Tendons and cables are used in civil structures as tensioning members in prestressed concrete, cable-stayed bridges and suspension bridges. Monitoring the structural performance of these components is important to ensure the proper functioning and safety of the entire structure. Among the various NDE techniques for monitoring tendons and cables, the use of acoustic guided waves shows good promises. One attractive outcome of the guided wave technique is the possibility of detecting defects and monitoring applied loads simultaneously. In the present work, defects examined include indentations in ungrouted and grouted tendons made of sevenwire steel strands. Magnetostrictive sensors are employed to generate and detect the guided waves. In addition, the technique is improved by implementing the Discrete Wavelet Transform (DWT) as a data post-processing tool. The data de-noising ability of the DWT allows for greater sensitivity, larger ranges and higher testing speed. It is shown that the implementation of the DWT in the acoustic guided-wave technique becomes necessary for monitoring tendons and cables in the field.
Guided acoustic waves for health monitoring of tendons and cables
MARZANI, ALESSANDRO
2004
Abstract
Tendons and cables are used in civil structures as tensioning members in prestressed concrete, cable-stayed bridges and suspension bridges. Monitoring the structural performance of these components is important to ensure the proper functioning and safety of the entire structure. Among the various NDE techniques for monitoring tendons and cables, the use of acoustic guided waves shows good promises. One attractive outcome of the guided wave technique is the possibility of detecting defects and monitoring applied loads simultaneously. In the present work, defects examined include indentations in ungrouted and grouted tendons made of sevenwire steel strands. Magnetostrictive sensors are employed to generate and detect the guided waves. In addition, the technique is improved by implementing the Discrete Wavelet Transform (DWT) as a data post-processing tool. The data de-noising ability of the DWT allows for greater sensitivity, larger ranges and higher testing speed. It is shown that the implementation of the DWT in the acoustic guided-wave technique becomes necessary for monitoring tendons and cables in the field.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
