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Summary: Operators want to maintain awareness of the structure being tested while observing sensor data. Normally, the human's gaze shifts to a separate device or screen during the experiment for data information, missing the structure's physical response. The human–computer interaction provides valuable data and information but separates the human from the reality. The sensor data does not collect experiment safety, quality, and other contextual information of critical value to the operator. To solve this problem, this research provides humans with real‐time information about vibrations using an augmented reality (AR) application. An application is developed to augment sensor data on top of the area of interest, which allows the user to perceive real‐time changes that the data may not warn of. This paper presents the results of an experiment that show how AR can provide a channel for direct sensor feedback while increasing awareness of reality. In the experiment a researcher attempts to closely follow a moving sensor with their own sensor while observing the moving sensor's data with and without AR. The results of the reported experiment indicate that augmenting the information collected from sensors in real time narrows the operator's focus to the structure of interest for more efficient and informed experimentation. [ABSTRACT FROM AUTHOR]

Summary: Precast buildings have been becoming popular in China in these 5 years since they have many merits such as effectiveness, safety, high quality, and environmental friendliness. In some cities of China, it is required to make the proportion of precast buildings account for 30% in newly built construction areas. Following the rapid development, their vibration behaviors are attracting more attention since it may be quite different from the cast‐in‐situ building. To investigate the difference, this paper studies the modal properties of two kinds of buildings, i.e., new‐type precast building and cast‐in‐situ building. They were built in the same area, while the structural forms are also similar. The main difference is the construction manner. Ambient vibration tests of these two structures were conducted respectively. Since the number of sensors is limited, the locations of interest were measured by a multiple‐setup technique. The difficulty encountered during the field test was discussed. A frequency domain Bayesian approach was used to conduct operational modal analysis. Both the most probable value and posterior uncertainties of modal parameters were studied, including translational, torsional, and wrapping modes. The difference of the modal parameters of the two kinds of buildings are compared and discussed. Finite element models were also built to perform a comparison. It is seen that although the structural forms and appearances of the two buildings are similar, some obvious differences were observed regarding the dynamic characteristics, which provide valuable information for popularizing and future assessment of the new‐type precast structure. [ABSTRACT FROM AUTHOR]

Summary: Large‐scale, long‐term structural health monitoring systems have become more feasible in recent years as the required data acquisition and analysis systems are more affordable to deploy. These long‐term systems must process and store vast amounts of data without wasting computational power and storage capacity with redundant or poor quality data. While not a primary system for damage detection, large‐scale, long‐term vibration monitoring systems aim to leverage changes in the dynamic signature of a structure to assess global structural changes. Although the ability to continually collect vibration data at high rates exists, it is not always feasible to store all these data long term. As more long‐term monitoring systems are deployed, efficient methods need to be developed to quickly and efficiently analyze large quantities of vibration data so that only the most pertinent information is archived. Previous researchers have used scheduled approaches, eg, taking data every hour, or triggered sensing systems. A monitoring system on the I‐35W St. Anthony Falls Bridge, which crosses the Mississippi River in Minneapolis, Minnesota, has been collecting vibration and temperature data since the structure's opening in 2008. This provides a uniquely large data set to establish the characteristics of a good signal for output‐only system identification to consistently and efficiently capture natural frequencies and mode shapes. To this end, a system identification routine using a novel signal selection approach and modal sorting routine that leverages NExT‐ERA/DC is proposed to analyze this large data set. The resulting information allows long‐term and temperature‐based trends to be identified. [ABSTRACT FROM AUTHOR]

Challenges concerning the automation of modal identification and tracking procedures in permanent monitoring systems for Structural Health Monitoring purposes are discussed. In this context, an automated procedure based on parametric identification methods that involve the interpretation of stabilization diagrams is proposed. The methodology comprehends two key points: (i) automatic analysis of stabilization diagrams, performed through a first check of reasonable damping ratio, a subsequent modal complexity check and a final clustering of structural modes; (ii) automated tracking of the evolution in time of the identified modal properties. The proposed modal clustering and tracking steps exploit the introduction of self-adaptable dynamic thresholds, that do not require any a priori manual tuning for the different recorded data set. Finally, the proposed approach was successfully validated using real data collected on a historic iron arch bridge. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper examines the influence of fire damage on experimentally measurable modal parameters to explore the potential role of vibration-based structural identification in post-fire condition assessment. Experimental modal analysis of a precast, prestressed concrete roof comprised of modular double-tee joists was performed following exposure to an accidental fire. Empirical evidence of localized structural degradation is identified in the mode shapes, which suggests that modal parameters are sensitive to fire-induced damage in prestressed concrete members. Additionally, measured out-of-plane global modes are correlated with finite element simulations using a model of the as-built roof as well as a model updated using a large set of impact-echo measurements across the double-tee roof to spatially map localized reductions in stiffness. The comparisons support the experimental conclusions and further demonstrate that, by coupling nondestructive techniques, it is possible to construct a validated analytical model of structural components with sufficient fidelity to assess suitability for rehabilitation and reuse. With further development, vibration-based monitoring and structural identification may be an attractive alternative to physical load testing, particularly when the risk of structural collapse under proof testing loads is high. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Multihop communication is an essential functionality of wireless smart sensor networks used for full-scale civil infrastructure monitoring. It allows sensors to cooperate and deliver data between nodes outside the direct communication range. Multihop communication that can reliably collect a large amount of data generated by the entire monitoring system to a single base-station can be made efficient with the consideration of the specific communication characteristics of civil infrastructure monitoring as well as radio interference and channel contention. This paper proposes an efficient multihop communication service for large static wireless sensor networks in the application to civil infrastructure monitoring. The proposed protocols include a flooding-based routing method that is able to efficiently generate stable static routes and a theoretically efficiency-optimal data collection protocol to promptly retrieve data from the entire network. Additionally, crucial enhancements are introduced for the stable implementation of the proposed methods. Experiments and a full-scale instrumentation are also included to demonstrate the protocols' applicability. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an extended constitutive relation error (ECRE)‐based method for detecting damage in structural systems. Although most ECRE‐based methods for damage detection have relied on an iterative model calibration process, the approach advocated in this study uses residual energy to identify structural damage. Residual energy represents the spatial distribution of discrepancies between model predictions of the undamaged system and experimental measurements obtained from the damaged system. The current study calculates this residual energy by tightly linking experimentally measured vibration data to an associated numerical model. The approach implemented in this paper, referred to as the M‐K ECRE‐based approach, differs from previous ECRE‐based damage detection methods in that it incorporates both unbalanced elastic and unbalanced inertial forces in the calculation of residual energy. The rationale for including unbalanced inertial forces is that damage can also alter the mass distribution of a structure in addition to its influence on the distribution of structural stiffness. By considering unbalanced inertial forces, the proposed approach improves the calculation of residual energy, which in turn leads to an improvement in the method's ability to identify damage. At the end of this study, the efficiency of the M‐K ECRE‐based approach to identify damage is demonstrated on a scaled two‐story steel frame that is subjected to varying types and severities of structural damage. [ABSTRACT FROM AUTHOR]