Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.

The use of a dynamic truck-trailer drive-by system to monitor bridge damping

Abstract: Bridge structures are continuously subject to degradation due to the environment, ageing and excess loading. Periodic monitoring of bridges is therefore a key part of any maintenance strategy as it can give early warning if a bridge becomes unsafe. This article investigates an alternative method for the monitoring of bridge dynamic behaviour: a truck–trailer vehicle system, with accelerometers fitted to the axles of the trailer. The method aims to detect changes in the damping of a bridge, which may indicate the existence of damage. A simplified vehicle–bridge interaction model is used in theoretical simulations to assess the effectiveness of the method in detecting those changes. The influence of road profile roughness on the vehicle vibration is overcome by recording accelerations from both axles of a trailer and then analysing the spectra of the difference in the accelerations between the two axles. The effectiveness of the approach in detecting damage simulated as a loss in stiffness is also investiga...

Finite Element Model Updating Using Evolutionary Strategy for Damage Detection

Abstract: : Structural health monitoring through the use of finite element model updating techniques for dispersed civil infrastructures usually deals with minimizing a complex, nonlinear, nonconvex, high-dimensional cost function with several local minima. Hence, stochastic optimization algorithms with promising performance in solving global optimization problems have received considerable attention for finite element model updating purposes in recent years. In this study, the performance of an evolutionary strategy in the finite element model updating approach was investigated for damage detection in a quarter-scale two-span reinforced concrete bridge system which was tested experimentally at the University of Nevada, Reno. The damage sequence in the structure was induced by a range of progressively increasing excitations in the transverse direction of the specimen. Intermediate nondestructive white noise excitations and response measurements were used for system identification and damage detection purposes. It is shown that, when evaluated together with the strain gauge measurements and visual inspection results, the applied finite element model updating algorithm of this article could accurately detect, localize, and quantify the damage in the tested bridge columns throughout the different phases of the experiment.

Flexible strain sensors fabricated using carbon-based nanomaterials: A review

Abstract: Flexible strain sensors have experienced growing demand due to their several potential applications, such as personalized health monitoring, human motion detection, structural health monitoring, smart garments, and robots. Recently, several academic results have been reported concerning flexible and stretchable strain sensors. These reports indicate that the materials and design methods have an important influence on the performance of strain sensors. Carbon-based nanomaterials including carbon-based nanofibers, carbon nanotubes, graphene, and carbon black nanoparticles play a key role in the fabrication of flexible strain sensors with excellent properties. In terms of design, carbon-based nanomaterials are generally combined with polymers to maintain the flexibility and stability of a strain sensor. Various combined methods were successfully developed using different assembly structures of carbon-based nanomaterials in polymers, such as uniform mixing and ordered structures, including films, fibers, nanofiber membranes, yarns, foams, and fabrics. The working mechanisms of the flexible strain sensors, including changing the conductive network between overlapped nanomaterials, tunneling effect, and crack propagation, are also different compared with that of traditional semiconductor and metal sensors. The effects of the carbon-based nanomaterial structures in polymers on the strain sensing performance have been comprehensively studied and analyzed. The potential applications of flexible strain sensors and current challenges have been summarized and evaluated. This review provides some suggestions for further development of flexible and stretchable strain sensors with outstanding performance.

Sensor validation using principal component analysis

Abstract: For a reliable on-line vibration monitoring of structures, it is necessary to have accurate sensor information. However, sensors may sometimes be faulty or may even become unavailable due to failure or maintenance activities. The problem of sensor validation is therefore a critical part of structural health monitoring. The objective of the present study is to present a procedure based on principal component analysis which is able to perform detection, isolation and reconstruction of a faulty sensor. Its efficiency is assessed using an experimental application.

Design of a structural health monitoring system for long-span bridges

Abstract: Structural health monitoring systems (SHMSs) have been adopted over the past decade to monitor and evaluate the structural health condition of long-span bridges. A SHMS is currently included as a standard mechatronic system in the design and construction of most large-scale and multi-disciplinary bridge projects, such as Stonecutters Bridge and SuTong Bridge in Hong Kong and China. The modular concept used in the design of the SHMSs for Tsing Ma Bridge, Kap Shui Mun Bridge and Ting Kau Bridge has a significant influence on the design of new SHMSs in Hong Kong and China. This modular concept has, however, been enhanced in the detailed design of the SHMS for Stonecutters Bridge by the Highways Department of Hong Kong. This paper introduces the enhanced modular concept of six integrated modules in terms of their respective functional performance requirements. The six integrated modules are the sensory system, the data acquisition and transmission system, the data processing and control system, the structural...