Early Age Concrete Strength Monitoring Using Power Spectral Density and Wavelet Packet Analysis
Auteur(s): |
Xia Yang
Wenwei Yang Shuntao Li Chang Wu |
---|---|
Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Advances in Civil Engineering, janvier 2020, v. 2020 |
Page(s): | 1-11 |
DOI: | 10.1155/2020/8837128 |
Abstrait: |
Concrete is a complex building material. Under normal curing conditions, concrete strength shows a nonlinear development process at an early age (1∼28 d). In the first few days after the completion of pouring, the strength of concrete increases slowly. Subsequently, the strength of concrete increases rapidly, reaching about 90% of its age strength. Finally, its strength gradually stabilizes. This paper introduces the experiment of 28-day concrete age strength monitoring based on embedded piezoelectric smart aggregate (SA). Two piezoelectric SAs were embedded in a concrete-filled GFRP (glass fiber reinforced polymer) tube column, one of which emitted a sinusoidal sweep signal and the other SA received the signal. With the hydration reaction of concrete, the stress wave would be significantly different when passing through concrete, and the received signal is changing constantly. Through power spectral density and wavelet packet energy analysis, the monitoring signal of concrete age within 28 days was analyzed. The experimental results show that the wavelet packet energy and power spectral density of the sensor monitoring signal show a nonlinear growth trend with time during the concrete target age. It can be divided into three stages, and the fifth day and the fourteenth day are the demarcation point of energy growth. And the trend of energy change corresponds well with the change of actual concrete strength and age. Comparing and analyzing the received signal energy of the sensor and the power spectral density function of the stress wave signal of the concrete specimen, the trend of the amplitude in the natural frequency domain is found to be the same in the three stages. |
Copyright: | © Xia Yang et al. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
3.74 MB
- Informations
sur cette fiche - Reference-ID
10526003 - Publié(e) le:
11.12.2020 - Modifié(e) le:
02.06.2021