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.

scholarly journals Acoustic Emission Wavelet Analysis of Filament Wound Composite Tube Fatigue Damage Process

2015 ◽  
Vol 9 (1) ◽  
pp. 214-219 ◽  
Author(s):  
Su Hua ◽  
Chang Cheng
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Fatigue Damage ◽  
Frequency Band ◽  
Low Frequency ◽  
High Signal ◽  
Wave Form ◽  
Radial Compression ◽  
Time Frequency ◽  
Emission Signal

This paper performed a radial compression fatigue test on glass fiber winding composite tubes, collected acoustic emission signals at different fatigue damages stages, used time frequency analysis techniques for modern wavelet transform, and analyzed the wave form and frequency characteristics of fatigue damaged acoustic emission signals. Three main frequency bands of acoustic emission signal had been identified: 80-160 kHz (low frequency band), 160-300 kHz (middle frequency band), and over 300kHz (high frequency band), corresponding to the three basic damage modes: the fragmentation of matrix resin, the layered damage of fiber and matrix, and the fracture of cellosilk respectively. The usage of wavelet transform enabled the separation of fatigue damaged acoustic emission signals from interference wave, and the access to characteristics of high signal-noise-ratio fatigue damage.

Based on Multi-Sensor Tool Steel Hard Turning Process Monitoring and Controlling

2010 ◽  
Vol 108-111 ◽  
pp. 549-555 ◽  
Author(s):  
Fei Wu ◽  
Xi Wang ◽  
Wei Wu Zhong ◽  
Hui Yu ◽  
Li Bing Liu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Virtual Instrument ◽  
Hard Turning ◽  
Wavelet Packet ◽  
Signal Acquisition ◽  
Turning Process ◽  
Cooling Fluid ◽  
Emission Signal ◽  
Temperature Signal

Through a set of electro-hydraulic digital valve as the core of the fuzzy control system to provide an appropriate amount of cooling fluid, the hard turning process temperature can be controlled at any set temperature. The use of the signal acquisition system based on virtual instrument, acquisition acoustic emission signals, vibration signals and temperature signals during the hard turning process. The temperature signal is processed by wavelet transform ,after vibration and acoustic emission signals be processed by wavelet packet decomposition and energy method, it is found that through providing appropriate cooling fluid can control temperatures in the processing and decrease the amplitude of vibration and acoustic emission signal, it also means that we can improve the quality of processing, and prolong the life of tool.

Wavelet Packet analyses of Acoustic Emission Signal for Tool Wear in High Speed Milling

2013 ◽  
Vol 589-590 ◽  
pp. 600-605
Author(s):  
Shun Xing Wu ◽  
Peng Nan Li ◽  
Zhi Hui Yan ◽  
Li Na Zhang ◽  
Xin Yi Qiu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Acoustic Emission Signal ◽  
High Speed ◽  
Feature Vector ◽  
Wavelet Packet ◽  
High Speed Milling ◽  
Band Energy ◽  
Emission Signal ◽  
Frequency Band Energy

Tool wear condition monitoring technology is one of the main parts of advanced manufacturing technology and is a hot research direction in recent years. A method based on the characteristics of acoustic emission signal and the advantages of wavelet packets decomposition theory in the non-stationary signal feature extraction is proposed for tool wear state monitoring with monitor the change of acoustic emission signal feature vector. In this paper, through the method, firstly, acoustic emission signal were decomposed into 4 layers with wavelet packet analysis, secondly, the frequency band energy of the have been decomposed signal were extracted, thirdly, the frequency band energy that are sensitive to tool wear were selected as feature vector, and then the corresponding relation between feature vector and tool wear was established , finally, the state of the tool wear can be distinguished according to the change of feature vector. The results show that this method can be feasibility used to monitor tool wear state in high speed milling.

scholarly journals Experimental Study on Influence of Borehole Arrangement on Energy Conversion and Acoustic Characteristics of Coal-Like Material Sample

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Chuanbo Hao ◽  
Zhiyuan Hou ◽  
Fukun Xiao ◽  
Gang Liu
Keyword(s):  
Acoustic Emission ◽  
Energy Conversion ◽  
Frequency Band ◽  
Acoustic Emission Signal ◽  
Conversion Ratio ◽  
Acoustic Characteristics ◽  
Band Energy ◽  
Emission Signal ◽  
Material Sample ◽  
Frequency Band Energy

This paper examines the effects of borehole arrangement on the failure process of coal-like materials based on its energy conversion and acoustic characteristics from the perspectives of energy, AE energy, AE spectrum, and frequency band. Findings from the study revealed that the presence of borehole can significantly reduce the conversion ratio and growth rate of elastic energy during the loading of coal-like material sample and delay the release of internal energy of the sample. Also, it can reduce the frequency band energy of the main frequency of acoustic emission signal but has little effect on the size and richness of the peak frequency of acoustic emission signal. The practice that makes drilling diameter and depth increase stepwise can minimize the elastic energy conversion ratio, the growth rate, and the main frequency band energy of acoustic emission signal of coal-like material sample and postpone the internal energy release of the sample to the greatest extent, so as to enrich the richness of the secondary frequency of acoustic emission signal. The results of this study have certain guiding significance for the layout of pressure relief boreholes in the production process of coal mines.

Research of Acoustic Emission Signal De-Noising Based on Lifting Wavelet Packet

2011 ◽  
Vol 143-144 ◽  
pp. 622-626
Author(s):  
X.J. Li ◽  
Z. Q. Deng ◽  
L. L. Jiang ◽  
P Li ◽  
K. F He
Keyword(s):  
Acoustic Emission ◽  
Characteristic Frequency ◽  
Wavelet Packet ◽  
Noise Signal ◽  
Emission Signal ◽  
Feature Information ◽  
Weak Fault ◽  
Lifting Wavelet ◽  
Ae Signals ◽  
Fault Characteristic

Aiming at the extraction of failure character signal for early acoustic emission (AE) signals, a method to combine lifting wavelet packet with spectrum zoom technology is developed. Using lifting wavelet packet de-noising method, not only filters the noise signal, but also retains the feature information. After the signals de-noising, combining the envelope demodulation analysis with the spectrum zoom technology, which can effective extract the weak fault characteristic frequency The result of simulated signals and experimental signals shows that the proposed method has better noise reduction with a higher signal noise ratio (SNR) and lower mean square error (MSE), and it can successfully extract the fault characteristic frequency of rotating machinery early AE signals.

Acoustic Emission Analysis of Fracture Events in Cu Films with W Overlayers

1999 ◽  
Vol 563 ◽  
Author(s):  
Alex A. Volinsky ◽  
William W. Gerberich
Keyword(s):  
Acoustic Emission ◽  
Energy Release ◽  
Strain Energy ◽  
Strain Energy Release ◽  
Crack Arrest ◽  
Work Of Adhesion ◽  
Emission Analysis ◽  
Cu Films ◽  
Plastic Energy ◽  
Emission Signal

AbstractIndentation-induced delamination of thin films provides the basis for adhesion calculations. In the case of ductile Cu films plastic deformation usually prevents a film from debonding from the substrate. Deadhesion is facilitated by the use of a hard W superlayer, which promotes indenter-induced Cu film failure, increasing the delamination area by an order of magnitude. Radial as well as annular cracking acts like a secondary mechanism in the strain energy release, and can be resolved from excursions on the load-displacement curves. For the thicker Cu films no excursions were observed, though radial cracking took place. It is important to identify fracture events as they occur in order to understand the system behavior and accurately apply the analysis. An acoustic emission signal is used to detect the magnitude of fracture events in thin Cu films. For the films of different thickness from 40 nm to 3 microns the corresponding interfacial fracture energy ranged from 0.2 to over 100 J/m2. Limits of plastic energy dissipation are determined with the lower limit, the true work of adhesion, being associated with a dislocation emission criterion. Crack arrest marks were found upon the blister removal, and are proposed to represent the shape of the crack tip. Total acoustic emission energy was found to be inversely proportional to the strain energy release rate.

The EMD Analysis AE Signals of Rock Failure under Uniaxial Compression

2014 ◽  
Vol 571-572 ◽  
pp. 845-852
Author(s):  
Tian Jun Zhang ◽  
Sheng Hong Yu ◽  
Jin Hu Ren ◽  
Wei Cui
Keyword(s):  
Acoustic Emission ◽  
Uniaxial Compression ◽  
Acoustic Emission Signal ◽  
Wavelet Packet ◽  
Testing Machine ◽  
Waveform Analysis ◽  
Mode Analysis ◽  
Emission Signal ◽  
Mode Decomposition ◽  
Emd Method

The wavelet packet basis is difficult to be extracted by wavelet analysis at present. To solve this problem, an experiment of Acoustic Emission under uniaxial compression is conducted by SAEU2S acoustic Emission system and Electro-hydraulic servo universal testing machine and the method of empirical mode analysis is adopted to explore the acoustic emission signal in this paper. Firstly with the method of empirical mode decomposition, the acoustic emission signal is decomposed into the forms of intrinsic mode function with several local time scale and residual components, and then these data is analyzed. After the noise-reducing IMF and residual components are refactored, the error between the final and the initial reconstruction signals is less than 10-6. The experiment indicates that the EMD method is effective in processing the local rock acoustic emission signals. The EMD method also provides an efficient way to predict deformation trend of rock damage through deformation of waveform analysis.

Research on Feature Extraction Experiment for Acoustic Emission Signal of Rotor Crack Fault

2010 ◽  
Vol 34-35 ◽  
pp. 1005-1009 ◽  
Author(s):  
Kuan Fang He ◽  
Xue Jun Li ◽  
X.C. Li
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Acoustic Emission Signal ◽  
Wavelet Packet ◽  
Fault Simulation ◽  
Early Period ◽  
Test Bed ◽  
Simulation Test ◽  
Emission Signal ◽  
Extraction Experiment

The acoustic emission extraction experiment of rotor crack fault has done on the rotor comprehensive fault simulation test-bed. Characteristics of acoustic emission signal of different crack rotors in various depth and conditions are analyzed. The noise-disturbing problems and the noise-eliminating methods of the acoustic emission signal were researched in the paper, and the comparison has been done with the vibration method of crack fault diagnosis by the experiment. The advantages of acoustic emission technique has been highlighted in the early period crack fault diagnosis. The wavelet packet technique was applied to obtain the characteristics of acoustic emission signal of the rotor crack propagation. the diagnosis results are shown to be quite clear, reliable and accurate.

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