Term Structural Health Monitoring Research Articles

Hybrid Fiber Optic Cable for Strain Profiling and Crack Growth Measurement in Rock, Cement, and Brittle Installation Media.

Brillouin scattering-based distributed fiber optic sensing (DFOS) technologies such as Brillouin optical time domain reflectometry (BOTDR) and Brillouin optical time domain analysis (BOTDA) have broad applicability for the long term and real-time monitoring of large concrete structures, underground mine excavations, pit slopes, and deep subsurface wellbores. When installed in brittle media, however, the meter scale spatial resolution of the BOTDR/A technology prohibits the detection or measurement of highly localized deformations, such as those which form at or along cracks, faults, and other discontinuities. This work presents a novel hybrid fiber optic cable with the ability to self-anchor to any brittle installation media without the need for manual installation along fixed interval points. Laboratory scale testing demonstrates the ability of the hybrid fiber optic cable to measure strains across highly localized deformation zones in both tension and shear. In addition, results show the applicability of the developed technology for strain monitoring in high displacement environments. Linear relationships are proposed for use in estimating the displacement magnitude along discontinuities in brittle media from strain signals collected from the hybrid fiber optic cable. The hybrid fiber optic cable has broad potential applications, such as geomechanical monitoring in underground mines, surface pits, large civil infrastructure projects, and deep subsurface wellbores. The benefits of fiber optic sensing, such as the intrinsic safety of the sensors, the long sensing range, and real time capabilities make this a compelling technique for long term structural health monitoring (SHM) in a wide range of industrial and civil applications.

Fully automated precise operational modal identification

Modal identification has been playing an important role in structural health monitoring. Traditional modal identification process requires too much user interaction and many manually defined thresholds. In this study, a new fully automated modal identification approach is proposed to automatically identify the modal parameters through automatic interpretation of stabilization diagram. The proposed approach works efficiently without any manually tuned threshold or index except some widely used thresholds, is robust to the mere input, and can be used to identify the closely spaced modes. A modified Fuzzy C-means clustering algorithm is proposed to automatically interpret the stabilization diagram, without any specifically tuned index or threshold but only with a default maximum clustering number. The optimal cluster number and desired clustering result can be obtained through an iterative intelligent graph partitioning algorithm. The boxplot is introduced in the last step to assess the precision of the clustering results from a statistical perspective, and outliers can be found and eliminated. The proposed approach is applied to analyze the real monitoring data of a long-span suspension bridge and a benchmark footbridge with closely spaced modes to validate the feasibility, and parametric analysis is also conducted to assess the robustness. It can be concluded from the results that the proposed approach can automatically extract the modal parameters, including the closely spaced modes, with a high accuracy and robustness. The proposed approach provides a reliable and promising method for analyzing the monitoring data from long term structural health monitoring.

Review on structural health monitoring for restoration of heritage buildings

This study to an enormous number of heritage structures around the world. Hence, the safety of structures will be decreased due to aggressive environmental conditions and vulnerable actives. So, we can maintain and conservation of heritage buildings. The Non-destructive testing (NDT) can be used for architectural archaeology, structural stability analysis, materials characterization, durability, and we observed that structural health monitoring with the help of combined wired and wireless sensors are power and time-consuming and costly, and it needs to be replaced by the more efficient system to be used in engineering application, using different routines and the research work done by collecting data and application of the long term and short term structural health monitoring system on structures using linear and nonlinear method of Non-destructive testing (NDT) techniques.

Long term structural health monitoring for old deteriorated bridges: a copula-ARMA approach

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

Diagnostic Testing of a Vertical Lift Truss Bridge for Model Verification and Decision-Making Support

A practical long term structural health monitoring program must be based on reasonable field capabilities, the needs of the bridge owner, and the anticipated structural behavior unique to the structure. Each sensor installed as part of the monitoring program should provide information directly in response to an operational needs related to the structure’s short term and long term performance. A thoughtfully considered instrumentation plan developed in cooperation with the bridge designer, bridge manager, bridge maintenance operator and academic researchers will provide data to enhance both the state of the practice and state of the art for the bridge structural design, management and maintenance. Monitoring a bridge’s structural response has the potential to a) detect the presence of structural changes for condition assessment, b) inform the bridge manger to assist in daily operational decision-making and c) validate the structural design assumptions and (d) refine a structural model of the bridge to be used for performance prediction. The excitation for these responses typically comes from traffic or environmental demands. Vertical lift bridges provide a unique opportunity for structural health monitoring based on the dynamic response due to the frequent and repeated impact imparted on the structure each time the lift span open and closes. In this paper, a structural health monitoring system designed to provide valuable information for design verification, structural model calibration, fatigue monitoring, and operational decision-making support for the reconstructed Memorial Bridge carrying US Route 1 between Portsmouth, New Hampshire and Kittery, Maine. This paper will detail the development of the sensor layout including input from stakeholders, accessibility issues and complementary and contradicting objectives. A set of structural models with varying degrees on complexity were created based on the structural performance objectives. The data collected during a pseudo-static truck load test was used to calibrate the structural models of the bridge and to select the appropriate model for each post-processing and decision-making tools related to structural performance.

Structural monitoring of “Himera” viaduct by low-cost MEMS sensors: characterization and preliminary results

The term structural health monitoring (SHM) usually refers to the process of implementing a damage detection strategy for aerospace, civil or mechanical engineering infrastructures. Under an extreme event, such as an earthquake or unanticipated blast loading, SHM could be used for rapid condition screening, to provide, in near real time, reliable information about the performance of a structural system during the event and about the subsequent integrity of the system itself. On the other hand, owners of buildings and civil infrastructures need information on the actual state of the structures in order to realize effective life-cycle management plans and reduce the economic and social impact of maintenance. In fact, inspections and repairs entail huge direct and social costs due to the interruption or reduction of the structure serviceability. Such information can be collected and elaborated by means of adequate monitoring systems but their diffusion is still limited by the high cost of sensors and devices needed. In this work, the realization of a monitoring system on some bridge piers of the “Himera” viaduct, located in Italian A19 Palermo–Catania highway and recently damaged by a landslide, is presented. The proposed monitoring system aims to observe the global stability of the un-collapsed side of the viaduct during the demolition works of the other side and it is intended as a quasi-real-time alert tool able to send data and warning messages to an operations center. In order to contain costs, low-cost micro electronic mechanical system sensors have been used for the monitoring. The architecture and main features of the developed monitoring system are described in detail and the preliminary results, recorded during the first months of the campaign, are reported and discussed. Since the proposed monitoring system is still a prototype, it has been necessary to provide a metrological characterization campaign in laboratory conditions in order to define a calibration law to correct the acquired data and to estimate the sensitivity and the accuracy of the measurements. The results proved that the proposed system can be used for the monitoring of civil structures and infrastructures.

An integrated approach for structural health monitoring using an in-house built fiber optic system and non-parametric data analysis

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.

Structural health monitoring of a stress-ribbon footbridge

This work describes the development and implementation of a structural health monitoring system on a stress-ribbon footbridge. In a first part, it characterises the implemented continuous dynamic monitoring system and the application of automated operational modal analysis to analyse the variation of modal properties estimates along several years. A correlation analysis is then conducted showing that environmental and operational factors (e.g. temperature and pedestrian traffic) induce significant nonlinear effects on the modal frequency estimates, which may mask subtle early damage. Taking into account linear relations between frequency estimates of different modes, the linear Principal Component Analysis (PCA) is applied to remove those effects. Novelty analysis of the residual errors of PCA is used to build a statistical damage indicator for long term structural health monitoring. Finally, the efficiency of the described damage detection methodology is evidenced by simulating some realistic damage scenarios based on an experimentally validated finite element model and observing the clear deviation of the damage indicator. It is demonstrated that such a dynamic monitoring system can serve as an effective tool for long term bridge health monitoring.

Long term structural health monitoring by Brillouin fibre-optic sensing: a real case

We report the results of a long term structural health monitoring (SHM) test campaign performed on a concrete bridge. A one-year test campaign was performed by a portable prototype instrument based on stimulated Brillouin scattering in a single-mode optical fibre. The optical fibre sensor was attached along one arch of the bridge using two types of adhesive for comparison purposes. The attached fibre was able to provide the strain distribution along the structure during the one-year test campaign, with a spatial resolution of 1 m. A crack was revealed and correctly localized by the distributed sensor.

Structural health monitoring and reliability estimation: Long span truss bridge application with environmental monitoring data

The main objective of this study is to present the reliability estimation studies for the main truss components as well as the entire structural system of a long span truss bridge which is the longest in its category in the USA. It is possible to assess the safety level of a long span bridge by using a probabilistic approach in terms of its component and system reliability indices. However, most of the older long span bridges were designed based on allowable stress design and it is not possible to quantify their reliability. The reliability analysis in this study is based on the distributions estimated for dead, live and wind loads. The bridge was also subjected to long term structural health monitoring where large amount of input and response data have been collected. Analysis of the long term monitoring data revealed distinct structural behavior in terms of patterns and magnitudes under various external loading effects. As an example, it is shown that the structural responses due to temperature are not very easy to conceptualize and subsequently model using conventional analysis methods. In order to explore the effects of temperature on the structure and to include the long term monitoring data in reliability estimation, temperature-induced responses are also incorporated in the analysis. It is seen that the responses due to temperature have a significant effect on the overall system reliability.