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Item type:Publication, Access status: without files , Validation of an ultra-low-cost wireless structural health monitoring system for civil infrastructureStructural health monitoring (SHM) is critical to ensure safety of civil infrastructure, such as bridges, railways, or pipelines. However, existing SHM techniques suffer from high investment, installation, and maintenance cost. This paper presents an ultra-low-cost and easy-to-use wireless SHM system for civil infrastructure, featuring real-time sensing, on-board data analysis, energy-efficient wireless communication, and Internet of Things (IoT) connectivity. To validate its performance, the proposed SHM system is installed at Itztal Bridge, Germany, for monitoring and analyzing quasi-static horizontal deck displacements in response to thermal loads. In parallel to the ultra-low-cost SHM system, a traditional tethered SHM system, also installed at the bridge, is used in this study for direct comparison and validation. As a result, the ultra-low-cost wireless SHM system is shown to be easy-to-install and sufficiently accurate for monitoring and analyzing the behavior of civil infrastructure under static loads, serving as a low-cost yet high-performance diagnostic tool with IoT connectivity.Publicationtype: Conference Paper46 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A support vector regression-based approach towards decentralized fault diagnosis in wireless structural health monitoring systems(2019-10); ; The reliability of sensors in structural health monitoring (SHM) systems is affected by sensor faults that compromise the quality of monitoring, causing erroneous judgment of structural conditions. To ensure reliable operation of SHM systems, techniques for diagnosing sensor faults have been proposed. In wireless SHM systems, embedding techniques for fault diagnosis (FD) into sensor nodes is of increasing importance as sensor nodes process data on board and communicate analysis results instead of large sets of raw data. As a consequence of on-board processing, raw data is frequently unavailable and sensor faults remain undetected. In this paper, a decentralized fault diagnosis approach based on support vector regression (FD-SVR) is proposed. Due to the high accuracy of the support vector regression (SVR), which can be achieved even with relatively small data sets, the FD-SVR approach enables wireless sensor nodes autonomously self-diagnose sensor faults, enhancing the reliability of wireless SHM systems without a need for large data sets to be used for fault diagnosis. The ability of the embedded FD-SVR approach to detect and isolate sensor faults, increasing the reliability of sensors in wireless SHM systems, is validated in laboratory experiments.Publicationtype: Conference Paper43 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A metamodel for cyber-physical systems(2019-08); ; With the advent of the Internet of Things and Industry 4.0 concepts, cyber-physical systems in civil engineering experience an increasing impact on structural health monitoring (SHM)and control applications. Designing, optimizing, and documenting cyber-physical system on a formal basis require platform-independent and technology-independent metamodels. This study, with emphasis on communication in cyber-physical systems, presents a metamodel for describing cyber-physical systems. First, metamodeling concepts commonly used in computing in civil engineering are reviewed and possibilities and limitations of describing communication-related information are discussed. Next, communication-related properties and behavior of distributed cyber-physical systems applied for SHM and control are explained, and system components relevant to communication are specified. Then, the metamodel to formally describe cyber-physical systems is proposed and mapped into the Industry Foundation Classes (IFC), an open international standard for building information modeling (BIM). Finally, the IFC-based approach is verified using software of the official IFC certification program, and it is validated by BIM-based example modeling of a prototype cyber-physical system, which is physically implemented in the laboratory. As a result, cyber-physical systems applied for SHM and control are described and the information is stored, documented, and exchanged on the formal basis of IFC, facilitating design, optimization, and documentation of cyber-physical systems.Publicationtype: Journal Article76 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A semantic model of intelligent transportation systems(2019-06); Intelligent transportation systems, representing core components of smart cities, combine sensing, computing, and wireless communication technologies to provide efficient and convenient mobility. Road intelligent transportation systems (ITS) have been studied in recent decades through simulation platforms that integrate computational models for various use cases, such as traffic lights control and management. However, semantic descriptions, illustrating road ITS as a whole and creating a basis for designing simulation platforms, have not been addressed. In this paper, a semantic model of road intelligent transportation systems is proposed, which describes road ITS components and architecture, serving as a formal basis for road ITS simulation platforms. Building upon the semantic model, an extension of the Industry Foundation Classes schema, facilitating ITS simulation platforms based on building information modeling, is discussed. The paper concludes with a summary, a discussion, and an outlook on potential formalization efforts.Publicationtype: Conference Paper46 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Automated wireless structural health monitoring and control using tuned liquid column dampers(2019-06); ; Current trends in structural design and retrofit frequently dictate artificially modifying the structural behavior in an attempt to target unfavorable loading scenarios expected to compromise the fulfilment of stability and serviceability criteria. Particularly in structures where operational requirements result in adopting unconventional structural systems, usually falling outside the scope of codified regulations and guidelines, adapting the structural behavior by means of structural subsystems has been widespread. Referred to as “structural control”, enhancing the ability of structures to adapt to unfavorable loading conditions encompasses attaching structural subsystems, such as dampers, to the main structure. Moreover, the increasing application of structural health monitoring (SHM) for structural assessment and maintenance has fueled research in coupling SHM with structural control, thus paving the way for developing structural systems capable of autonomously adapting structural properties. In this context, this paper describes a preliminary approach to automated structural health monitoring and control by coupling a wireless SHM system with a tuned liquid column damper (TLCD). The wireless SHM system is equipped with embedded algorithms managing SHM tasks, such as data sampling and data processing, and with actuators able to modify the properties of the TLCD based on any user-defined control algorithm. The proposed approach serves as a first step towards fully automated structural health monitoring and control and is validated through laboratory tests on a four-story shear frame structure equipped with a wireless SHM system and a TLCD on the top story.Publicationtype: Conference Paper54 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A Semantic Model for Wireless Sensor Networks in Cognitive Buildings(2019-06); ; Cognitive buildings, being aware of their own performance, actively learn and adapt to the environment, enhancing comfort and safety of occupants. While the integration of Internet of things (IoT) technology, machine learning, reasoning, and augmented reality into cognitive building concepts has made substantial progress, the integration of structural health monitoring (SHM) and control systems into cognitive buildings has received little attention. In this paper, a semantic model for describing SHM and control systems associated with cognitive buildings is proposed. The semantic model, formally describing SHM and control systems components as well as interrelations between the components, serves as a basis to document, to manage, and to optimize cognitive buildings. Through the semantic model, a laboratory test structure, mimicking a cognitive building, and a prototype SHM and control system, which is installed on the laboratory test structure, are described using building information modeling (BIM). Both the cognitive building and the SHM and control system are physically implemented in the laboratory for validation tests. The results clearly demonstrate the ability of the semantic model to formally describe SHM and control systems associated with cognitive buildings.Publicationtype: Conference Paper58 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Metamodeling wireless communication in cyber-physical systems(2019-06); ; With recent developments in embedded sensing technologies, cyber-physical systems, materializing Industry 4.0 concepts, are increasingly implemented in civil engineering to advance structural health monitoring (SHM) and control applications. Recent studies have shown the potential of metamodels enabling information integration and interoperability between different platforms and technologies, while metamodeling of cyber-physical systems has been scarce. In this study, a metamodel for describing cyber-physical systems, putting emphasis on communication issues, is proposed and implemented into a SHM and control system. The metamodel is mapped into the Industry Foundation Classes (IFC) data schema that is standardized for describing structures compliant to the principles of building information modeling (BIM). Finally, the metamodel proposed in this study is validated by IFC-compliant, BIM-based example modeling and implementation of a cyber-physical system designed to monitor and control a laboratory test structure.Publicationtype: Conference Paper39 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , On-board data synchronization in wireless structural health monitoring systems based on phase lockingWireless sensor networks are prone to synchronization discrepancies, due to the lack of intrinsic global clock management from a centralized server. In wireless structural health monitoring (SHM) systems, synchronization discrepancies may lead to erroneous estimations of structural parameters of monitored structures. To avoid errors in the estimations of structural parameters, structural response data sets collected from a structure must be synchronized. Synchronization between structural response data sets can be achieved through offline processing. However, in wireless SHM systems, offline processing requires wireless communication of entire structural response data sets, which has been proven detrimental to the power autonomy of wireless sensor nodes. This paper presents an embedded synchronization algorithm for wireless SHM systems. The embedded synchronization algorithm functions as a module added to embedded algorithms performing peak picking, which is part of operational modal analysis, for ensuring accurate outcomes. The embedded synchronization algorithm enables wireless SHM systems to synchronize structural response data sets on board using the embedded computing capabilities of wireless sensor nodes. The synchronization is achieved by imposing the expected relationship between the phase angles of Fourier spectra of acceleration response data sets at peaks corresponding to vibration modes. Time lags are autonomously estimated by the wireless sensor nodes through collaborative analysis of the phase angle relationship between acceleration response data sets collected by different sensor nodes. The embedded synchronization algorithm is implemented into a prototype wireless SHM system with embedded peak picking algorithms and validated by laboratory tests and by ambient vibration tests on a pedestrian bridge.Publicationtype: Journal Article85 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , IFC Monitor – An IFC schema extension for modeling structural health monitoring systems(2018-08); The pervasive emergence of sensing technologies for structural health monitoring (SHM) and the digitalization ubiquitous in engineering (“Industry 4.0”) pose increasing demands on information modeling concepts in civil engineering. While in building information modeling (BIM) conventional building information (such as geometry, material, or cost) can precisely be described using current modeling standards, information about SHM systems, referred to as “monitoring-related information” cannot be fully described on a well-defined, formal basis. In this paper, a BIM-based approach towards describing monitoring-related information is proposed, using the Industry Foundation Classes (IFC), an open BIM standard facilitating the interoperability of BIM models, as a formal basis. First, possibilities and constraints of describing monitoring-related information with the IFC schema are discussed. Then, information necessary to describe SHM systems is integrated into a semantic model serving as a technology-independent metamodel. Next, the IFC schema is extended to enable BIM-based descriptions of SHM systems in compliance with IFC modeling capabilities, which is referred to as “IFC Monitor” schema. The IFC Monitor schema is verified with test software used in the official IFC certification program. For validation, a prototype SHM system is formally described using the IFC Monitor schema. The validation aims at checking if the IFC Monitor schema is capable of precisely describing monitoring-related information. As will be shown in this paper, the description of the prototype SHM system meets the requirements of a well-defined IFC model as specified in the official IFC certification program. As a result, the IFC Monitor schema proposed in this study advances BIM-based descriptions of SHM systems in association with structural systems being monitored on a well-defined, formal basis.Publicationtype: Journal Article151 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , An abstract approach towards modeling intelligent structural systems(2018-07); Current design standards have not kept pace with the rapid developments in intelligent sensing technologies. In modern engineering practice, engineering structures and structural health monitoring (SHM) systems are considered one entity, referred to as “intelligent structural system”, which is, however, not reflected in current design standards. Sensor data, obtained by SHM systems, provides valuable information about a structure throughout the life cycle, but sensor information provided by SHM systems is not considered in structural modeling concepts. This paper investigates the integration of sensor-based information into design and modeling concepts for intelligent structural systems on an abstract level. Since every civil engineering structure is built with a specific objective, the SHM system installed on the structure must be designed to maintain the specific objective. For example, stress concentration areas identified during the design of civil engineering structures should be observed by monitoring systems with respect to physical quantities of interest. Moreover, continuous validation of sensor data collected by SHM systems against corresponding design models involves coupling of structural models and SHM systems. Such coupling must be considered in the conceptual design phase. This paper presents an abstract approach towards modeling intelligent structures, with particular emphasis focused on coupling of structural models and SHM systems on a conceptual level. As a result, components of intelligent structures are described using an abstract algebraic approach, as illustrated on an intelligent structural system in laboratory experiments.Publicationtype: Conference Paper33