Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures

被引:138
作者
Kralovec, Christoph [1 ]
Schagerl, Martin [1 ,2 ]
机构
[1] Johannes Kepler Univ Linz, Inst Struct Lightweight Design, A-4040 Linz, Austria
[2] Johannes Kepler Univ Linz, Christian Doppler Lab Struct Strength Control Lig, A-4040 Linz, Austria
关键词
multi-sensor; data fusion; composite; metal; electro-mechanical impedance; guided wave; electrical impedance tomography; carbon nanotube; strain-based SHM; ELECTRICAL-IMPEDANCE TOMOGRAPHY; GUIDED-WAVES; TEMPERATURE; DIAGNOSIS;
D O I
10.3390/s20030826
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Structural health monitoring (SHM) is the continuous on-board monitoring of a structure's condition during operation by integrated systems of sensors. SHM is believed to have the potential to increase the safety of the structure while reducing its deadweight and downtime. Numerous SHM methods exist that allow the observation and assessment of different damages of different kinds of structures. Recently data fusion on different levels has been getting attention for joint damage evaluation by different SHM methods to achieve increased assessment accuracy and reliability. However, little attention is given to the question of which SHM methods are promising to combine. The current article addresses this issue by demonstrating the theoretical capabilities of a number of prominent SHM methods by comparing their fundamental physical models to the actual effects of damage on metal and composite structures. Furthermore, an overview of the state-of-the-art damage assessment concepts for different levels of SHM is given. As a result, dynamic SHM methods using ultrasonic waves and vibrations appear to be very powerful but suffer from their sensitivity to environmental influences. Combining such dynamic methods with static strain-based or conductivity-based methods and with additional sensors for environmental entities might yield a robust multi-sensor SHM approach. For demonstration, a potent system of sensors is defined and a possible joint data evaluation scheme for a multi-sensor SHM approach is presented.
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页数:25
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