Effects of environmental and operational variability on structural health monitoring
Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affec...
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| Published in | Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences Vol. 365; no. 1851; pp. 539 - 560 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
London
The Royal Society
15.02.2007
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1364-503X 1471-2962 |
| DOI | 10.1098/rsta.2006.1935 |
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| Abstract | Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization. |
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| AbstractList | Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization. Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization. Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization.Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization. |
| Author | Sohn, Hoon |
| Author_xml | – sequence: 1 givenname: Hoon surname: Sohn fullname: Sohn, Hoon email: hsohn@andrew.cmu.edu organization: Civil and Environmental Engineering Department, Carnegie Mellon University Pittsburgh, PA 15213, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/17255051$$D View this record in MEDLINE/PubMed |
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| Snippet | Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based
on measured dynamic or static... Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static... |
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| SubjectTerms | Algorithms Bridge engineering Bridges Computer Simulation Construction Materials - analysis Damage Detection Data Normalization Datasets Engineering - instrumentation Engineering - methods Environment Environmental And Operational Variation Environmental disorders Environmental Monitoring - instrumentation Environmental Monitoring - methods Equipment Design Equipment Failure Analysis - instrumentation Equipment Failure Analysis - methods Facility Design and Construction - instrumentation Facility Design and Construction - methods Maintenance - methods Materials Testing - methods Mathematical vectors Models, Theoretical Novelty detection Principal components analysis Signal Processing, Computer-Assisted Structural health monitoring Transducers Vibration |
| Title | Effects of environmental and operational variability on structural health monitoring |
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