Crack identification in concrete structures using implantable sensors. (October 2022)

• Record Type: Journal Article
• Authors: Yang, Ziqian; Chen, Qingjun; Li, Xiuquan; Chen, Hongbing; Wang, Zixin; Huang, Ruitao; Kong, Qingzhao
• Is Part Of: Measurement. Volume 202(2022)
• Publication Date: 2022-10
• Subjects: Concrete implantable module -- Spherical piezoceramic shell -- Concrete crack identification -- Structural health monitoring; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.111780
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A new structure-transducer installation method for monitoring of concrete structural health by using a designed multi-transducer integrated module is proposed. A CIM that can generate superimposing probing signals is designed. The CIM can be implanted into a host structure to sample data and be removed for updating. Four data fusion-based damage indices are developed to quantify structural security. Abstract: Although current sensing techniques have made remarkable achievements in solving many practical structural health monitoring problems, there exists a long-standing problem, that is, field sensors and systems cannot be easily deployed on concrete structures for sustainable and long-term monitoring owing to complex environmental impacts. This study investigates the development of an implantable sensor for crack identification in concrete. A multi-transducer integrated concrete implantable module (CIM) with the appearance of a wall socket is designed to provide a stress-wave scanning ability in concrete. A spherical piezoceramic shell (SPS) array with a diamond shape is embedded in the CIM that enables probing-signal energies to superimpose at the module surface. The functionality and performance of the CIM are studied numerically and experimentally. Four wavelet-packet-based damage indices are proposed to combine the data received for a comprehensive description of the degree of structural damage. The results show that the Euclidean distance yields the best positive linear correlation relative to the crack depths, and the Manhattan and Chebyshev distances have the potential to indicate the initial cracking process.