Value of Information analysis accounting for data quality
Giordano, Pier Francesco ; Quqa, Said and Limongelli, Maria Pina LU
(2023)
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023
In Proceedings of SPIE - The International Society for Optical Engineering
12486.
- Abstract
Structural Health Monitoring (SHM) can provide valuable information for maintenance-related activities and post-disaster emergency management. However, as with any technological system, SHM systems can be susceptible to errors due to malfunctioning. Therefore, it is essential to assess the potential for malfunctions and the associated costs of maintenance and repair when evaluating the long-term benefits of SHM systems. In the last two decades, sensor validation tools (SVTs) have been proposed to support decisions by isolating and discarding abnormal data. Recently, the authors of this paper have proposed a framework based on the Value of Information (VoI) from Bayesian decision analysis to account for different states of an SHM system... (More)
Structural Health Monitoring (SHM) can provide valuable information for maintenance-related activities and post-disaster emergency management. However, as with any technological system, SHM systems can be susceptible to errors due to malfunctioning. Therefore, it is essential to assess the potential for malfunctions and the associated costs of maintenance and repair when evaluating the long-term benefits of SHM systems. In the last two decades, sensor validation tools (SVTs) have been proposed to support decisions by isolating and discarding abnormal data. Recently, the authors of this paper have proposed a framework based on the Value of Information (VoI) from Bayesian decision analysis to account for different states of an SHM system and assess the benefit of SVT information. By quantifying the additional value obtained from SVTs, decision-makers can make more informed decisions about investing in these systems. This framework is here demonstrated on a real case study, namely the S101 bridge in Austria, which has been artificially damaged for research purposes. The benefit of collecting SHM and SVT information is quantified by considering a simple decision problem related to the management of the bridge in the aftermath of a damaging event. Overall, the study highlights the potential benefits of using SVTs to improve the reliability of SHM data and inform decision-making in the management of structures.
(Less)
- author
- Giordano, Pier Francesco
; Quqa, Said
and Limongelli, Maria Pina
LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Bayesian decision theory, Data quality, Sensor fault, Sensor Validation Tool, Structural Health Monitoring, Value of Information
- host publication
- Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023
- series title
- Proceedings of SPIE - The International Society for Optical Engineering
- editor
- Su, Zhongqing ; Glisic, Branko and Limongelli, Maria Pina
- volume
- 12486
- article number
- 1248613
- publisher
- SPIE
- conference name
- Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023
- conference location
- Long Beach, United States
- conference dates
- 2023-03-13 - 2023-03-16
- external identifiers
-
- scopus:85159963287
- ISSN
- 1996-756X
- 0277-786X
- ISBN
- 9781510660793
- DOI
- 10.1117/12.2657933
- language
- English
- LU publication?
- yes
- id
- aeeb789a-1dc0-4da3-b660-c80b8d3df4f3
- date added to LUP
- 2023-09-25 10:09:17
- date last changed
- 2024-04-19 01:34:51
@inproceedings{aeeb789a-1dc0-4da3-b660-c80b8d3df4f3,
abstract = {{<p>Structural Health Monitoring (SHM) can provide valuable information for maintenance-related activities and post-disaster emergency management. However, as with any technological system, SHM systems can be susceptible to errors due to malfunctioning. Therefore, it is essential to assess the potential for malfunctions and the associated costs of maintenance and repair when evaluating the long-term benefits of SHM systems. In the last two decades, sensor validation tools (SVTs) have been proposed to support decisions by isolating and discarding abnormal data. Recently, the authors of this paper have proposed a framework based on the Value of Information (VoI) from Bayesian decision analysis to account for different states of an SHM system and assess the benefit of SVT information. By quantifying the additional value obtained from SVTs, decision-makers can make more informed decisions about investing in these systems. This framework is here demonstrated on a real case study, namely the S101 bridge in Austria, which has been artificially damaged for research purposes. The benefit of collecting SHM and SVT information is quantified by considering a simple decision problem related to the management of the bridge in the aftermath of a damaging event. Overall, the study highlights the potential benefits of using SVTs to improve the reliability of SHM data and inform decision-making in the management of structures.</p>}},
author = {{Giordano, Pier Francesco and Quqa, Said and Limongelli, Maria Pina}},
booktitle = {{Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023}},
editor = {{Su, Zhongqing and Glisic, Branko and Limongelli, Maria Pina}},
isbn = {{9781510660793}},
issn = {{1996-756X}},
keywords = {{Bayesian decision theory; Data quality; Sensor fault; Sensor Validation Tool; Structural Health Monitoring; Value of Information}},
language = {{eng}},
publisher = {{SPIE}},
series = {{Proceedings of SPIE - The International Society for Optical Engineering}},
title = {{Value of Information analysis accounting for data quality}},
url = {{http://dx.doi.org/10.1117/12.2657933}},
doi = {{10.1117/12.2657933}},
volume = {{12486}},
year = {{2023}},
}