Paper
1 April 2010 Experimental research on crack damage detection of concrete beam based on PZT wave method
Yanyu Meng, Shi Yan, Wei Sun, Naizhi Zhao, Gong Qiu
Author Affiliations +
Abstract
Concrete cracks which are gradually extended, damaged and destructed by the load have become difficult to be solved in engineering. Due to the advantages of convenient production, high sensitivity, reasonable performance-price ratio, selfsensing, piezoelectric ceramic (such as PZT) smart aggregates used as sensor and actuator are embedded in the reinforced concrete beams to generate sin-sweep excitation signals on-line and detect real-time signals with digital oscilloscope before and after damage. The optimal extraction damage signals are extracted and statistical pattern recognition algorithm of wavelet decomposition about the detection signals is established by wavelet analysis and statistical characteristics analysis. The statistical distribution of signal amplitude and the relevant damage indicators are proposed for the use of active health monitoring and energy damage principles. The results of loading tests show that the amplitude of active monitoring signal produced a larger attenuation after damage and sweep wave signals used in active health monitoring are effective in identifying the different health status of structure. The statistical pattern recognition algorithm based on wavelet packet decomposition can effectively detect crack damages of concrete structure. This technology may open a new road for active and permanent monitoring and damage detection on line as well as development of active health monitoring system based on probability statistics of piezoelectric concrete.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yanyu Meng, Shi Yan, Wei Sun, Naizhi Zhao, and Gong Qiu "Experimental research on crack damage detection of concrete beam based on PZT wave method", Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, 76473P (1 April 2010); https://doi.org/10.1117/12.847495
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Signal detection

Wavelets

Signal attenuation

Sensors

Statistical analysis

Damage detection

Ferroelectric materials

Back to Top