressed concrete slab bridge (pretensioned slab) 18.0 85.0
2 prestressed concrete slab bridge (pretensioned slab) 16.0
3 prestressed concrete slab bridge (pretensioned slab) 18.0
4 prestressed concrete slab bridge (pretensioned slab) 14.0
end point side 5 prestressed concrete slab bridge (pretensioned slab) 19.0
Shiratsuchi Daini Bridge 1933 (estimated) span No. start point side 1 reinforced concrete (T-girder) 7.0 15.0
end point side 2 reinforced concrete (T-girder) 7.0
Shingondai Bridge June 1998 single-span prestressed concrete girder bridge (Bi-prestressing method) 22.4 23.6
Tab.2  Data on bridges selected for long-term monitoring
item specifications
net vehicle weight 8,130 kg
gross vehicle weight 11,485 kg
front axle weight 2,730 kg
rear axle weight 5,400 kg
wheel base 4.4 m
Tab.3  Specifications of bus (vehicle) used for long-term monitoring
name: Fuji Ceramics SA11ZSC-TI(Three-axis piezoelectric acceleration transducer with built-in amplifier)
charge sensitivity 1 mV/m/s2
frequency range 1–8000 Hz
resonant frequency 35 kHz or higher
maximum measurable acceleration 4000 m/s2
maximum allowable acceleration 30000 m/s2 or higher
power supply for built-in amplifier 21–24 V/0.5–10 mA
temperature range −50 ~ +110 °C
dimensions 14.2 mm × 14.2 mm × 14.2 mm
mass Approx. 11.1 g
Tab.4  Specifications of three-axis acceleration sensor used for long-term monitoring (vehicle side)
Fig.22  General view of the bus (vehicle) used for the Bus Monitoring System
Fig.23  Installation of acceleration sensor to the bus (vehicle). (a) Acceleration sensor installed to the rear wheel of the bus; (b) Wiring routed into the bus
Fig.24  Configuration of the on-board measurement system of the Bus Monitoring System
Fig.25  Measurement in progress in the bus and the measuring equipment used (in the back of the bus)
Fig.26  Acceleration sensor location at the bridge and the route and direction of movement of the bus
Fig.27  Example of acceleration response waveform in the midspan zone of the bridge
Fig.28  Comparison between midspan acceleration response waveform and rear-wheel-under-spring acceleration response waveform and results of FSWT based time–frequency space analysis. (a) Comparison of girder-midspan and under-rear-wheel-spring acceleration responses; (b) Results of FSWT based time- -frequency space analysis of bridge acceleration response waveform
Fig.29  Differences in standard deviation of characteristic deflection among data sections (Shingondai Bridge: Tokonami → Nishikiwa (direction of vehicle movement))
Fig.30  Examples of measured values of characteristic deflection and simple moving averages
structural soundness of bridge decrease in prestressing force ratio of geometrical moment of inertia relative to 0% reduction ratio of characteristic deflection relative to 0% reduction
sound 0% 1.0 1.0
deterioration Phase 1 50% 0.52 1.93
deterioration Phase 2 90% 0.35 2.86
Tab.5  Serious deterioration (damage) of “Shingondai Bridge (PC girder bridge)” used in vehicle-induced vibration simulation and changes in characteristic deflection
Fig.31  Example of changes in characteristic deflection from 2010 to 2013 (Shingondai Bridge) and comparison with the serious deterioration (damage) criteria (calculated values) shown in Table 5. (a) Tokonami→Nishikiwa Gakkomae; (b) Nishikiwa Gakkomae →Tokonami
bridge name speed (km/h) rainfall(mm) temperature(°C) oncoming traffic (vehicles) number of persons on vehicle (persons)
Shingondai Bridge 40–50 0 20–30 0 5–15
Shiratsuchi Daini Bridge 40–50 0 20–30 0 5–15
Jase Bridge 45–55 0 20–30 0–1 no restriction
Tab.6  Conditions (data restrictions) for correlation coefficient calculation by bridge
bridge name direction of movement span speed rainfall temperature
? Toko → Nishi – −0.162 0.240 0.135
Shingondai Bridge little correlation weak positive correlation little correlation
Nishi → Toko – −0.257 0.151 −0.337
weak negative correlation little correlation weak negative correlation
Shiratsuchi Daini Bridge Nishi → Yoshi A −0.014 −0.095 0.005
little correlation little correlation little correlation
B 0.022 −0.201 −0.182
weak positive correlation weak negative correlation little correlation
Yoshi → Nishi B −0.434 0.317 −0.507
Negative correlation weak positive correlation Negative correlation
A –−0.058 −0.008 −0.136
little correlation little correlation little correlation
Jase Bridge Sho → Kin A −0.192 0.091 0.004
little correlation little correlation little correlation
B 0.026 0.117 0.071
little correlation little correlation little correlation
C 0.087 −0.005 −0.044
little correlation little correlation little correlation
D 0.159 0.124 0.206
little correlation little correlation weak positive correlation
E 0.095 0.062 0.186
little correlation little correlation little correlation
Kin → Sho E −0.270 −0.117 −0.135
weak negative correlation little correlation little correlation
D 0.161 −0.234 0.088
little correlation weak negative correlation little correlation
C −0.348 0.046 −0.144
weak negative correlation little correlation little correlation
B 0.332 0.053 0.309
weak positive correlation little correlation weak positive correlation
A −0.328 0.156 0.052
weak negative correlation little correlation little correlation
Tab.7  Correlations between characteristic deflection and bus operating conditions by bridge (correlation with vehicle speed/rainfall/temperature)
bridge name direction of movement span oncoming traffic number of persons on bus
? Toko → Nishi – −0.059 0.205
Shingondai Bridge little correlation weak positive correlation
Nishi → Toko –– −0.150 −0.101
little correlation little correlation
Shiratsuchi Daini Bridge Nishi → Yoshi A 0.124 −0.097
little correlation little correlation
B 0.222 0.044
weak positive correlation little correlation
Yoshi → Nishi B −0.217 −0.152
weak negative correlation little correlation
A 0.148 −0.011
little correlation little correlation
Jase Bridge Sho → Kin A 0.099 0.263
little correlation weak positive correlation
B −0.266 −0.270
weak negative correlation weak negative correlation
C 0.024 0.018
little correlation little correlation
D 0.328 0.081
weak positive correlation little correlation
E 0.308 0.031
weak positive correlation little correlation
Kin → Sho E 0.013 −0.044
little correlation little correlation
D 0.088 0.469
little correlation positive correlation
C 0.036 −0.322
little correlation weak negative correlation
B −0.009 0.366
little correlation positive correlation
A – 0.184 −0.030
little correlation little correlation
Tab.8  Correlations between characteristic deflection and bus operating conditions by bridge (correlation with number of oncoming vehicles/number of persons on bus)
coefficient of correlation correlation
0.0 –±0.2 little correlation
±0.2 –±0.4 weak correlation
±0.4 –±0.7 correlated
±0.7 –±0.9 strong correlation
±0.9 –±1.0 very strong correlation
Tab.9  Correspondence between the range of correlation coefficients and correlations (expressed in words)
bridge name direction of movement number of measurement data sets
Shingondai Bridge Toko → Nishi 80 sets
Nishi → Toko
Shiratsuchi Daini Bridge Nishi → Yoshi 77 sets
Yoshi → Nishi
Jase Bridge Sho → Kin 66 sets
Kin → Sho 64 sets
Tab.10  Number of measurement data sets
bridge name direction of movement span characteristic deflection(mm)
average standard deviation
Shingondai Bridge Toko → Nishi – –5.218 1.733
Nishi → Toko – –2.909 1.231
Shiratsuchi Daini Bridge Nishi → Yoshi A –2.731 1.071
B –2.030 0.868
Yoshi → Nishi B –1.577 0.727
A –2.439 1.021
Jase Bridge Sho → Kin A –2.153 0.608
B –1.910 0.533
C –2.017 0.651
D –2.085 0.657
E –2.467 0.669
Kin → Sho E –1.423 0.628
D –1.499 0.651
C –1.131 0.547
B –1.164 0.579
A –1.532 0.554
Tab.11  Calculated values of characteristic deflection by bridge/span
Fig.32  Characteristic deflection values obtained by applying the simple moving average method to four-year monitoring data (Shingondai Bridge). (a) Tokonami→Nishikiwa Gakkomae (Number of data sets: 80); (b) Nishikiwa Gakkomae→Tokonami (Number of data sets: 80)
Fig.33  Characteristic deflection values obtained by applying the simple moving average method to four-year monitoring data (Shiratsuchi Daini Bridge). (a) Nishikiwa Gakkomae→Yoshida (Span A); (b) Yoshida→Nishikiwa Gakkomae (Span A); (c) Nishikiwa Gakkomae→Yoshida (Span B); (d) Yoshida→Nishikiwa Gakkomae (Span B)
Fig.34  Sightseeing bus used for the field test
Fig.35  Side view of the out-of-service bridge used for field testing
Fig.36  Bridge view before and after guardrail removal. (a) Before guardrail removal; (b) After guardrail removal
Fig.37  Changes in characteristic deflection due to guardrail removal
Fig.38  Fixed-route bus used and sensor location
Fig.39  Structural types, dimensions and appearances of target bridges. (a) FCT-in; (b) FCT-out. (unit: m)
Fig.40  Velocity censor
Fig.41  Comparison of under-rear-wheel-spring and girder-midspan acceleration responses during bridge crossing. (a) FCT-in; (b) FCT-out
Fig.42  Deflection estimated from under-rear-wheel-spring acceleration response of bus (FCT-in)
Bridge name Type of superstructure Bridge length (m)
FCT-in Span number Start point 1 3-span continuous prestressed concrete slab girder bridge 16.00 68.13(total)
2 36.13
End point 3 16.00
FCT-out Span number Start point 1 Reinforced concrete T-girder cantilever bridge 10.65 49.04(total)
2 13.87
3 13.87
End point 4 10.65
Tab.12  Bridge data
No. Characteristic deflection (mm)
1 −4.51
2 −4.06
3 −4.37
4 −4.26
5 −4.65
6 −4.67
7 −3.72
8 −2.97
9 −4.87
10 −4.23
11 −3.33
12 −4.83
13 −4.44
14 −3.43
15 −3.11
Average −4.10
Tab.13  Characteristic deflection (FCT-in)
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