Structural Control and Health Monitoring

Bosurgi, Gaetano; Bruneo, Dario; De Vita, Fabrizio; Pellegrino, Orazio; Sollazzo, Giuseppe

doi: 10.1002/stc.2905pmid: N/A

Recently, even the road industry has been involved in an evolutionary process, inspired by the novel ‘Industry 4.0’. This transition moves the attention towards big‐data and Internet of Things concepts, determining novel data flows and relevant management efforts. In smart roads, modern instrumented vehicles and networks of sensors will provide frequent helpful measures (traffic, weather, condition, accidents, mechanical performance, etc.), with reduced efforts and costs. However, this process is currently at the preliminary phases and several issues raise. Since the management and elaboration of huge amounts of data represent a relevant novel issue, in this study, an original web platform for collection and analysis of road performance data is proposed. This platform can acquire and process several data classes and support maintenance activity planning. This paper focuses on pavement maintenance, to provide a reliable decision support tool for road agencies, alternatively feedable by modern survey equipment and, in future, widespread sensors (when effective smart road sensors are installed on the main highways). The platform has been tested, in a preliminary form, on an existing motorway, considering high‐performance survey systems data, with interesting and positive results.

Quqa, Said; Landi, Luca; Diotallevi, Pier Paolo

doi: 10.1002/stc.2891pmid: N/A

In this paper, a new strategy for vibration‐based structural health monitoring is proposed, specifically designed for smart sensors with edge computing capabilities organized in a line topology. This solution is aimed at maximizing resource optimization and enables the identification of modal parameters even for large or densely instrumented structures, where star‐topology monitoring systems are typically unsuitable. In particular, an efficient data management procedure is proposed to reduce data transmission, thus improving efficiency and minimizing maintenance interventions for battery replacement in wireless applications. The maximum volume of transmitted data can be selected by the user, based on the specific requirements of the network. Although the considerable reduction of data size, the proposed approach enables accurate estimation of the structural parameters in challenging scenarios where other techniques generally fail. Modal parameters are identified in an online fashion, enabling near real‐time detection and localization of early damage. Applications to a real case study instrumented with a dense sensor network show the effectiveness of the proposed approach and the possibility of localizing structural defects in slightly damaged civil structures.

doi: 10.1002/stc.2786pmid: N/A

No abstract is available for this article.

Prawin, J.

doi: 10.1002/stc.2903pmid: N/A

A novel dynamic principal component analysis (DPCA)‐based baseline‐free damage diagnostic technique addressing breathing crack detection, localization, and characterization is proposed using ambient vibration data in the time domain. The nonlinear components sensitive to breathing crack, buried in the noisy responses, are first reconstructed by the elimination of the active principal components contributing to the total response using DPCA. A temporal damage sensitive feature based on the evolution of the variation of the residual principal component over time is proposed for confirming the presence and identifying the exact time instant of breathing crack in the structure. Besides detection, three new damage localization indices based on the fractal dimensional analysis of the residual response, first residual principal component vector, and directional angle are proposed for breathing crack localization. The effectiveness of the proposed DPCA approach is verified using the synthetic datasets of the benchmark simply supported beam with a breathing crack, provided by Helsinki Metropolia University of Applied Sciences and a numerically simulated cantilever beam with varied spatial locations and different depths of breathing crack. Finally, experimental investigations have been carried out to demonstrate the practical viability of the proposed DPCA approach.

Jeong, Jong‐Hyun; Jo, Hongki

doi: 10.1002/stc.2902pmid: N/A

While structural displacement provides essential information about static and/or low‐frequency dynamic characteristics of structural behaviors, full‐scale measurement of absolute displacement in field structures is extremely challenging because of the requirement of fixed reference in most cases. Recent computer vision‐based sensing technologies have advanced to the level of reference‐free monitoring of full‐scale dynamic displacement using generic features of the structure. However, current generic feature‐based methods have limited to only short‐term or campaign‐type monitoring applications due to the intrinsic limitations of computer‐vision sensing under variable environmental conditions. This study investigates deep learning‐based approaches for real‐time computer‐vision sensing that enables displacement monitoring using generic features under harsh environmental uncertainties. Distractor‐Aware Siamese Region Proposal Network (DaSiamRPN) was employed to address the environmental uncertainty issues, particularly caused by luminous condition change and obstructed vision, without sacrificing real‐time processing capability. A series of indoor and outdoor experiments have been conducted to evaluate the performance under light condition change, occlusion, and haze. Comparative tests showed that the proposed method outperformed other various vision‐based object tracking methods, showing the feasibility for long‐term structural displacement monitoring of full‐scale structures.

Leon‐Medina, Jersson X.; Camacho‐Olarte, Jaiber; Rueda, Bernardo; Vargas, Wilmar; Bonilla, Luis; Ruiz, Janneth; Sofrony, Jorge; Guerra‐Gomez, John A.; Restrepo‐Calle, Felipe; Tibaduiza, Diego A.

doi: 10.1002/stc.2885

Yuan, Cheng; Wang, Shuyin; Qi, Yanzhi; Kong, Qingzhao

doi: 10.1002/stc.2899pmid: N/A

As one of the most common coupling elements in infrastructures, bolted joints play an important part in ensuring the integrity and safety of the whole system, whose failure may cause disastrous consequences. In recent years, precise detection and evaluation of bolt looseness have attracted numerous researchers' interest. However, the reliability of existing methods cannot be well guaranteed in long‐term field detection, and real‐time feedback is rather costly. This paper proposes a novel bolt looseness detection method based on audio recognition and deep learning. Firstly, a percussion experiment was designed to collect audio signals of bolts at different torque levels. Then, the time‐domain bolt percussion signals were converted into Mel‐frequency spectrograms, and the convolutional neural network (CNN) was adopted to mining deep information from the images for classification. To further verify the effect of different initial prestress levels on the vibration frequency of the bolted joint, a numerical study was conducted with the consideration of three different prestress levels. The results reveal that the proposed method has a high recognition accuracy in identifying bolt looseness conditions. Additionally, an iOS APP of acoustic vibration was established for real application. The prerecorded and untrained percussion audio was used to simulate the real‐time bolt looseness detection, which shows its potential in real future applications.

Cao, Liyuan; Li, Chunxiang

doi: 10.1002/stc.2887pmid: N/A

This paper proposes a novel high performance hybrid passive base‐isolated system integrating the base‐isolated system (BIS) with the tuned tandem mass damper inerters (TTMDI), referred to as the BIS+TTMDI. To reveal the interaction between two components and their integrated control performance, the proposed configuration is modeled by a simplified four degree‐of‐freedom model together taking the dynamic characteristics of the isolation system, TTMDI, and superstructure into inclusion. Employing the optimization criterion defined as minimization of the dimensionless variance of superstructure displacement relative to the ground and by resorting to the particle swarm optimization, the system parameters of TTMDI are tuned to get their best integrated control performance. Evaluations are in turn unfolded on the performance taking into diverse TTMDI inertial properties and different isolation layer characteristics account and robustness, to fully explore the effectiveness of reducing both the displacement and acceleration for the isolation layer and superstructure, the TTMDI's energy dissipation mechanism and capacity, evolution of stiffness and damping, stroke, and structural frequency response. Subsequently, the findings of the BIS+TTMDI in the frequency domain is further tested via the time history analyses using the real records including both near‐field with pulse and far‐field earthquakes. In two analysis domains, the integrated performance of the proposed BIS+TTMDI is compared not only to the BIS but also to the BIS+TMDI, as well as to the BIS+TTMD and BIS+TMD. Results confirm that the BIS+TTMDI is a high performance system, namely, with high control effectiveness, high robustness, highly smaller stroke, and drastically reduced damping demand.

Ümütlü, Rafet Can; Bidikli, Baris; Ozturk, Hasan

doi: 10.1002/stc.2893pmid: N/A

The design of a novel backstepping controller for using with active tuned mass damper (ATMD) system is investigated in this study. The main aim of this study is to design the controller for the ATMD system to reduce earthquake‐induced vibrations in multistory buildings. Obtaining a generalizable control design for such systems is another important aim of this study. To reach this aim, the designed controller is based on the assumption that the system parameters are completely uncertain. The parametric uncertainty is coped with via adaptive compensation rules proposed in accordance with available system states. Effects of the control force on the displacement of the controller mass and the last floor of a multistory building are considered together. Owing to this approach, a control operation is provided in which zero convergence of the displacement of the mass of ATMD and all floors of the building can be guaranteed. Using Lyapunov‐based arguments, theoretically, it has been proven that the designed controller can maintain its stability of the structure and controller mass while achieving this main control objective. The efficiency of the designed controller in terms of reaching the mentioned control objective is observed via numerical simulations. In these simulations, the designed controller is used in conjunction with an ATMD system placed on a multistory building model, and it has been shown that the controller designed in such structures can be used effectively for damping the earthquake‐induced vibrations of these types of structures.

Kleingesinds, Shalom; Lavan, Oren

doi: 10.1002/stc.2901pmid: N/A

Current research on tall buildings design has shown the need for multi‐hazard approaches in numerous practical cases. To improve the performance under hazard‐related horizontal loads, supplemental damping devices emerge as an efficient solution. For example, passive tuned massive dampers (TMDs) have been used in tall buildings for decades. However, since earthquakes and winds mobilize the structures in different ways, the multi‐hazard design of TMDs remains a difficult task. Thus, adaptive devices are an encouraging solution for this purpose. This research proposes an efficient use of existing semi‐active TMDs that were proposed for other purposes through tuning them exclusively to two sets of frequency and damping ratio: a set for seismic loads and a set for wind loads. These bi‐tuned STMDs would behave as passive dampers during any hazard event, but with an appropriate tuning. Because mechanical properties switch only at the beginning and at the end of seismic events, the control system required would be simple and reliable. An optimization‐based methodology is proposed to design multiple BSTMDs. The total added mass is minimized, while the building life‐cycle cost (LCC) is selected as a performance constraint. An efficient gradient‐based algorithm, originally developed for passive TMDs, is adapted for BSTMDs. Two problem formulations are proposed, to allow distinct design alternatives. The devices design is illustrated by four case studies. The examples show that BSTMDs may provide the same performance of their passive counterparts, using less than half of their total added mass.