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Item type:Publication, Access status: with files , Mobile structural health monitoring based on legged robots(Multidisciplinary Digital Publishing Institute (MDPI), 2023-09-15); ; ; With the advancements in information, communication, and sensing technologies, structural health monitoring (SHM) has matured into a substantial pillar of infrastructure maintenance. In particular, wireless sensor networks have gradually been incorporated into SHM, leveraging new opportunities towards reduced installation efforts and enhanced flexibility and scalability, as compared to cable-based SHM systems. However, wireless sensor nodes are installed at fixed locations and need to be employed at high density to reliably monitor large infrastructure, which may cause high installation costs. Furthermore, the limited power autonomy of wireless sensor networks, installed at fixed locations for unattended long-term operation, still represents a significant constraint when deploying stationary wireless sensor nodes for SHM. To resolve the critical constraints stemming from costly high-density deployment and limited power autonomy, a mobile structural health monitoring concept based on legged robots is proposed in the study reported in this paper. The study explores the accuracy and cost-efficiency of deploying legged robots in dense measurement setups for wireless SHM of civil infrastructure, aiming to gain insights into the advantages of mobile wireless sensor nodes in general and of legged robots in particular, in terms of obtaining rich information on the structural condition. As is shown in this paper, the legged robots, as compared to stationary wireless sensor nodes, require a smaller number of nodes to be deployed in civil infrastructure to achieve rich sensor information, entailing more cost-efficient, yet accurate, SHM. In conclusion, this study represents a first step towards autonomous robotic fleets advancing structural health monitoring.Publicationtype: Journal ArticleScopus© Citations 1 8 83 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adaptive fault diagnosis for simultaneous sensor faults in structural health monitoring systems(Multidisciplinary Digital Publishing Institute (MDPI), 2023-02-22); ; ; Structural health monitoring (SHM) is a non-destructive testing method that supports the condition assessment and lifetime estimation of civil infrastructure. Sensor faults may result in the loss of valuable data and erroneous structural condition assessments and lifetime estimations, in the worst case with structural damage remaining undetected. As a result, the concepts of fault diagnosis (FD) have been increasingly adopted by the SHM community. However, most FD concepts for SHM consider only single-fault occurrence, which may oversimplify actual fault occurrences in real-world SHM systems. This paper presents an adaptive FD approach for SHM systems that addresses simultaneous faults occurring in multiple sensors. The adaptive FD approach encompasses fault detection, isolation, and accommodation, and it builds upon analytical redundancy, which uses correlated data from multiple sensors of an SHM system. Specifically, faults are detected using the predictive capabilities of artificial neural network (ANN) models that leverage correlations within sensor data. Upon defining time instances of fault occurrences in the sensor data, faults are isolated by analyzing the moving average of individual sensor data around the time instances. For fault accommodation, the ANN models are adapted by removing faulty sensors and by using sensor data prior to the occurrence of faults to produce virtual outputs that substitute the faulty sensor data. The proposed adaptive FD approach is validated via two tests using sensor data recorded by an SHM system installed on a railway bridge. The results demonstrate that the proposed approach is capable of ensuring the accuracy, reliability, and performance of real-world SHM systems, in which faults in multiple sensors occur simultaneously.Publicationtype: Journal ArticleScopus© Citations 8 75 154 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Holistic simulation approach for optimal operation of smart integrated energy systems under consideration of resilience, economics and sustainability(Multidisciplinary Digital Publishing Institute (MDPI), 2021-10-23); ; ; ; The intermittent energy supply from distributed resources and the coupling of different energy and application sectors play an important role for future energy systems. Novel operational concepts require the use of widespread and reliable Information and Communication Technology (ICT). This paper presents the approach of a research project that focuses on the development of an innovative operational concept for a Smart Integrated Energy System (SIES), which consists of a physical architecture, ICT and energy management strategies. The cellular approach provides the architecture of the physical system in combination with Transactive Control (TC) as the system’s energy management framework. Independent dynamic models for each component, the physical and digital system, operational management and market are suggested and combined in a newly introduced co-simulation platform to create a holistic model of the integrated energy system. To verify the effectiveness of the operational concept, energy system scenarios are derived and evaluation criteria are suggested which can be employed to evaluate the future system operations.Publicationtype: Journal ArticleScopus© Citations 7 243 279 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Optimal temperature-based condition monitoring system for wind turbines(Multidisciplinary Digital Publishing Institute (MDPI), 2021-03-26); ; ; ; With the increasing demand for the efficiency of wind energy projects due to challenging market conditions, the challenges related to maintenance planning are increasing. In this paper, a condition-based monitoring system for wind turbines (WTs) based on data-driven modeling is proposed. First, the normal condition of the WTs key components is estimated using a tailor-made artificial neural network. Then, the deviation of the real-time measurement data from the estimated values is calculated, indicating abnormal conditions. One of the main contributions of the paper is to propose an optimization problem for calculating the safe band, to maximize the accuracy of abnormal condition identification. During abnormal conditions or hazardous conditions of the WTs, an alarm is triggered and a proposed risk indicator is updated. The effectiveness of the model is demonstrated using real data from an offshore wind farm in Germany. By experimenting with the proposed model on the real-world data, it is shown that the proposed risk indicator is fully consistent with upcoming wind turbine failures.Publicationtype: Journal ArticleScopus© Citations 11 208 167 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , BIM-based description of intelligent transportation systems for roadsIntelligent transportation systems (ITS) provide safer, greener, and more convenient mobility, while reducing the impact on the environment. In recent years, simulation platforms have been employed to study ITS applications, mostly focusing on traffic-related simulations. Despite several research studies on ITS applications and simulation platforms, formal semantic descriptions of intelligent transportation systems have not been addressed yet. In this paper, a semantic model describing intelligent transportation systems for roads is proposed. The semantic model is devised to provide a basis for designing ITS simulation platforms. Building upon the semantic model, an extension to an open building information modeling (BIM) standard, i.e., the Industry Foundation Classes (IFC) schema, is presented. The IFC schema extension is verified and validated using a BIM-based simulation scenario of ITS for roads. It is shown that the proposed IFC-compliant description of ITS for roads provides a formal basis for generating BIM-based simulations and hence facilitates ITS infrastructure modeling in BIM projects. It is concluded that the present work represents a cornerstone for designing BIM-based ITS simulation platforms. In future endeavors, potential standardization and formalization efforts may be discussed.Publicationtype: Journal ArticleScopus© Citations 8 159 642 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Maturity improvements in flood protection asset management across the North Sea Region(Multidisciplinary Digital Publishing Institute (MDPI), 2020-12-10); ; ; ; North Sea Region countries depend heavily on flood protection infrastructure, such as dikes, dams, sluices and flood gates. Knowledge on where, when and how much to invest to ensure functioning is of crucial importance for asset owners and operators. This requires asset management approaches that are adaptable, respond to feedback and function within various contexts. The FAIR (Flood defense infrastructure Asset management & Investment in Renovation, adaptation, optimisation and maintenance) project has developed a unique framework to ensure that asset management processes are adaptive, comprehensive and make effective connections across strategic, tactical and operational contexts. The framework has for the first time informed an assessment of maturity of five flood protection asset management organisations in the North Sea Region, using a seven-factor maturity assessment model. This paper describes the self-assessment process and the self-reported maturity changes during the project. Maturity assessments were undertaken on two occasions, at the start of the project, and again toward the end. This has revealed how the baseline level of maturity for each organisation developed over the course of the three-year project. The observed maturity changes indicate that adopting the FAIR framework has added value in improving current approaches to asset management.Publicationtype: Journal ArticleScopus© Citations 4 181 184 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adaptive asset management for flood protection: The FAIR framework in action(Multidisciplinary Digital Publishing Institute (MDPI), 2020-12-03); ; ; ; Uncertainties about climate change consequences, changing societal requirements and system complexity require flood protection asset managers to continuously evaluate their asset management policies and practice to manage risk and improve the resilience of their assets. However, there are many challenges in doing this, with asset operators often facing conflicting interests and major uncertainties about the future needs for asset performance. In the EU Interreg IV FAIR project, flood protection asset owners and operators, with scientific partners from the North Sea Region of Europe collaborated to develop practical guidance for adaptive asset management of flood protection infrastructure. The central component of this guidance is the FAIR framework, presented here. The framework combines insights and principles from ISO 55000 on asset management and ISO 14090 on climate adaptation with asset operator experiences to provide a practical guide for integration of asset management considerations within both strategic and operational contexts via a tactical handshake. This is a means to avoid the common lack of connection between strategic plans and operational practice. The applicability of the framework is illustrated with examples from Pilot Cases within the FAIR project, in which its value in terms of improved asset management and reduced costs has been demonstrated.Publicationtype: Journal ArticleScopus© Citations 9 185 188