Research on early weak structural damage detection of aeroengine intershaft bearing based on acoustic emission technology

2020 ◽  
pp. 147592172098035
Author(s):  
Zheming Liang ◽  
Anna Wang ◽  
Yang Yu ◽  
Ping Yang
Keyword(s):  
Acoustic Emission ◽  
Characteristic Frequency ◽  
Structural Damage ◽  
Outer Ring ◽  
Structure Damage ◽  
Ring Fault ◽  
Emission Signal ◽  
Aero Engine ◽  
Acoustic Emission Technology ◽  
Fault Characteristic

Until now, there is no effective method to detect the early weak structural damage of the aero engine intershaft bearing. In this article, an online method based on acoustic emission technology is used to detect the early weak structural damage of aeroengine intershaft bearing. The combination of maximum correlated kurtosis deconvolution and bandpass filter is proposed to enhance and denoise fault characteristic signals of the aero engine intershaft bearing. The Hilbert envelope demodulation is used to extracting the bear fault characteristic frequency. Under aeroengine working conditions, the experiment of an intershaft bearing with outer ring fault is carried out. The result shows that bearing outer ring fault characteristic frequency and bearing vibration frequencies clearly appear in the envelope spectrum of the acoustic emission signal. Therefore, online detection of early weak structure damage of aeroengine intershaft bearing is realized by acoustic emission technology under the background of strong noise.

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.

The Indication of Damage in Concrete by Amplitude-Frequency of Acoustic Emission Signal

2014 ◽  
Vol 638-640 ◽  
pp. 1436-1440
Author(s):  
Zhi Yu Jin ◽  
Qi Yin Shi ◽  
Qing Li ◽  
Fan Yang
Keyword(s):  
Acoustic Emission ◽  
Least Squares ◽  
Acoustic Emission Signal ◽  
Structural Damage ◽  
Least Squares Method ◽  
Regression Coefficients ◽  
Emission Signal ◽  
Empirical Function ◽  
Function Expression ◽  
Damage In Concrete

When the concrete is in the process of load, the curve of amplitude - frequency shows significant characteristic of exponential. As the load increases, the acoustic emission signals gradually become complete, the more obvious features of this exponential function. Using the least squares method, we can get an empirical function expression by fitting the data.Function expression has different regression coefficients in different load stages, and regression coefficients changing with load also presents certain rules, which has a good indication to qualitative process of structural damage.

scholarly journals Thermodynamic Approach for the Identification of Instability in the Wood Using Acoustic Emission Technology

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 534
Author(s):  
Qi Zhao ◽  
Dong Zhao ◽  
Jian Zhao
Keyword(s):  
Acoustic Emission ◽  
Propagation Distance ◽  
Image Correlation ◽  
Thermodynamic Approach ◽  
Wood Material ◽  
Emission Signal ◽  
Theoretical Support ◽  
Source Signal ◽  
Crack Tips ◽  
Acoustic Emission Technology

In order to monitor the crack growth of the wood material better and reduce failure risks, this paper studied the attenuation characteristics of acoustic emission signals in wood through pencil lead breaking (PLB) tests, in the aim of estimating the true amplitude value of the acoustic emission source signal. The tensile test of the double cantilever beam (DCB) specimens was used to simulate the crack tip growth within wood material, monitoring acoustic activity and location of crack tips within wood material using acoustic emission technology and digital image correlation (DIC). Results showed that the attenuation degree of acoustic emission signals increased exponentially as the propagation distance increased, and the relationship between relative amplitude attenuation rate and the propagation distance of the acoustic emission signal was established by the regression method, which provides the input parameters for the establishment of the crack instability prediction model in the next step. Based on a thermodynamic approach, a theoretical model for predicting crack instability was established, and the model was verified by DCB tests. The model uses acoustic emission parameters as the basis for judging whether the crack is instable. It provides theoretical support for the application of acoustic emission technology in wood health monitoring.

Diagnostic Testing on Crack Propagation of Asphalt Pavement Materials

2015 ◽  
Vol 667 ◽  
pp. 396-401
Author(s):  
Gang Shen ◽  
Xin Qiu ◽  
Jue Qiang Tao ◽  
Ning Da Du ◽  
Yong Ju Hu
Keyword(s):  
Acoustic Emission ◽  
Crack Propagation ◽  
Acoustic Emission Signal ◽  
Asphalt Concrete ◽  
Concrete Pavement ◽  
Analysis Method ◽  
Emission Signal ◽  
Pavement Structure ◽  
Asphalt Concrete Pavement ◽  
Acoustic Emission Technology

Asphalt concrete is a typical road building material of advanced asphalt pavements. Under the reciprocating vehicle loading, fatigue cracks are reduced inevitably, which seriously affect road performance. Therefore, effective detection and diagnosis of fatigue crack propagation has become a hot research issue. Acoustic emission detection test is a new dynamic nondestructive testing technology which has some features of real-time, online and overall detection. The main purpose of this paper systematically analyses the development process of acoustic emission technology applied in health monitoring field of asphalt concrete pavement structure, and to state the acoustic emission source localization principle, the parameters of acoustic emission signal analysis method, the acoustic emission signal waveform analysis method, etc. Furthermore, from the aspects of the asphalt concrete fatigue performance, crack evolution process and positioning technology, this paper fundamentally discuss the future technological development prospect of acoustic emission technology which is applied in the field of monitoring and diagnosis of asphalt concrete pavement structure, and provide a new perspective for the whole dynamic maintenance of road , and the information implementation of pavement maintenance strategies at later stage.

scholarly journals Acoustic Emission Detection and Analysis Method for Health Status of Lithium Ion Batteries

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 712
Author(s):  
Kai Zhang ◽  
Jianxiang Yin ◽  
Yunze He
Keyword(s):  
Acoustic Emission ◽  
Lithium Ion Batteries ◽  
Stress Wave ◽  
Acoustic Emission Signal ◽  
Lithium Ion ◽  
Emission Measurement ◽  
Emission Signal ◽  
Pulse Type ◽  
Number Of Cycles ◽  
Acoustic Emission Technology

The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries.

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

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