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.

Damage identification based on response-only measurements using cepstrum analysis and artificial neural networks

Abstract: This article presents a response-only structural health monitoring technique that utilises cepstrum analysis and artificial neural networks for the identification of damage in civil engineering structures. The method begins by applying cepstrum-based operational modal analysis, which separates source and transmission path effects to determine the structure’s frequency response functions from response measurements only. Principal component analysis is applied to the obtained frequency response functions to reduce the data size, and structural damage is then detected using a two-stage ensemble of artificial neural networks. The proposed method is verified both experimentally and numerically using a laboratory two-storey framed structure and a finite element representation, both subjected to a single excitation. The laboratory structure is tested on a large-scale shake table generating ambient loading of Gaussian distribution. In the numerical investigation, the same input is applied to the finite model, but...

An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Nanotubes for SHM of Large Structures.

Abstract: The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation Previous work by the authors was devoted to material fabrication, modeling and applications in SHM In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications

Wireless impedance sensor nodes for functions of structural damage identification and sensor self-diagnosis

Abstract: Economic and reliable online health monitoring strategies are very essential for safe operation of civil, mechanical and aerospace structures. This study presents online structural health monitoring (SHM) techniques using wireless impedance sensor nodes equipped with both functions of structural damage identification and sensor self-diagnosis. The wireless impedance sensor node incorporating a miniaturized impedance measuring chip, a microcontroller and radio-frequency (RF) telemetry is equipped with the capabilities for temperature sensing, multiplexing of several sensors, and local data analysis. The feasibility of the sensor node for structural damage identification is firstly investigated through a series of experimental studies inspecting loosened bolt damage and cut damage cases. Additionally, a temperature effects-free sensor self-diagnosis algorithm is embedded into the sensor node and its feasibility is examined from the experiments monitoring the integrity of each piezoelectric sensor on a wireless sensor network.

Influence of the gauge length on the accuracy of long-gauge sensors employed in monitoring of prismatic beams

Abstract: Depending on the geometric basis of measurement (gauge length), discrete strain sensors used in structural monitoring of civil engineering structures can be considered as short-gauge sensors or long-gauge sensors. Long-gauge sensors measure average strain over the gauge lengths and are used for global monitoring of structures, in particular, those built of inhomogeneous materials. However, the strain distribution along the sensor's gauge length may be nonlinear and the measured average strain value that is commonly attributed to the midpoint of the sensor may be different from the real value of strain at that point. Consequently, excessively long sensors may feature significant errors in measurement. However, short-gauge sensors are more susceptible to other types of measurement error, most notably, error caused by discontinuities (open cracks) distributed in the monitored material. Thus an optimum gauge length is to be found. The error in average strain measurement inherent to the sensor's gauge length introduced by the strain distribution and discontinuities in the monitored material is modelled for the most common applications met in civil engineering practice. The modelling takes into account the geometric properties of the monitored structure and various load cases. Guidelines for the selection of an appropriate gauge length are proposed, and tables for measurement error estimation are presented.