Concrete-filled fiber-reinforced polymer tubes (CFFTs) have attracted interest for their structural applications in corrosive environments. However, a weak interfacial strength between the fiber-reinforced polymer (FRP) tube and the concrete infill may develop due to concrete shrinkage and inadequate concrete compaction during concrete casting, which will destroy the confinement effect and thereby reduce the load bearing capacity of a CFFT. In this paper, the lead zirconate titanate (PZT)-based ultrasonic time-of-flight (TOF) method was adopted to assess the concrete infill condition of CFFTs. The basic idea of this method is that the velocity of the ultrasonic wave propagation in the FRP material is about half of that in concrete material. Any voids or debonding created along the interface between the FRP tube and the concrete will delay the arrival time between the pairs of PZT transducers. A comparison of the arrival times of the PZT pairs between the intact and the defected CFFT was made to assess the severity of the voids or the debonding. The feasibility of the methodology was analyzed using a finite-difference time-domain-based numerical simulation. Experiments were setup to validate the numerical results, which showed good agreement with the numerical findings. The results showed that the ultrasonic time-of-flight method is able to detect the concrete infill condition of CFFTs.
A novel electrocardiogram (ECG) signal de-noising and baseline wander correction method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold is proposed. Although CEEMDAN is based on empirical mode decomposition (EMD), it represents a significant improvement of the original EMD by overcoming the mode-mixing problem. However, there has been no previous study on using CEEMDAN to de-noise ECG signals, to the authors’ best knowledge. In the proposed method, the original noisy ECG signal is decomposed into a series of intrinsic mode functions (IMFs) sorted from high to low frequency by CEEMDAN. Each IMF is then analyzed by the autocorrelation method to find out the first few high frequency IMFs containing random noise, and these IMFs should be de-noised by the wavelet threshold. The zero-crossing rate (ZCR) of all IMFs, including final residue, are computed, and the IMFs with ZCR less than a certain value are removed. Finally, the remaining IMFs are reconstructed to obtain the clean ECG signal. The proposed algorithm is validated through experiments using the MIT–BIH ECG databases, and the results show that the random noise in the ECG signal can be effectively suppressed, and at the same time the baseline wander can be corrected efficiently.
In the process of pipeline structural health monitoring, it is necessary to detect pipe defects as well as to locate the defect's axial and circumferential positions. Axial locating of a pipeline defect can be achieved by identifying the defect reflection packets in the direct detected axial displacement time history signals. In practice, various kinds of noise are involved in the actual detection signal. Using the matching pursuit (MP) algorithm based on a custom overcomplete waveform dictionary, the noisy detection signal can be effectively de-noised, and the defect's axial position can be located. The time-reversal method used in a waveguide leads to temporal and spatial focusing, and this feature is used to locate the defect's circumferential position in the pipeline. In this paper, a new pipeline defect locating approach based on the time-reversal method and MP de-noising is proposed. The integration of the finite element method (FEM) numerical simulation with experiment is utilized to locate the pipeline defect. The defect axial position L x is located by the direct detected signal obtained from the actual pipeline defect detection experiment, after MP de-noising. A defect-free FEM reference model is established, and it has the same geometric and material parameters as the actual pipeline. Re-generating the time reversed defect reflection and the converted mode signals in the reference model, the energy will focus on the L x position. After obtaining the maximum values of the axial displacement time history signals received from the reference model at the L x position, the polar coordinate map based on these maxima can be plotted. The defect circumferential position is located based on the maximum values on the map. The FEM numerical simulation and experimental results are performed in this research. The defect locating results agree well with the actual pipeline defects, in both the axial and the circumferential directions.
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