scholarly journals Damage Identification of Prefabricated Reinforced Concrete Box Culvert Based on Improved Fuzzy Clustering Algorithm and Acoustic Emission Parameters

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yafeng Gong ◽  
Siyuan Lin ◽  
Feng He ◽  
Yang He ◽  
Jiaxiang Song
Keyword(s):  
Acoustic Emission ◽  
Road Safety ◽  
Clustering Algorithm ◽  
Damage Identification ◽  
Detection Method ◽  
Road Engineering ◽  
Original Algorithm ◽  
Box Culverts ◽  
Damage Process ◽  
Box Culvert

Prefabricated box culvert is a new structure in road engineering, whose health is very important to road safety. The use of acoustic emission (AE) as a detection method and the use of other improved algorithms to evaluate the damage of prefabricated box culverts are still insufficient. In this paper, two kinds of prefabricated box culverts are tested and studied, and the damage process of the box culverts is analysed based on the AE parameters of the box culvert using the traditional fuzzy C-means method (FCM). In addition, an improved algorithm based on the combination of grid density and distance (G-DFCM) was proposed, which was simulated and applied to the AE data analysis of the prefabricated box culvert. The research results show that the application effect of the G-DFCM algorithm is good, which not only overcomes the shortcomings of the original algorithm but also improves the effectiveness of the algorithm. This work can provide a supplement to the damage identification of fabricated box culverts.

Quantitative acoustic emission investigation on the crack evolution in concrete prisms by frequency analysis based on wavelet packet transform

2021 ◽  
pp. 147592172110188
Author(s):  
Zonglian Wang ◽  
Keqin Ding ◽  
Huilan Ren ◽  
Jianguo Ning
Keyword(s):  
Acoustic Emission ◽  
Frequency Band ◽  
Wavelet Packet ◽  
Strain Energy Release ◽  
Crack Size ◽  
Frequency Bands ◽  
Emission Signal ◽  
Damage Process ◽  
Concrete Materials ◽  
Stage 1

To gain an insight into the evolution of micro-cracks in concrete materials, a quantitative acoustic emission investigation on the damage process of concrete prisms subjected to three-point bending loading was performed. Each of the monitored acoustic emission signals was processed by a two-level wavelet packet decomposition into four different frequency bands (AA2, DA2, AD2, and DD2), and the energy coefficients R1, R2, R3, and R4 that parameterize their characteristic frequency bands were calculated. By analyzing variations in energy coefficients of the lowest frequency band (AA2), R1, and the energy coefficients of the highest frequency band (DD2), R4, the whole damage process was divided into three stages: crack initiation, crack growth, and crack coalescence. An inverse relationship between the frequency of the acoustic emission signal emitted by the propagating crack and the crack size in concrete materials was acquired based on the damage theory of brittle materials and the strain energy release theory. The statistical analysis results of the experimental data indicated that the average of R1 increased in turn, and the average of R4 correspondingly decreased in turn from Stage 1 to Stage 3. It revealed that the frequencies of acoustic emission signals decreased gradually with the evolution of the damage of concrete prisms, which is in a good agreement with the theoretical analysis result.

Acoustic emission waveforms for damage monitoring in composite materials: Shifting in spectral density, entropy and wavelet packet transform

2021 ◽  
pp. 147592172110446
Author(s):  
Claudia Barile ◽  
Caterina Casavola ◽  
Giovanni Pappalettera ◽  
Vimalathithan Paramsamy Kannan
Keyword(s):  
Acoustic Emission ◽  
Spectral Density ◽  
Flicker Noise ◽  
Wavelet Packet ◽  
Research Work ◽  
Wavelet Packet Transform ◽  
Spectral Energy ◽  
Emission Data ◽  
Cfrp Composites ◽  
Damage Process

Signal-based acoustic emission data are analysed in this research work for identifying the damage modes in carbon fibre–reinforced plastic (CFRP) composites. The research work is divided into three parts: analysis of the shifting in the spectral density of acoustic waveforms, use of waveform entropy for selecting the best wavelet and implementation of wavelet packet transform (WPT) for identifying the damage process. The first two methodologies introduced in this research work are novel. Shifting in the spectral density is introduced in analogous to ‘flicker noise’ which is popular in the field of waveform processing. The entropy-based wavelet selection is refined by using quadratic Renyi’s entropy and comparing the spectral energy of the dominating frequency band of the acoustic waveforms. Based on the method, ‘dmey’ wavelet is selected for analysing the waveforms using WPT. The slope values of the shifting in spectral density coincide with the results obtained from WPT in characterising the damage modes. The methodologies introduced in this research work are promising. They serve the purpose of identifying the damage process effectively in the CFRP composites.

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