• Smart Structures and Systems
• /
• v.17 no.6
• /
• pp.995-1015
• /
• 2016

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.

• Smart Structures and Systems
• /
• v.22 no.5
• /
• pp.509-525
• /
• 2018

Sensors and systems in Civionics technology play an important role for continuously facilitating real-time structure monitoring systems by detecting and locating damage to or degradation of structures. An advanced materials, design processes, long-term sensing ability of sensors, electromagnetic interference, sensor placement techniques, data acquisition and computation, temperature, harsh environments, and energy consumption are important issues related to sensors for structural health monitoring (SHM). This paper provides a comprehensive survey of various sensor technologies, sensor classes and sensor networks in Civionics research for existing SHM systems. The detailed classification of sensor categories, applications, networking features, ranges, sizes and energy consumptions are investigated, summarized, and tabulated along with corresponding key references. The current challenges facing typical sensors in Civionics research are illustrated with a brief discussion on the progress of SHM in future applications. The purpose of this review is to discuss all the types of sensors and systems used in SHM research to provide a sufficient background on the challenges and problems in optimizing design techniques and understanding infrastructure performance, behavior and current condition. It is observed that the most important factors determining the quality of sensors and systems and their reliability are the long-term sensing ability, data rate, types of processors, size, power consumption, operation frequency, etc. This review will hopefully lead to increased efforts toward the development of low-powered, highly efficient, high data rate, reliable sensors and systems for SHM.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.10 no.3
• /
• pp.159-164
• /
• 2006

Mobile communication with wireless modem can be powerful tool in web-based structural health monitoring system in which power and communication method are crucial points. In this study, the major reasons of side cracks in tunnel lining are studied by FEM analysis. In addition, a web-based monitoring system using mobile communication with wireless modem is applied to the tunnel structure to monitor the long term behavior of the side cracks. The field application shows that CDMA is useful method for structural health monitoring system which installed long distance away.

• Smart Structures and Systems
• /
• v.11 no.5
• /
• pp.511-531
• /
• 2013

Recent advances in low-cost remote monitoring systems have made it possible and practical to perform structural health monitoring (SHM) on a large scale. However, it is difficult for a single remote monitoring system to cover a wide range of SHM applications due to the amount of specialization required. For the remote monitoring system to be flexible, sustainable, and robust, this article introduces a new cost-effective, advanced remote monitoring and inspection system named DuraMote that can serve as a next generation supervisory control and data acquisition (SCADA) system for civil infrastructure systems. To evaluate the performance of DuraMote, we conduct experiments at two representative counterpart sites: a bridge and water pipelines. The objectives of this article are to improve upon the existing SCADA by integrating the remote monitoring system (i.e., DuraMote), to describe a prototype SCADA for civil engineering structures, and to validate its effectiveness with long-term field deployment results.

• Smart Structures and Systems
• /
• v.11 no.6
• /
• pp.637-662
• /
• 2013

The Jiangyin Bridge is a suspension bridge with a main span of 1385 m over the Yangtze River in Jiangsu Province, China. Being the first bridge with a main span exceeding 1 km in Chinese mainland, it had been instrumented with a structural health monitoring (SHM) system when completed in 1999. After operation for several years, it was found with malfunction in sensors and data acquisition units, and insufficient sensors to provide necessary information for structural health evaluation. This study reports the SHM system upgrade project on the Jiangyin Bridge. Although implementations of SHM system have been reported worldwide, few studies are available on the upgrade of SHM system so far. Recognizing this, the upgrade of original SHM system for the bridge is first discussed in detail. Especially, lessons learned from the original SHM system are applied to the design of upgraded SHM system right away. Then, performance assessment of the bridge, including: (i) characterization of temperature profiles and effects; (ii) recognition of wind characteristics and effects; and (iii) identification of modal properties, is carried out by making use of the long-term monitoring data obtained from the upgraded SHM system. Emphasis is placed on the verification of design assumptions and prediction of bridge behavior or extreme responses. The results may provide the baseline for structural health evaluation.

• Computers and Concrete
• /
• v.30 no.5
• /
• pp.301-310
• /
• 2022

Cement-based sensors have been widely used as structural health monitoring systems, however, their long-term sensing performance have not actively investigated. In this study, a deep learning-based methodology is adopted to predict the long-term piezoresistive properties of cement-based sensors. Samples with different multi-walled carbon nanotube contents (0.1, 0.3, and 0.5 wt.%) are fabricated, and piezoresistive tests are conducted over 10,000 loading cycles to obtain the training data. Time-dependent degradation is predicted using a modified long short-term memory (LSTM) model. The effects of different model variables including the amount of training data, number of epochs, and dropout ratio on the accuracy of predictions are analyzed. Finally, the effectiveness of the proposed approach is evaluated by comparing the predictions for long-term piezoresistive sensing performance with untrained experimental data. A sensitivity of 6% is experimentally examined in the sample containing 0.1 wt.% of MWCNTs, and predictions with accuracy up to 98% are found using the proposed LSTM model. Based on the experimental results, the proposed model is expected to be applied in the structural health monitoring systems to predict their long-term piezoresistice sensing performances during their service life.

• Smart Structures and Systems
• /
• v.30 no.6
• /
• pp.649-659
• /
• 2022

Structural Health Monitoring (SHM) researchers have identified Augmented Reality (AR) as a new technology that can assist inspections. Post-seismic structural inspections are conducted to evaluate the safety level of the damaged structures. Quantification of nearby structural changes over short-term and long-term periods can provide building inspectors with information to improve their safety. This paper proposes a Time Machine Measure (TMM) application based on an Augmented Reality (AR) Head-Mounted-Device (HMD) platform. The primary function of TMM is to restore the saved meshes of a past environment and overlay them onto the real environment so that inspectors can intuitively measure dynamic structural deformation and other environmental movements. The proposed TMM application was verified by demo experiments simulating a real inspection environment.

• Structural Monitoring and Maintenance
• /
• v.1 no.1
• /
• pp.47-67
• /
• 2014

This study has been motivated to examine the performance of a wireless sensor system under the typhoons as well as to analyze the effect of the typhoons on the bridge's vibration responses and the variation of cable forces. During the long-term field experiment on a real cable-stayed bridge in years 2011-2012, the bridge had experienced two consecutive typhoons, Bolaven and Tembin, and the wireless sensor system had recorded data of wind speeds and vibration responses from a few survived sensor nodes. In this paper, the wireless structural health monitoring of stay cables under the two consecutive typhoons is presented. Firstly, the wireless monitoring system for cable-stayed bridge is described. Multi-scale vibration sensor nodes are utilized to measure both acceleration and PZT dynamic strain from stay cables. Also, cable forces are estimated by a tension force monitoring software based on vibration properties. Secondly, the cable-stayed bridge with the wireless monitoring system is described and its wireless monitoring capacities for deck and cables are evaluated. Finally, the structural health monitoring of stay cables under the attack of the two typhoons is described. Wind-induced deck vibration, cable vibration and cable force variation are examined based on the field measurements in the cable-stayed bridge under the two consecutive typhoons.

• Smart Structures and Systems
• /
• v.20 no.2
• /
• pp.197-205
• /
• 2017

The dynamic performance of railway bridges under high-speed trains draws the attention of bridge engineers. The vibration issue for long-span bridges under high-speed trains is still not well understood due to lack of validations through structural health monitoring (SHM) data. This paper investigates the correlation between bridge acceleration and train speed based on structural dynamics theory and SHM system from three foci. Firstly, the calculated formula of acceleration response under a series of moving load is deduced for the situation that train length is near the length of the bridge span, the correlation between train speed and acceleration amplitude is analyzed. Secondly, the correlation scatterplots of the speed-acceleration is presented and discussed based on the transverse and vertical acceleration response data of Dashengguan Yangtze River Bridge SHM system. Thirdly, the warning indexes of the bridge performance for correlation scatterplots of speed-acceleration are established. The main conclusions are: (1) The resonance between trains and the bridge is unlikely to happen for long-span bridge, but a multimodal correlation curve between train speed and acceleration amplitude exists after the resonance speed; (2) Based on SHM data, multimodal correlation scatterplots of speed-acceleration exist and they have similar trends with the calculated formula; (3) An envelope line of polylines can be used as early warning indicators of the changes of bridge performance due to the changes of slope of envelope line and peak speed of amplitude. This work also gives several suggestions which lay a foundation for the better design, maintenance and long-term monitoring of a long-span high-speed bridge.

• Smart Structures and Systems
• /
• v.15 no.2
• /
• pp.469-488
• /
• 2015

Thermal loads, especially thermal gradients, have a considerable effect on the behaviors of large-scale bridges throughout their lifecycles. Bridge design specifications provide minimal guidance regarding thermal gradients for simple bridge girders and do not consider transversal thermal gradients in wide girder cross-sections. This paper investigates the three-dimensional thermal gradients of arch bridge girders by integrating long-term field monitoring data recorded by a structural health monitoring system, with emphasis on the vertical and transversal thermal gradients of wide concrete-steel composite girders. Based on field monitoring data for one year, the time-dependent characteristics of temperature and three-dimensional thermal gradients in girder cross-sections are explored. A statistical analysis of thermal gradients is conducted, and the probability density functions of transversal and vertical thermal gradients are estimated. The extreme thermal gradients are predicted with a specific return period by employing an extreme value analysis, and the profiles of the vertical thermal gradient are established for bridge design. The transversal and vertical thermal gradients are developed to help engineers understand the thermal behaviors of concrete-steel composite girders during their service periods.