1,720,986 research outputs found
Automatic identification of dense damage-sensitive features in civil infrastructure using sparse sensor networks
Full text linkWidespread monitoring of bridges is yet rarely employed at a territorial level due to the high costs of monitoring systems. However, the aging of civil infrastructures, combined with the growing traffic demand, poses the need for a simple and automatic tool that helps emergency management. In this paper, an integrated algorithm for the identification of dynamic and dense quasi-static structural features exploiting moving vehicles is proposed. Filtering raw acceleration structural responses, triggered by passing vehicles, enables the identification of modal parameters and curvature influence lines. The procedure can be implemented efficiently as its main computational core consists of convolutions. The definition of a curvature-based damage index leads to accurate localization and quantification of structural anomalies using few sensors. The proposed procedure is tested on three viaducts of the Italian A24 motorway. Moreover, a numerical model is studied to evaluate the potentialities of the strategy for damage localization
Modal assurance distribution of multivariate signals for modal identification of time-varying dynamic systems
Full text linkMost time–frequency representations (TFRs) and signal analysis methods used for the identification of dynamic systems through non-parametric techniques are based on univariate signals. However, combining the information obtained from different sensors to investigate the overall behavior of the monitored structure is not trivial, as different recordings may show different features. Moreover, methods based upon the analysis of the energy density distribution in the time–frequency plane generally suffer from problems related to crossing and closely-spaced modes. In this paper, a new time–frequency representation of multivariate and multicomponent signals based on the modal assurance criterion (MAC) is presented. The analysis of the modal assurance distribution (MAD) thus obtained enables the extraction of decoupled modal responses, which can then be used to evaluate the instantaneous modal parameters of time-varying systems. To this end, a decomposition algorithm based on modal assurance (DAMA) is proposed, employing the watershed segmentation of the MAD. The results for two case studies, a finite element model and a full-scale experimental benchmark, are shown, considering both the original MAD and two enhanced versions, here proposed to improve its readability. The results are compared with those obtained from modern and widely used techniques, showing the promising efficacy of the proposed method for signals with time-varying frequency and amplitude, even in the presence of narrow-band disturbances and white noise, as well as with vanishing modes
Structural integrity assessment of railway bridges during the passage of trains
No full textTraditional algorithms for the identification of dynamic parameters based on vibrational structural response generally involve strict assumptions about stationarity and may not be suitable for time-varying systems. Therefore, there is a tendency to discard the measurements of the structural response collected during short-time events, such as train passages on bridges. The response to a strong event may however include valuable information about structural features that cannot be observed in low-excitation scenarios. Moreover, a strong excitation typically generates a higher-amplitude structural response, which is particularly convenient when using low-cost instrumentation for data collection that is usually characterized by low sensitivity. In this paper, dynamic parameters of bridges during the passage of trains are identified by fitting the structural response to a simplified analytical model specialized for railway applications. The efficacy of a damage index based on the fitting residuals is investigated using a numerical study, simulating the use of an event-triggered smart sensing system. Applying the proposed method, damage detection can be achieved using a single low-cost sensing node
The value of seismic structural health monitoring for post-earthquake building evacuation
No full textIn the aftermath of a seismic event, decision-makers have to decide quickly among alternative management actions with limited knowledge on the actual health condition of buildings. Each choice entails different direct and indirect consequences. For example, if a building sustains low damage in the mainshock but people are not evacuated, casualties may occur if aftershocks lead the structure to fail. On the other hand, the evacuation of a structurally sound building could lead to unnecessary financial losses due to business and occupancy interruption. A monitoring system can provide information about the condition of the building after an earthquake that can support the choice between several competing alternatives, targeting the minimization of consequences. This paper proposes a framework for quantifying the benefit of installing a permanent seismic structural health monitoring (S2HM) system to support building evacuation operations after a seismic event. Decision-makers can use this procedure to preventively evaluate the benefit of an SHM system and decide about the worthiness of its installation
A method to assess the value of monitoring an SHM system
No full textAging structural components, together with the increasing transportation needs and limited budgets, are challenging aspects that typically concern decision-makers and infrastructure owners. Although Structural Health Monitoring (SHM) has been a powerful tool to optimize maintenance-related activities and post-disaster emergency management, the sensor readout and, therefore, the outcome of the monitoring system is susceptible to errors due to malfunctioning. For years, the Value of Information (VoI) has been studied to quantify the long-term benefit of SHM systems against the initial investment in sensing instrumentation without considering the eventuality of faulty sensing nodes. However, these are very common in field applications. This paper proposes a new framework to calculate the benefit of using Sensor Validation Tools (SVTs) before calculating the damage-sensitive features that drive the SHM process. The novel approach extends the traditional Vol to consider multiple "health"states of the SHM system, associate the outcome of the SHM system with the state of both the structure and the SHM system, and quantify the additional value obtained from SVTs
Reducing false alarms in structural health monitoring systems by exploiting time information via Binomial Distribution Classifier
Full text linkThis paper proposes an approach for anomaly/damage detection via structural health monitoring (SHM) systems based on a Binomial Distribution Classifier (BDC). The approach consists of two monitoring levels, labeled as alert and alarm states, respectively, where a damage index (DI) is computed and tracked over time. The alert state is reached when the DI exceeds a given threshold. At this stage, the BDC algorithm starts counting the number of DI values above the threshold within an observation window and computing the related probability of occurrence by using the binomial probability distribution. If the probability falls below a desired limit, the alarm state is triggered. Conversely, the SHM system returns in the non-alert condition. The proposed approach is discussed and evaluated through case studies involving both simulated and experimental data. In the examples, the DI is computed using the Mahalanobis distance of the monitored modal frequencies. The results demonstrate the capability of the BDC to reduce false alarms while preserving the probability of detection
Shared micromobility-driven modal identification of urban bridges
No full textRecent research in Indirect Structural Health Monitoring (ISHM) uses the dynamic response of instrumented vehicles to carry out “drive-by” monitoring of bridges. These vehicles are generally cars or trucks instrumented with different types of sensors. However, some urban bridges are inaccessible to regular vehicles. Also, cars and trucks have non-negligible weight and suspension systems that may affect the collected vibration data. Stiff, light, and standardized shared micromobility vehicles, such as bicycles and electric kick scooters, have never been explored for ISHM purposes. This paper proposes an innovative and automatic ISHM strategy based on the data collected by smartphones temporarily installed on shared micromobility vehicles. An identification procedure suitable for cloud computing is proposed to extract the dynamic parameters of bridges without needing any sensor deployment, becoming particularly appealing for monitoring a densely built environment at a territorial scale. The methodology is applied to a real footbridge in Bologna (Italy)
Structure-type classification and flexibility-based detection of earthquake-induced damage in full-scale RC buildings
Full text linkDetecting early damage in civil structures is highly desirable. In the area of vibration-based damage detection, modal flexibility (MF)-based methods have proven to be promising tools for promptly identifying changes in the global structural behavior. Many of these methods have been developed for specific types of structures, giving rise to different approaches and damage-sensitive features (DSFs). Although structural type classification is an important part of the damage detection process, this part of the process has received little attention in most literature and often relies on the use of a-priori engineering knowledge. Moreover, in general, experimental validations are only performed on small-scale laboratory structures with controlled artificial damage (e.g., imposed stiffness reductions). This paper proposes data-driven criteria for structure-type classification usable in the framework of MF-based damage identification methods to select the most appropriate algorithms and DSFs for detecting and localizing structural anomalies. This paper also tests the applicability of the proposed classification criteria and the damage identification methods on full-scale reinforced concrete (RC) structures that have experienced earthquake-induced damage. The considered structures are a seven-story RC wall building and a five-story RC frame building, which were both tested on the large-scale University of California, San Diego-Network for Earthquake Engineering Simulation (UCSD-NEES) shaking table
Impact of Decision Scenarios on the Value of Seismic Structural Health Monitoring
No full textThe limited knowledge that decision-makers have on the actual condition of civil structures and infrastructures complicates the management of seismic emergencies in urbanized areas. In this respect, Seismic Structural Health Monitoring (S2HM) can support decision-makers by providing real-time information on the structural condition. Nevertheless, S2HM information comes with a cost, and decision-makers have to decide if installing this type of system is worthy before the information is collected. In this paper, the benefit of S2HM in post-earthquake emergency management is assessed through the Value of Information (VoI) from Bayesian decision analysis. The VoI can be intended as the expected reduction in management costs resulting from monitoring information. If the VoI is higher than the cost of the monitoring system, the manager should install it. The methodology is applied to an exemplary building in a seismic area. It is demonstrated and discussed in the paper that the value of S2HM is strongly influenced by the decision scenario considered by the decision-maker. Specifically, it is shown that the VoI is particularly high when the S2HM information prevents unnecessary building evacuation and related losses of functionality
Lightweight vehicles in indirect structural health monitoring: Current advances and future prospects
Full text linkRecent research has explored the potential of using the dynamic response of passing vehicles to conduct Structural Health Monitoring (SHM) efficiently. Various types of vehicles, including cars, vans, trucks, and even manually propelled carts, have been employed in this approach, with different configurations of exciters and receivers. A noteworthy development in this field involves the inclusion of lightweight vehicles like bicycles and scooters. Lightweight vehicles offer several advantages, including their affordability, sustainability, and minimal environmental impact. These vehicles have a negligible impact on the dynamic behavior of structures due to their low speeds and negligible mass, making them ideal for monitoring structures that are challenging to access, such as footbridges. This paper provides a comprehensive review of recent literature on the application of lightweight vehicles in SHM of urban bridges. It emphasizes the potential benefits and current challenges associated with these applications while offering insights into future research directions
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