Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Elizabeth J. Cross"'
Publikováno v:
Sensors, Vol 24, Iss 12, p 3879 (2024)
Various approaches have been proposed for bridge structural health monitoring. One of the earliest approaches proposed was tracking a bridge’s natural frequency over time to look for abnormal shifts in frequency that might indicate a change in stif
Externí odkaz:
https://doaj.org/article/f05a6b5b844341449d4861cea756e0df
Autor:
Elizabeth J. Cross, Timothy J. Rogers, Daniel J. Pitchforth, Samuel J. Gibson, Sikai Zhang, Matthew R. Jones
Publikováno v:
Data-Centric Engineering, Vol 5 (2024)
Despite the growing availability of sensing and data in general, we remain unable to fully characterize many in-service engineering systems and structures from a purely data-driven approach. The vast data and resources available to capture human acti
Externí odkaz:
https://doaj.org/article/d8ad6890e06b4b26a9e13bccb43d7e64
Autor:
Connor O’Higgins, David Hester, Patrick McGetrick, Elizabeth J. Cross, Wai Kei Ao, James Brownjohn
Publikováno v:
Sensors, Vol 23, Iss 14, p 6328 (2023)
Structural Health Monitoring (SHM) is a technique that involves gathering information to ensure that a structure is safe and behaving as expected. Within SHM, vibration-based monitoring is generally seen as one of the more cost-effective types of mon
Externí odkaz:
https://doaj.org/article/92d6c8a1f3714fb092d9f695fc14d69b
Publikováno v:
Data-Centric Engineering, Vol 3 (2022)
Population-based structural health monitoring (PBSHM) provides a means of accounting for inter-turbine correlations when solving the problem of wind farm anomaly detection. Across a wind farm, where a group of structures (turbines) is placed in close
Externí odkaz:
https://doaj.org/article/fbf2a961e433495f9baba40b530675e0
Autor:
Keith Worden, Lawrence A. Bull, Paul Gardner, Julian Gosliga, Timothy J. Rogers, Elizabeth J. Cross, Evangelos Papatheou, Weijiang Lin, Nikolaos Dervilis
Publikováno v:
Frontiers in Built Environment, Vol 6 (2020)
One of the main problems in data-based Structural Health Monitoring (SHM), is the scarcity of measured data corresponding to damage states in the structures of interest. One approach to solving this problem is to develop methods of transferring healt
Externí odkaz:
https://doaj.org/article/5339ca2873814118bdb2ef8f179d6bfc
Publikováno v:
Lecture Notes in Civil Engineering ISBN: 9783031072574
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ea1c9accdda15855867482732682561
https://doi.org/10.1007/978-3-031-07258-1_110
https://doi.org/10.1007/978-3-031-07258-1_110
Publikováno v:
Lecture Notes in Civil Engineering ISBN: 9783031072574
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::501608fc7361d8c55a4fb8ecdd8da3ce
https://doi.org/10.1007/978-3-031-07258-1_100
https://doi.org/10.1007/978-3-031-07258-1_100
Autor:
Elizabeth J. Cross, Timothy J. Rogers
Publikováno v:
IFAC-PapersOnLine. 54:168-173
This paper attempts to bridge the gap between standard engineering practice and machine learning when modelling stochastic processes. For a number of physical processes of interest, derivation of the (auto)covariance is achievable. This paper suggest
Autor:
Carles Campos, Elizabeth J. Cross, Timothy J. Rogers, Keith Worden, L.A. Bull, Paul Gardner, Nikolaos Dervilis, A.E. Maguire, Evangelos Papatheou
Power curves capture the relationship between wind speed and output power for a specific wind turbine. Accurate regression models of this function prove useful in monitoring, maintenance, design, and planning. In practice, however, the measurements d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d45d67039f39ffed6de136cb373fb3df
Autor:
Rajdip Nayek, Mohamed Anis Ben Abdessalem, Nikolaos Dervilis, Elizabeth J. Cross, Keith Worden
Publikováno v:
Nonlinear Structures & Systems, Volume 1 ISBN: 9783031040856
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe8b6ff6d66a36f8722b903d8f889559
https://doi.org/10.1007/978-3-031-04086-3_23
https://doi.org/10.1007/978-3-031-04086-3_23