A Framework for Optimal Sensor Placement to Support Structural Health Monitoring

被引:8
|
作者
Li, Shen [1 ]
Coraddu, Andrea [2 ]
Brennan, Feargal [1 ]
机构
[1] Univ Strathclyde, Dept Naval Architecture Ocean & Marine Engn, Glasgow City G1 1XQ, Scotland
[2] Delft Univ Technol, Fac Mech Maritime & Mat Engn, NL-2600 AA Delft, Netherlands
关键词
structural health monitoring; optimisation; structural integrity; evolutionary algorithm; stress concentration; FATIGUE DAMAGE; MODEL; OPTIMIZATION;
D O I
10.3390/jmse10121819
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Offshore or drydock inspection performed by trained surveyors is required within the integrity management of an in-service marine structure to ensure safety and fitness for purpose. However, these physical inspection activities can lead to a considerable increase in lifecycle cost and significant downtime, and they can impose hazards for the surveyors. To this end, the use of a structural health monitoring (SHM) system could be an effective resolution. One of the key performance indicators of an SHM system is its ability to predict the structural response of unmonitored locations by using monitored data, i.e., an inverse prediction problem. This is highly relevant in practical engineering, since monitoring can only be performed at limited and discrete locations, and it is likely that structurally critical areas are inaccessible for the installation of sensors. An accurate inverse prediction can be achieved, ideally, via a dense sensor network such that more data can be provided. However, this is usually economically unfeasible due to budget limits. Hence, to improve the monitoring performance of an SHM system, an optimal sensor placement should be developed. This paper introduces a framework for optimising the sensor placement scheme to support SHM. The framework is demonstrated with an illustrative example to optimise the sensor placement of a cantilever steel plate. The inverse prediction problem is addressed by using a radial basis function approach, and the optimisation is carried out by means of an evolutionary algorithm. The results obtained from the demonstration support the proposal.
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页数:14
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