Experimental study on axial compression monitoring of pile foundation based on sensor-enabled piezoelectric geocable
Autor(en): |
Haokang Ying
Zhiming Liu Jun Wang Guangya Ding Hangyu Wang Junfeng Ni Ziyang Gao |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Smart Materials and Structures, 19 Oktober 2023, n. 11, v. 32 |
Seite(n): | 115003 |
DOI: | 10.1088/1361-665x/acfad7 |
Abstrakt: |
In concealed underground projects, pile foundations may cause severe engineering accidents owing to factors such as construction technology, geological conditions, and material properties. Accordingly, the construction industry has invariably focused on developing high-precision, distributed, and low-cost monitoring and disaster warning methods. Therefore, a new sensing material, sensor-enabled piezoelectric geocable (SPGC), was developed to monitor the deformation and failure of a pile foundation. Three model piles were constructed, and packaging and layout processes for the SPGC sensing material were proposed. Moreover, a fiber Bragg grating (FBG) sensor and resistance strain gauge were installed for comparison. Pile foundation failure and static load tests were performed using a large servo hydraulic press. The monitored effect was evaluated by obtaining the impedance and voltage signals of the SPGC. Pile foundation failure test results show that the mutation of impedance and voltage signals can be used as combined monitoring data, and the electrical signal of the SPGC can be used in three stages of early warning response. These findings ensure that pile foundation damage can be located, damage precursors can be identified, and timely warning can be provided. The static load test results indicate that the SPGC data are in good agreement with the FBG sensor and strain gauge data. The impedance of the SPGC increases linearly with the load. Accordingly, a linear calculation formula relating impedance and strain is derived. The research results are expected to provide a new technical method for pile foundation construction and long-term operation and maintenance monitoring. |
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Datenseite - Reference-ID
10742617 - Veröffentlicht am:
28.10.2023 - Geändert am:
28.10.2023