Structural Health Monitoring (SHM) is the monitoring of any type of structure for the express purpose of determining its condition and future lifespan and if, when and where any reparative action is needed. A focus of the work in this thesis is SHM for long-span bridges and particularly the effects of environmental and operational conditions on a monitoring campaign. There is currently a trend for heavily instrumenting civil structures with large sensor networks that continually collect terabytes of data. However, these large data sets are often redundantly stored and not used for anything. One of the principal aims in the thesis is to exploit such monitoring data for the development of diagnostic tools for structural condition assessment. The first part of the thesis concerns formulating a baseline for the Tamar Bridge that represents the normal undamaged condition of the structure. To do this a large amount of analysis was needed in order to understand how different structural measurements are interrelated and how the bridge responds to normal environmental and operational conditions. Particular attention was paid to measurements that can be sensitive to structural degradation (such as modal properties). Often simple causal relationships were found between monitored variables, and response surface models were formulated that could predict selected variables with good accuracy given measurement of operational and environmental conditions, such as air temperature, traffic loading and wind profile. The predictive models developed are intended to be used as diagnostic tools, for example, a departure from the normal condition of the bridge will bring about a significant increase in prediction error, which may be monitored as a system alarm. The second part of the thesis directly concerns how the influence of environmental and operational variation on features sensitive to damage can be lessened or removed without measurement of these conditions themselves. This is a very important issue in SHM, as often the effects of fluctuating environmental and operational conditions can mask any indication of damage to a structure that may be evident in structural response. In the thesis a solution to the problem based on the econometric theory of cointegration is introduced. Application of this theory is found to be ideally suited to remove unwanted environmental and operational trends from SHM data, and forms an exceedingly promising contribution to the development of SHM technology.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:557561 |
| Date | January 2012 |
| Creators | Cross, Elizabeth |
| Contributors | Worden, K. ; Manson, G. |
| Publisher | University of Sheffield |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/2673/ |
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