Special Issue on: "Data-driven Structural Damage Identification and Performance Assessment"
Prof. Ying Lei, Xiamen University, China
Prof. Ling Yu, Jinan University, China
Prof. Hua-Peng Chen, University of Greenwich, UK
Vibration-based structural damage identification (SDI) algorithms have been recognised and intensely studied as promising tools for monitoring structural conditions, detecting structural damage and assessing structural performance from a vast amount of monitoring data.
One of the main categories of such algorithms is data-driven SDI techniques, which extract features from measured data, identify structural damage and assess structural performance when manually or automatically interpreting the significance of potential changes in these features.
This special issue will present theoretical, computational and experimental work on data-driven structural damage identification and performance assessment technologies with possible applications in a wide range of engineering structures.
Suitable topics include, but are not limited, to the following:
- Data-driven structural identification
- Structural damage detection
- Structural model updating
- Structural performance assessment
- Moving load
- Signal processing techniques
- Sensors and instrumentation
- Laboratory and in-field applications
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper).
All papers are refereed through a peer review process.
All papers must be submitted online. To submit a paper, please read our Submitting articles page.
Manuscripts due by: 1 August, 2018